Amazon DynamoDB Developer Guide

Below you will find brief information for DynamoDB. Amazon DynamoDB is a fully managed NoSQL database service. It provides fast and predictable performance with seamless scalability. Learn how to create tables, load data, and perform CRUD operations.
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Amazon DynamoDB
Developer Guide
API Version 2012-08-10
Amazon DynamoDB Developer Guide
Amazon DynamoDB: Developer Guide
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Amazon DynamoDB Developer Guide
Table of Contents
What Is Amazon DynamoDB? ............................................................................................................... 1
How It Works ............................................................................................................................ 2
Core Components .............................................................................................................. 2
The DynamoDB API ............................................................................................................ 9
Naming Rules and Data Types ........................................................................................... 11
Read Consistency ............................................................................................................. 15
Throughput Capacity ........................................................................................................ 15
Partitions and Data Distribution ......................................................................................... 18
From SQL to NoSQL ................................................................................................................. 20
SQL or NoSQL? ................................................................................................................ 21
Accessing the Database ..................................................................................................... 22
Creating a Table ............................................................................................................... 24
Getting Information About a Table ..................................................................................... 26
Writing Data To a Table .................................................................................................... 27
Reading Data From a Table ............................................................................................... 29
Managing Indexes ............................................................................................................. 34
Modifying Data in a Table ................................................................................................. 37
Deleting Data from a Table ............................................................................................... 38
Removing a Table ............................................................................................................. 39
Setting Up DynamoDB ...................................................................................................................... 41
Setting Up DynamoDB Local (Downloadable Version) .................................................................... 41
Downloading and Running DynamoDB on Your Computer ..................................................... 41
Setting the Local Endpoint ................................................................................................ 44
Usage Notes .................................................................................................................... 44
Setting Up DynamoDB (Web Service) .......................................................................................... 46
Signing Up for AWS .......................................................................................................... 46
Getting an AWS Access Key ............................................................................................... 46
Conﬁguring Your Credentials ............................................................................................. 47
Accessing DynamoDB ........................................................................................................................ 48
Using the Console .................................................................................................................... 48
Using the CLI ........................................................................................................................... 49
Downloading and Conﬁguring the AWS CLI ......................................................................... 49
Using the AWS CLI with DynamoDB .................................................................................... 49
Using the AWS CLI with Downloadable DynamoDB ............................................................... 50
Using the API .......................................................................................................................... 51
Getting Started with DynamoDB ........................................................................................................ 52
Java and DynamoDB ................................................................................................................. 52
Prerequisites .................................................................................................................... 53
Step 1: Create a Table ...................................................................................................... 53
Step 2: Load Sample Data ................................................................................................. 54
Step 3: Create, Read, Update, and Delete an Item ................................................................. 57
Step 4: Query and Scan the Data ....................................................................................... 64
Step 5: (Optional) Delete the Table .................................................................................... 68
Summary ........................................................................................................................ 68
JavaScript and DynamoDB ......................................................................................................... 69
Prerequisites .................................................................................................................... 69
Step 1: Create a Table ...................................................................................................... 70
Step 2: Load Sample Data ................................................................................................. 72
Step 3: Create, Read, Update, and Delete an Item ................................................................. 74
Step 4: Query and Scan the Data ....................................................................................... 83
Step 5: (Optional): Delete the Table .................................................................................... 87
Summary ........................................................................................................................ 88
Node.js and DynamoDB ............................................................................................................. 89
Prerequisites .................................................................................................................... 89
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Step 1: Create a Table ...................................................................................................... 89
Step 2: Load Sample Data ................................................................................................. 90
Step 3: Create, Read, Update, and Delete an Item ................................................................. 92
Step 4: Query and Scan the Data ....................................................................................... 99
Step 5: (Optional): Delete the Table .................................................................................. 102
Summary ....................................................................................................................... 103
.NET and DynamoDB ............................................................................................................... 103
Prerequisites .................................................................................................................. 104
Step 1: Create a Table ..................................................................................................... 104
Step 2: Load Sample Data ............................................................................................... 106
Step 3: Create, Read, Update, and Delete an Item ............................................................... 109
Step 4: Query and Scan the Data ..................................................................................... 122
Step 5: (Optional) Delete the Table ................................................................................... 130
Summary ....................................................................................................................... 131
PHP and DynamoDB ............................................................................................................... 132
Prerequisites .................................................................................................................. 132
Step 1: Create a Table ..................................................................................................... 132
Step 2: Load Sample Data ............................................................................................... 134
Step 3: Create, Read, Update, and Delete an Item ............................................................... 136
Step 4: Query and Scan the Data ..................................................................................... 144
Step 5: (Optional) Delete the Table ................................................................................... 148
Summary ....................................................................................................................... 149
Python and DynamoDB ........................................................................................................... 149
Prerequisites .................................................................................................................. 150
Step 1: Create a Table ..................................................................................................... 150
Step 2: Load Sample Data ............................................................................................... 151
Step 3: Create, Read, Update, and Delete an Item ............................................................... 153
Step 4: Query and Scan the Data ..................................................................................... 160
Step 5: (Optional) Delete the Table ................................................................................... 163
Summary ....................................................................................................................... 164
Ruby and DynamoDB .............................................................................................................. 164
Prerequisites .................................................................................................................. 164
Step 1: Create a Table ..................................................................................................... 165
Step 2: Load Sample Data ............................................................................................... 166
Step 3: Create, Read, Update, and Delete an Item ............................................................... 168
Step 4: Query and Scan the Data ..................................................................................... 174
Step 5: (Optional) Delete the Table ................................................................................... 178
Summary ....................................................................................................................... 179
Programming with DynamoDB ......................................................................................................... 180
Overview of AWS SDK Support for DynamoDB ........................................................................... 180
Programmatic Interfaces .......................................................................................................... 182
Low-Level Interfaces ....................................................................................................... 182
Document Interfaces ....................................................................................................... 183
Object Persistence Interface ............................................................................................. 184
DynamoDB Low-Level API ....................................................................................................... 185
Request Format .............................................................................................................. 187
Response Format ............................................................................................................ 187
Data Type Descriptors ..................................................................................................... 188
Numeric Data ................................................................................................................. 188
Binary Data .................................................................................................................... 189
Error Handling ....................................................................................................................... 189
Error Components .......................................................................................................... 189
Error Messages and Codes ............................................................................................... 190
Error Handling in Your Application .................................................................................... 192
Error Retries and Exponential Backoﬀ ............................................................................... 193
Batch Operations and Error Handling ................................................................................ 194
Higher-Level Programming Interfaces for DynamoDB .................................................................. 194
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Java: DynamoDBMapper .................................................................................................. 195
.NET: Document Model .................................................................................................... 232
.NET: Object Persistence Model ........................................................................................ 253
Running the Code Samples ...................................................................................................... 280
Load Sample Data .......................................................................................................... 280
Java Code Samples ......................................................................................................... 285
.NET Code Samples ......................................................................................................... 287
Working with DynamoDB ................................................................................................................ 290
Working with Tables ............................................................................................................... 290
Basic Operations for Tables ............................................................................................. 291
Throughput Settings for Reads and Writes ......................................................................... 294
Item Sizes and Capacity Unit Consumption ........................................................................ 296
Managing Throughput Capacity with Auto Scaling .............................................................. 298
Tagging for DynamoDB ................................................................................................... 314
Working with Tables: Java .............................................................................................. 316
Working with Tables: .NET ............................................................................................... 321
Working with Items ................................................................................................................ 327
Reading an Item ............................................................................................................. 328
Writing an Item .............................................................................................................. 329
Return Values ................................................................................................................. 331
Batch Operations ............................................................................................................ 331
Atomic Counters ............................................................................................................. 333
Conditional Writes .......................................................................................................... 334
Using Expressions in DynamoDB ....................................................................................... 338
Time To Live .................................................................................................................. 362
Working with Items: Java ................................................................................................ 368
Working with Items: .NET ................................................................................................ 387
Working with Queries ............................................................................................................. 410
Key Condition Expression ................................................................................................. 410
Filter Expressions for Query ............................................................................................. 412
Limiting the Number of Items in the Result Set .................................................................. 413
Paginating the Results .................................................................................................... 413
Counting the Items in the Results ..................................................................................... 414
Capacity Units Consumed by Query ................................................................................... 414
Read Consistency for Query ............................................................................................. 415
Querying: Java ............................................................................................................... 415
Querying: .NET ............................................................................................................... 420
Working with Scans ................................................................................................................ 427
Filter Expressions for Scan ............................................................................................... 427
Limiting the Number of Items in the Result Set .................................................................. 428
Paginating the Results .................................................................................................... 428
Counting the Items in the Results ..................................................................................... 429
Capacity Units Consumed by Scan .................................................................................... 429
Read Consistency for Scan ............................................................................................... 430
Parallel Scan .................................................................................................................. 430
Scanning: Java ............................................................................................................... 431
Scanning: .NET ............................................................................................................... 438
Working with Indexes .............................................................................................................. 446
Global Secondary Indexes ................................................................................................ 448
Local Secondary Indexes .................................................................................................. 484
Working with Streams ............................................................................................................. 518
Endpoints for DynamoDB Streams .................................................................................... 519
Enabling a Stream .......................................................................................................... 520
Reading and Processing a Stream ..................................................................................... 521
DynamoDB Streams and Time To Live ............................................................................... 523
Using the DynamoDB Streams Kinesis Adapter to Process Stream Records .............................. 523
Walkthrough: DynamoDB Streams Low-Level API ............................................................... 534
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Cross-Region Replication .................................................................................................
DynamoDB Streams and AWS Lambda Triggers ..................................................................
In-Memory Acceleration with DAX ....................................................................................................
Use Cases for DAX ..................................................................................................................
Usage Notes ..........................................................................................................................
Concepts ...............................................................................................................................
How DAX Processes Requests ...........................................................................................
Item Cache ....................................................................................................................
Query Cache ..................................................................................................................
DAX Cluster Components .........................................................................................................
Nodes ...........................................................................................................................
Clusters .........................................................................................................................
Regions and Availability Zones .........................................................................................
Parameter Groups ...........................................................................................................
Security Groups ..............................................................................................................
Cluster ARN ...................................................................................................................
Cluster Endpoint .............................................................................................................
Node Endpoints ..............................................................................................................
Subnet Groups ...............................................................................................................
Events ...........................................................................................................................
Maintenance Window ......................................................................................................
Creating a DAX Cluster ............................................................................................................
Creating a DAX Service Role ............................................................................................
AWS CLI ........................................................................................................................
AWS Management Console ..............................................................................................
DAX and DynamoDB Consistency Models ...................................................................................
Consistency Among DAX Cluster Nodes .............................................................................
DAX Item Cache Behavior ................................................................................................
DAX Query Cache Behavior ..............................................................................................
Strongly Consistent Reads ...............................................................................................
Negative Caching ............................................................................................................
Strategies for Writes .......................................................................................................
Using the DAX SDK For Java in an Application ...........................................................................
Tutorial: Running a Sample Application .............................................................................
Modifying an Existing Application to Use DAX ....................................................................
Managing DAX Clusters ...........................................................................................................
IAM Permissions for Managing a DAX Cluster .....................................................................
Customizing DAX Cluster Settings .....................................................................................
Conﬁguring TTL Settings .................................................................................................
Tagging Support for DAX ................................................................................................
AWS CloudTrail Integration ..............................................................................................
Deleting a DAX Cluster ....................................................................................................
DAX Access Control .................................................................................................................
IAM Service Role for DAX ................................................................................................
IAM Policy to Allow DAX Cluster Access .............................................................................
Case Study: Accessing DynamoDB and DAX ........................................................................
Access to DynamoDB, But No Access With DAX ...................................................................
Access to DynamoDB and to DAX .....................................................................................
Access to DynamoDB Via DAX, But No Direct Access to DynamoDB ........................................
DAX API Reference ..................................................................................................................
Authentication and Access Control ....................................................................................................
Authentication .......................................................................................................................
Access Control ........................................................................................................................
Overview of Managing Access ..................................................................................................
Amazon DynamoDB Resources and Operations ...................................................................
Understanding Resource Ownership ..................................................................................
Managing Access to Resources .........................................................................................
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Specifying Policy Elements: Actions, Eﬀects, and Principals ..................................................
Specifying Conditions in a Policy ......................................................................................
Using Identity-Based Policies (IAM Policies) ................................................................................
Console Permissions ........................................................................................................
AWS Managed (Predeﬁned) Policies for Amazon DynamoDB .................................................
Customer Managed Policy Examples .................................................................................
DynamoDB API Permissions Reference ......................................................................................
Related Topics ................................................................................................................
Using Conditions ....................................................................................................................
Overview .......................................................................................................................
Specifying Conditions: Using Condition Keys ......................................................................
Related Topics ................................................................................................................
Using Web Identity Federation .................................................................................................
Additional Resources for Web Identity Federation ...............................................................
Example Policy for Web Identity Federation .......................................................................
Preparing to Use Web Identity Federation .........................................................................
Writing Your App to Use Web Identity Federation ...............................................................
Monitoring DynamoDB ....................................................................................................................
Monitoring Tools ....................................................................................................................
Automated Tools ............................................................................................................
Manual Tools .................................................................................................................
Monitoring with Amazon CloudWatch .......................................................................................
Metrics and Dimensions ...................................................................................................
Using Metrics .................................................................................................................
Creating Alarms ..............................................................................................................
Logging DynamoDB Operations by Using AWS CloudTrail ............................................................
DynamoDB Information in CloudTrail ................................................................................
Understanding DynamoDB Log File Entries ........................................................................
Best Practices for DynamoDB ...........................................................................................................
Table Best Practices ................................................................................................................
Item Best Practices .................................................................................................................
Query and Scan Best Practices .................................................................................................
Local Secondary Index Best Practices ........................................................................................
Global Secondary Index Best Practices ......................................................................................
Best Practices for Tables ..........................................................................................................
Design For Uniform Data Access Across Items In Your Tables ................................................
Understand Partition Behavior .........................................................................................
Use Burst Capacity Sparingly ...........................................................................................
Distribute Write Activity During Data Upload .....................................................................
Understand Access Patterns for Time Series Data ...............................................................
Cache Popular Items .......................................................................................................
Consider Workload Uniformity When Adjusting Provisioned Throughput ................................
Test Your Application At Scale .........................................................................................
Best Practices for Items ...........................................................................................................
Use One-to-Many Tables Instead Of Large Set Attributes .....................................................
Compress Large Attribute Values ......................................................................................
Store Large Attribute Values in Amazon S3 ........................................................................
Break Up Large Attributes Across Multiple Items ................................................................
Best Practices for Querying and Scanning Data ..........................................................................
Performance Considerations for Scans ...............................................................................
Avoid Sudden Spikes in Read Activity ................................................................................
Take Advantage of Parallel Scans .....................................................................................
Best Practices for Local Secondary Indexes ................................................................................
Use Indexes Sparingly .....................................................................................................
Choose Projections Carefully ............................................................................................
Optimize Frequent Queries To Avoid Fetches .....................................................................
Take Advantage of Sparse Indexes ....................................................................................
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Watch For Expanding Item Collections ..............................................................................
Best Practices for Global Secondary Indexes ..............................................................................
Choose a Key That Will Provide Uniform Workloads ............................................................
Take Advantage of Sparse Indexes ....................................................................................
Use a Global Secondary Index For Quick Lookups ...............................................................
Create an Eventually Consistent Read Replica .....................................................................
Integrating with Other AWS Services ................................................................................................
Amazon VPC Endpoints for DynamoDB .....................................................................................
Tutorial: Using a VPC Endpoint for DynamoDB ...................................................................
Integrating with Amazon Cognito .............................................................................................
Integrating with Amazon Redshift ............................................................................................
Integrating with Amazon EMR ..................................................................................................
Overview .......................................................................................................................
Tutorial: Working with Amazon DynamoDB and Apache Hive ................................................
Creating an External Table in Hive ....................................................................................
Processing HiveQL Statements .........................................................................................
Querying Data in DynamoDB ...........................................................................................
Copying Data to and from Amazon DynamoDB ..................................................................
Performance Tuning ........................................................................................................
Integrating with Amazon Data Pipeline .....................................................................................
Prerequisites to Export and Import Data ............................................................................
Exporting Data From DynamoDB to Amazon S3 .................................................................
Importing Data From Amazon S3 to DynamoDB .................................................................
Troubleshooting .............................................................................................................
Predeﬁned Templates for AWS Data Pipeline and DynamoDB ...............................................
Limits in DynamoDB .......................................................................................................................
Capacity Units and Provisioned Throughput ...............................................................................
Capacity Unit Sizes .........................................................................................................
Provisioned Throughput Default Limits ..............................................................................
Increasing Provisioned Throughput ...................................................................................
Decreasing Provisioned Throughput ..................................................................................
Tables ...................................................................................................................................
Table Size ......................................................................................................................
Tables Per Account .........................................................................................................
Secondary Indexes ..................................................................................................................
Secondary Indexes Per Table ............................................................................................
Projected Secondary Index Attributes Per Table ..................................................................
Partition Keys and Sort Keys ....................................................................................................
Partition Key Length .......................................................................................................
Partition Key Values ........................................................................................................
Sort Key Length .............................................................................................................
Sort Key Values ..............................................................................................................
Naming Rules .........................................................................................................................
Table Names and Secondary Index Names .........................................................................
Attribute Names .............................................................................................................
Data Types ............................................................................................................................
String ............................................................................................................................
Number .........................................................................................................................
Binary ...........................................................................................................................
Items ....................................................................................................................................
Item Size .......................................................................................................................
Item Size for Tables With Local Secondary Indexes .............................................................
Attributes ..............................................................................................................................
Attribute Name-Value Pairs Per Item .................................................................................
Number of Values in List, Map, or Set ...............................................................................
Attribute Values .............................................................................................................
Nested Attribute Depth ...................................................................................................
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Expression Parameters ............................................................................................................
Lengths .........................................................................................................................
Operators and Operands .................................................................................................
Reserved Words ..............................................................................................................
DynamoDB Streams ................................................................................................................
Simultaneous Readers of a Shard in DynamoDB Streams .....................................................
Maximum Write Capacity for a Table With a Stream Enabled ................................................
DynamoDB Accelerator (DAX) ...................................................................................................
AWS Region Availability ..................................................................................................
Nodes ...........................................................................................................................
Parameter Groups ...........................................................................................................
Subnet Groups ...............................................................................................................
API-Speciﬁc Limits ..................................................................................................................
Appendix .......................................................................................................................................
Example Tables and Data ........................................................................................................
Sample Data Files ...........................................................................................................
Creating Example Tables and Uploading Data ............................................................................
Creating Example Tables and Uploading Data - Java ...........................................................
Creating Example Tables and Uploading Data - .NET ...........................................................
Example Application Using AWS SDK for Python (Boto) ...............................................................
Step 1: Deploy and Test Locally .......................................................................................
Step 2: Examine the Data Model and Implementation Details ...............................................
Step 3: Deploy in Production ...........................................................................................
Step 4: Clean Up Resources .............................................................................................
Amazon DynamoDB Storage Backend for Titan ..........................................................................
Reserved Words in DynamoDB .................................................................................................
Legacy Conditional Parameters ................................................................................................
AttributesToGet ..............................................................................................................
AttributeUpdates ............................................................................................................
ConditionalOperator .......................................................................................................
Expected .......................................................................................................................
KeyConditions ................................................................................................................
QueryFilter ....................................................................................................................
ScanFilter ......................................................................................................................
Writing Conditions With Legacy Parameters .......................................................................
Current Low-Level API Version (2012-08-10) ..............................................................................
Previous Low-Level API Version (2011-12-05) ............................................................................
BatchGetItem .................................................................................................................
BatchWriteItem ..............................................................................................................
CreateTable ....................................................................................................................
DeleteItem .....................................................................................................................
DeleteTable ....................................................................................................................
DescribeTables ...............................................................................................................
GetItem .........................................................................................................................
ListTables ......................................................................................................................
PutItem .........................................................................................................................
Query ............................................................................................................................
Scan ..............................................................................................................................
UpdateItem ....................................................................................................................
UpdateTable ..................................................................................................................
Document History ..........................................................................................................................
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What Is Amazon DynamoDB?
Welcome to the Amazon DynamoDB Developer Guide.
Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable
performance with seamless scalability. DynamoDB lets you oﬄoad the administrative burdens
of operating and scaling a distributed database, so that you don't have to worry about hardware
provisioning, setup and conﬁguration, replication, software patching, or cluster scaling.
With DynamoDB, you can create database tables that can store and retrieve any amount of data, and
serve any level of request traﬃc. You can scale up or scale down your tables' throughput capacity
without downtime or performance degradation, and use the AWS Management Console to monitor
resource utilization and performance metrics.
DynamoDB allows you to delete expired items from tables automatically to help you reduce storage
usage and the cost of storing data that is no longer relevant. For more information, see Time To
Live (p. 362).
DynamoDB automatically spreads the data and traﬃc for your tables over a suﬃcient number of
servers to handle your throughput and storage requirements, while maintaining consistent and fast
performance. All of your data is stored on solid state disks (SSDs) and automatically replicated across
multiple Availability Zones in an AWS region, providing built-in high availability and data durability.
We recommend that you begin by reading the following sections:
• Amazon DynamoDB: How It Works (p. 2)—To learn essential DynamoDB concepts.
• Setting Up DynamoDB (p. 41)—To learn how to setup DynamoDB (Downloadable Version or Web
Service).
• Accessing DynamoDB (p. 48)—To learn how to access DynamoDB using the console, CLI, or API.
To get started quickly with DynamoDB, see Getting Started with DynamoDB (p. 52).
To learn more about application development see the following:
• Programming with DynamoDB and the AWS SDKs (p. 180)
• Working with DynamoDB (p. 290)
To quickly ﬁnd recommendations for maximizing performance and minimizing throughput costs see
Best Practices for DynamoDB (p. 658). To learn how to tag DynamoDB resources see Tagging for
DynamoDB (p. 314).
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How It Works
For best practices, how-to guides and tools, be sure to check the DynamoDB Developer Resources page:
http://aws.amazon.com/dynamodb/developer-resources/.
You can use AWS Database Migration Service to migrate data from a Relational Database or MongoDB
to an Amazon DynamoDB table. For more information, see AWS Database Migration Service User
Guide. To learn how to use MongoDB as a migration source, see Using MongoDB as a Source for AWS
Database Migration Service. To learn how to use DynamoDB as a migration target, see Using an Amazon
DynamoDB Database as a Target for AWS Database Migration Service.
Amazon DynamoDB: How It Works
The following sections provide an overview of Amazon DynamoDB service components and how they
interact.
After you read this introduction, try working through the Creating Tables and Loading Sample
Data (p. 280) section, which walks you through the process of creating sample tables, uploading data,
and performing some basic database operations.
For language-speciﬁc tutorials with sample code, see Getting Started with DynamoDB (p. 52).
Topics
• DynamoDB Core Components (p. 2)
• The DynamoDB API (p. 9)
• Naming Rules and Data Types (p. 11)
• Read Consistency (p. 15)
• Throughput Capacity for Reads and Writes (p. 15)
• Partitions and Data Distribution (p. 18)
DynamoDB Core Components
In DynamoDB, tables, items, and attributes are the core components that you work with. A table is a
collection of items, and each item is a collection of attributes. DynamoDB uses primary keys to uniquely
identify each item in a table and secondary indexes to provide more querying ﬂexibility. You can use
DynamoDB Streams to capture data modiﬁcation events in DynamoDB tables.
There are limits in DynamoDB. For more information, see Limits in DynamoDB (p. 724).
Topics
• Tables, Items, and Attributes (p. 2)
• Primary Key (p. 5)
• Secondary Indexes (p. 5)
• DynamoDB Streams (p. 8)
Tables, Items, and Attributes
The following are the basic DynamoDB components:
• Tables – Similar to other database systems, DynamoDB stores data in tables. A table is a collection of
data. For example, see the example table called People that you could use to store personal contact
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Core Components
information about friends, family, or anyone else of interest. You could also have a Cars table to store
information about vehicles that people drive.
• Items – Each table contains multiple items. An item is a group of attributes that is uniquely identiﬁable
among all of the other items. In a People table, each item represents a person. For a Cars table, each
item represents one vehicle. Items in DynamoDB are similar in many ways to rows, records, or tuples
in other database systems. In DynamoDB, there is no limit to the number of items you can store in a
table.
• Attributes – Each item is composed of one or more attributes. An attribute is a fundamental data
element, something that does not need to be broken down any further. For example, an item in a
People table contains attributes called PersonID, LastName, FirstName, and so on. For a Department
table, an item might have attributes such as DepartmentID, Name,Manager, and so on. Attributes in
DynamoDB are similar in many ways to ﬁelds or columns in other database systems.
The following diagram shows a table named People with some example items and attributes.
Note the following about the People table:
• Each item in the table has a unique identiﬁer, or primary key, that distinguishes the item from all of
the others in the table. In the People table, the primary key consists of one attribute (PersonID).
• Other than the primary key, the People table is schemaless, which means that neither the attributes
nor their data types need to be deﬁned beforehand. Each item can have its own distinct attributes.
• Most of the attributes are scalar, which means that they can have only one value. Strings and numbers
are common examples of scalars.
• Some of the items have a nested attribute (Address). DynamoDB supports nested attributes up to 32
levels deep.
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The following is another example table named Music that you could use to keep track of your music
collection.
Note the following about the Music table:
• The primary key for Music consists of two attributes (Artist and SongTitle). Each item in the table must
have these two attributes. The combination of Artist and SongTitle distinguishes each item in the table
from all of the others.
• Other than the primary key, the Music table is schemaless, which means that neither the attributes nor
their data types need to be deﬁned beforehand. Each item can have its own distinct attributes.
• One of the items has a nested attribute (PromotionInfo), which contains other nested attributes.
DynamoDB supports nested attributes up to 32 levels deep.
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For more information, see Working with Tables in DynamoDB (p. 290).
Primary Key
When you create a table, in addition to the table name, you must specify the primary key of the table.
The primary key uniquely identiﬁes each item in the table, so that no two items can have the same key.
DynamoDB supports two diﬀerent kinds of primary keys:
• Partition key – A simple primary key, composed of one attribute known as the partition key.
DynamoDB uses the partition key's value as input to an internal hash function. The output from the
hash function determines the partition (physical storage internal to DynamoDB) in which the item will
be stored.
In a table that has only a partition key, no two items can have the same partition key value.
The People table described in Tables, Items, and Attributes (p. 2) is an example of a table with a
simple primary key (PersonID). You can access any item in the People table immediately by providing
the PersonId value for that item.
• Partition key and sort key – Referred to as a composite primary key, this type of key is composed of
two attributes. The ﬁrst attribute is the partition key, and the second attribute is the sort key.
DynamoDB uses the partition key value as input to an internal hash function. The output from the
hash function determines the partition (physical storage internal to DynamoDB) in which the item will
be stored. All items with the same partition key are stored together, in sorted order by sort key value.
In a table that has a partition key and a sort key, it's possible for two items to have the same partition
key value. However, those two items must have diﬀerent sort key values.
The Music table described in Tables, Items, and Attributes (p. 2) is an example of a table with a
composite primary key (Artist and SongTitle). You can access any item in the Music table immediately, if
you provide the Artist and SongTitle values for that item.
A composite primary key gives you additional ﬂexibility when querying data. For example, if you
provide only the value for Artist, DynamoDB retrieves all of the songs by that artist. You could even
provide a value for Artist and a range of SongTitle values, to retrieve only a subset of songs by a
particular artist.
Note
The partition key of an item is also known as its hash attribute. The term hash attribute derives
from the use of an internal hash function in DynamoDB that evenly distributes data items across
partitions, based on their partition key values.
The sort key of an item is also known as its range attribute. The term range attribute derives
from the way DynamoDB stores items with the same partition key physically close together, in
sorted order by the sort key value.
Each primary key attribute must be a scalar (meaning that it can hold only a single value). The only data
types allowed for primary key attributes are string, number, or binary. There are no such restrictions for
other, non-key attributes.
Secondary Indexes
You can create one or more secondary indexes on a table. A secondary index lets you query the data
in the table using an alternate key, in addition to queries against the primary key. DynamoDB doesn't
require that you use indexes, but they give your applications more ﬂexibility when querying your data.
After you create a secondary index on a table, you can read data from the index in much the same way as
you do from the table.
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DynamoDB supports two kinds of indexes:
• Global secondary index – An index with a partition key and sort key that can be diﬀerent from those
on the table.
• Local secondary index – An index that has the same partition key as the table, but a diﬀerent sort key.
You can deﬁne up to 5 global secondary indexes and 5 local secondary indexes per table.
In the example Music table shown previously, you can query data items by Artist (partition key) or by
Artist and SongTitle (partition key and sort key). What if you also wanted to query the data by Genre and
AlbumTitle? To do this, you could create an index on Genre and AlbumTitle, and then query the index in
much the same way as you'd query the Music table.
The following diagram shows the example Music table, with a new index called GenreAlbumTitle. In the
index, Genre is the partition key and AlbumTitle is the sort key.
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Note the following about the GenreAlbumTitle index:
• Every index belongs to a table, which is called the base table for the index. In the preceding example,
Music is the base table for the GenreAlbumTitle index.
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• DynamoDB maintains indexes automatically. When you add, update, or delete an item in the base
table, DynamoDB adds, updates, or deletes the corresponding item in any indexes that belong to that
table.
• When you create an index, you specify which attributes will be copied, or projected, from the base
table to the index. At a minimum, DynamoDB projects the key attributes from the base table into the
index. This is the case with GenreAlbumTitle, where only the key attributes from the Music table are
projected into the index.
You can query the GenreAlbumTitle index to ﬁnd all albums of a particular genre (for example, all Rock
albums). You can also query the index to ﬁnd all albums within a particular genre that have certain
album titles (for example, all Country albums with titles that start with the letter H).
For more information, see Improving Data Access with Secondary Indexes (p. 446).
DynamoDB Streams
DynamoDB Streams is an optional feature that captures data modiﬁcation events in DynamoDB tables.
The data about these events appear in the stream in near real time, and in the order that the events
occurred.
Each event is represented by a stream record. If you enable a stream on a table, DynamoDB Streams
writes a stream record whenever one of the following events occurs:
• If a new item is added to the table, the stream captures an image of the entire item, including all of its
attributes.
• If an item is updated, the stream captures the &quot;before&quot; and &quot;after&quot; image of any attributes that were
modiﬁed in the item.
• If an item is deleted from the table, the stream captures an image of the entire item before it was
deleted.
Each stream record also contains the name of the table, the event timestamp, and other metadata.
Stream records have a lifetime of 24 hours; after that, they are automatically removed from the stream.
You can use DynamoDB Streams together with AWS Lambda to create a trigger—code that executes
automatically whenever an event of interest appears in a stream. For example, consider a Customers
table that contains customer information for a company. Suppose that you want to send a &quot;welcome&quot;
email to each new customer. You could enable a stream on that table, and then associate the stream
with a Lambda function. The Lambda function would execute whenever a new stream record appears,
but only process new items added to the Customers table. For any item that has an EmailAddress
attribute, the Lambda function would invoke Amazon Simple Email Service (Amazon SES) to send an
email to that address.
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Note
In this example, the last customer, Craig Roe, will not receive an email because he doesn't have
an EmailAddress.
In addition to triggers, DynamoDB Streams enables powerful solutions such as data replication within
and across AWS regions, materialized views of data in DynamoDB tables, data analysis using Kinesis
materialized views, and much more.
For more information, see Capturing Table Activity with DynamoDB Streams (p. 518).
The DynamoDB API
To work with Amazon DynamoDB, your application must use a few simple API operations. The following
is a summary of these operations, organized by category.
Topics
• Control Plane (p. 9)
• Data Plane (p. 10)
• DynamoDB Streams (p. 11)
Control Plane
Control plane operations let you create and manage DynamoDB tables. They also let you work with
indexes, streams, and other objects that are dependent on tables.
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• CreateTable – Creates a new table. Optionally, you can create one or more secondary indexes, and
enable DynamoDB Streams for the table.
• DescribeTable– Returns information about a table, such as its primary key schema, throughput
settings, index information, and so on.
• ListTables – Returns the names of all of your tables in a list.
• UpdateTable – Modiﬁes the settings of a table or its indexes, creates or remove new indexes on a table,
or modiﬁes DynamoDB Streams settings for a table.
• DeleteTable – Removes a table and all of its dependent objects from DynamoDB.
Data Plane
Data plane operations let you perform create, read, update, and delete (also called CRUD) actions on
data in a table. Some of the data plane operations also let you read data from a secondary index.
Creating Data
• PutItem – Writes a single item to a table. You must specify the primary key attributes, but you don't
have to specify other attributes.
• BatchWriteItem – Writes up to 25 items to a table. This is more eﬃcient than calling PutItem multiple
times because your application only needs a single network round trip to write the items. You can also
use BatchWriteItem for deleting multiple items from one or more tables.
Reading Data
• GetItem – Retrieves a single item from a table. You must specify the primary key for the item that you
want. You can retrieve the entire item, or just a subset of its attributes.
• BatchGetItem – Retrieves up to 100 items from one or more tables. This is more eﬃcient than calling
GetItem multiple times because your application only needs a single network round trip to read the
items.
• Query – Retrieves all items that have a speciﬁc partition key. You must specify the partition key value.
You can retrieve entire items, or just a subset of their attributes. Optionally, you can apply a condition
to the sort key values, so that you only retrieve a subset of the data that has the same partition key.
You can use this operation on a table, provided that the table has both a partition key and a sort key.
You can also use this operation on an index, provided that the index has both a partition key and a sort
key.
• Scan – Retrieves all items in the speciﬁed table or index. You can retrieve entire items, or just a subset
of their attributes. Optionally, you can apply a ﬁltering condition to return only the values that you are
interested in and discard the rest.
Updating Data
• UpdateItem – Modiﬁes one or more attributes in an item. You must specify the primary key for the
item that you want to modify. You can add new attributes and modify or remove existing attributes.
You can also perform conditional updates, so that the update is only successful when a user-deﬁned
condition is met. Optionally, you can implement an atomic counter, which increments or decrements a
numeric attribute without interfering with other write requests.
Deleting Data
• DeleteItem – Deletes a single item from a table. You must specify the primary key for the item that
you want to delete.
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• BatchWriteItem – Deletes up to 25 items from one or more tables. This is more eﬃcient than calling
DeleteItem multiple times because your application only needs a single network round trip to delete
the items. You can also use BatchWriteItem for adding multiple items to one or more tables.
DynamoDB Streams
DynamoDB Streams operations let you enable or disable a stream on a table, and allow access to the
data modiﬁcation records contained in a stream.
• ListStreams – Returns a list of all your streams, or just the stream for a speciﬁc table.
• DescribeStream – Returns information about a stream, such as its Amazon Resource Name (ARN) and
where your application can begin reading the ﬁrst few stream records.
• GetShardIterator – Returns a shard iterator, which is a data structure that your application uses to
retrieve the records from the stream.
• GetRecords – Retrieves one or more stream records, using a given shard iterator.
Naming Rules and Data Types
This section describes the DynamoDB naming rules and the various data types that DynamoDB supports.
There are limits that apply to datatypes. For more information, see Data Types (p. 727).
Topics
• Naming Rules (p. 11)
• Data Types (p. 12)
Naming Rules
Tables, attributes, and other objects in DynamoDB must have names. Names should be meaningful and
concise—for example, names such as Products, Books, and Authors are self-explanatory.
The following are the naming rules for DynamoDB:
• All names must be encoded using UTF-8, and are case-sensitive.
• Table names and index names must be between 3 and 255 characters long, and can contain only the
following characters:
• a-z
• A-Z
• 0-9
• _ (underscore)
• - (dash)
• . (dot)
• Attribute names must be between 1 and 255 characters long.
Reserved Words and Special Characters
DynamoDB has a list of reserved words and special characters. For a complete list of reserved words in
DynamoDB, see Reserved Words in DynamoDB (p. 773). Also, the following characters have special
meaning in DynamoDB: # (hash) and : (colon).
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Although DynamoDB allows you to use these reserved words and special characters for names, we
recommend that you avoid it because you have to deﬁne placeholder variables whenever you use these
names in an expression. For more information, see Expression Attribute Names (p. 342).
Data Types
DynamoDB supports many diﬀerent data types for attributes within a table. They can be categorized as
follows:
• Scalar Types – A scalar type can represent exactly one value. The scalar types are number, string,
binary, Boolean, and null.
• Document Types – A document type can represent a complex structure with nested attributes—such
as you would ﬁnd in a JSON document. The document types are list and map.
• Set Types – A set type can represent multiple scalar values. The set types are string set, number set,
and binary set.
When you create a table or a secondary index, you must specify the names and data types of each
primary key attribute (partition key and sort key). Furthermore, each primary key attribute must be
deﬁned as type string, number, or binary.
DynamoDB is a NoSQL database and is schemaless. This means that, other than the primary key
attributes, you don't have to deﬁne any attributes or data types when you create tables. By comparison,
relational databases require you to deﬁne the names and data types of each column when you create a
table.
The following are descriptions of each data type, along with examples in JSON format.
Scalar Types
The scalar types are number, string, binary, Boolean, and null.
String
Strings are Unicode with UTF-8 binary encoding. The length of a string must be greater than zero and is
constrained by the maximum DynamoDB item size limit of 400 KB.
If you deﬁne a primary key attribute as a string type attribute, the following additional constraints apply:
• For a simple primary key, the maximum length of the ﬁrst attribute value (the partition key) is 2048
bytes.
• For a composite primary key, the maximum length of the second attribute value (the sort key) is 1024
bytes.
DynamoDB collates and compares strings using the bytes of the underlying UTF-8 string encoding. For
example, &quot;a&quot; (0x61) is greater than &quot;A&quot; (0x41), and &quot;&iquest;&quot; (0xC2BF) is greater than &quot;z&quot; (0x7A).
You can use the string data type to represent a date or a time stamp. One way to do this is by using ISO
8601 strings, as shown in these examples:
• 2016-02-15
• 2015-12-21T17:42:34Z
• 20150311T122706Z
For more information, see http://en.wikipedia.org/wiki/ISO_8601.
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Number
Numbers can be positive, negative, or zero. Numbers can have up to 38 digits precision. Exceeding this
results in an exception.
• Positive range: 1E-130 to 9.9999999999999999999999999999999999999E+125
• Negative range: -9.9999999999999999999999999999999999999E+125 to -1E-130
In DynamoDB, numbers are represented as variable length. Leading and trailing zeroes are trimmed.
All numbers are sent across the network to DynamoDB as strings, to maximize compatibility across
languages and libraries. However, DynamoDB treats them as number type attributes for mathematical
operations.
Note
If number precision is important, you should pass numbers to DynamoDB using strings that you
convert from number type.
You can use the number data type to represent a date or a time stamp. One way to do this is by using
epoch time—the number of seconds since 00:00:00 UTC on 1 January 1970. For example, the epoch time
1437136300 represents 12:31:40 UTC on 17 July 2015.
For more information, see http://en.wikipedia.org/wiki/Unix_time.
Binary
Binary type attributes can store any binary data, such as compressed text, encrypted data, or images.
Whenever DynamoDB compares binary values, it treats each byte of the binary data as unsigned.
The length of a binary attribute must be greater than zero, and is constrained by the maximum
DynamoDB item size limit of 400 KB.
If you deﬁne a primary key attribute as a binary type attribute, the following additional constraints
apply:
• For a simple primary key, the maximum length of the ﬁrst attribute value (the partition key) is 2048
bytes.
• For a composite primary key, the maximum length of the second attribute value (the sort key) is 1024
bytes.
Your applications must encode binary values in base64-encoded format before sending them to
DynamoDB. Upon receipt of these values, DynamoDB decodes the data into an unsigned byte array and
uses that as the length of the binary attribute.
The following example is a binary attribute, using base64-encoded text:
dGhpcyB0ZXh0IGlzIGJhc2U2NC1lbmNvZGVk
Boolean
A Boolean type attribute can store either true or false.
Null
Null represents an attribute with an unknown or undeﬁned state.
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Document Types
The document types are list and map. These data types can be nested within each other, to represent
complex data structures up to 32 levels deep.
There is no limit on the number of values in a list or a map, as long as the item containing the values ﬁts
within the DynamoDB item size limit (400 KB).
An attribute value cannot be an empty String or empty Set (String Set, Number Set, or Binary Set).
However, empty Lists and Maps are allowed. For more information, see Attributes (p. 728).
List
A list type attribute can store an ordered collection of values. Lists are enclosed in square brackets:
[ ... ]
A list is similar to a JSON array. There are no restrictions on the data types that can be stored in a list
element, and the elements in a list element do not have to be of the same type.
The following example shows a list that contains two strings and a number:
FavoriteThings: [&quot;Cookies&quot;, &quot;Coffee&quot;, 3.14159]
Note
DynamoDB lets you work with individual elements within lists, even if those elements are deeply
nested. For more information, see Using Expressions in DynamoDB (p. 338).
Map
A map type attribute can store an unordered collection of name-value pairs. Maps are enclosed in curly
braces: { ... }
A map is similar to a JSON object. There are no restrictions on the data types that can be stored in a map
element, and the elements in a map do not have to be of the same type.
Maps are ideal for storing JSON documents in DynamoDB. The following example shows a map that
contains a string, a number, and a nested list that contains another map.
{
}
Day: &quot;Monday&quot;,
UnreadEmails: 42,
ItemsOnMyDesk: [
&quot;Coffee Cup&quot;,
&quot;Telephone&quot;,
{
Pens: { Quantity : 3},
Pencils: { Quantity : 2},
Erasers: { Quantity : 1}
}
]
Note
DynamoDB lets you work with individual elements within maps, even if those elements are
deeply nested. For more information, see Using Expressions in DynamoDB (p. 338).
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Sets
DynamoDB supports types that represent sets of Number, String, or Binary values. All of the elements
within a set must be of the same type. For example, an attribute of type Number Set can only contain
numbers; String Set can only contain strings; and so on.
There is no limit on the number of values in a set, as long as the item containing the values ﬁts within
the DynamoDB item size limit (400 KB).
Each value within a set must be unique. The order of the values within a set is not preserved; therefore,
your applications must not rely on any particular order of elements within the set. Finally, DynamoDB
does not support empty sets.
The following example shows a string set, a number set, and a binary set:
[&quot;Black&quot;, &quot;Green&quot; ,&quot;Red&quot;]
[42.2, -19, 7.5, 3.14]
[&quot;U3Vubnk=&quot;, &quot;UmFpbnk=&quot;, &quot;U25vd3k=&quot;]
Read Consistency
Amazon DynamoDB is available in multiple AWS regions around the world. Each region is independent
and isolated from other AWS regions. For example, if you have a table called People in the us-east-2
region and another table named People in the us-west-2 region, these are considered two entirely
separate tables. For a list of all the AWS regions in which DynamoDB is available, see AWS Regions and
Endpoints in the Amazon Web Services General Reference.
Every AWS region consists of multiple distinct locations called Availability Zones. Each Availability Zone
is isolated from failures in other Availability Zones, and to provide inexpensive, low-latency network
connectivity to other Availability Zones in the same region. This allows rapid replication of your data
among multiple Availability Zones in a region.
When your application writes data to a DynamoDB table and receives an HTTP 200 response (OK), all
copies of the data are updated. The data is eventually consistent across all storage locations, usually
within one second or less.
DynamoDB supports eventually consistent and strongly consistent reads.
Eventually Consistent Reads
When you read data from a DynamoDB table, the response might not reﬂect the results of a recently
completed write operation. The response might include some stale data. If you repeat your read request
after a short time, the response should return the latest data.
Strongly Consistent Reads
When you request a strongly consistent read, DynamoDB returns a response with the most up-to-date
data, reﬂecting the updates from all prior write operations that were successful. A strongly consistent
read might not be available if there is a network delay or outage.
Note
DynamoDB uses eventually consistent reads, unless you specify otherwise. Read operations
(such as GetItem, Query, and Scan) provide a ConsistentRead parameter. If you set this
parameter to true, DynamoDB uses strongly consistent reads during the operation.
Throughput Capacity for Reads and Writes
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Throughput Capacity
• DynamoDB Auto Scaling (p. 16)
• Provisioned Throughput (p. 17)
• Reserved Capacity (p. 17)
When you create a table or index in Amazon DynamoDB, you must specify your capacity requirements
for read and write activity. By deﬁning your throughput capacity in advance, DynamoDB can reserve
the necessary resources to meet the read and write activity your application requires, while ensuring
consistent, low-latency performance.
You specify throughput capacity in terms of read capacity units and write capacity units:
• One read capacity unit represents one strongly consistent read per second, or two eventually
consistent reads per second, for an item up to 4 KB in size. If you need to read an item that is larger
than 4 KB, DynamoDB will need to consume additional read capacity units. The total number of read
capacity units required depends on the item size, and whether you want an eventually consistent or
strongly consistent read.
• One write capacity unit represents one write per second for an item up to 1 KB in size. If you need to
write an item that is larger than 1 KB, DynamoDB will need to consume additional write capacity units.
The total number of write capacity units required depends on the item size.
For example, suppose that you create a table with 5 read capacity units and 5 write capacity units. With
these settings, your application could:
• Perform strongly consistent reads of up to 20 KB per second (4 KB &times; 5 read capacity units).
• Perform eventually consistent reads of up to 40 KB per second (twice as much read throughput).
• Write up to 5 KB per second (1 KB &times; 5 write capacity units).
If your application reads or writes larger items (up to the DynamoDB maximum item size of 400 KB), it
will consume more capacity units.
If your read or write requests exceed the throughput settings for a table, DynamoDB can throttle that
request. DynamoDB can also throttle read requests exceeds for an index. Throttling prevents your
application from consuming too many capacity units. When a request is throttled, it fails with an HTTP
400 code (Bad Request) and a ProvisionedThroughputExceededException. The AWS SDKs have built-in
support for retrying throttled requests (see Error Retries and Exponential Backoﬀ (p. 193)), so you do
not need to write this logic yourself.
You can use the AWS Management Console to monitor your provisioned and actual throughput, and to
modify your throughput settings if necessary.
DynamoDB provides the following mechanisms for managing throughput:
• DynamoDB auto scaling
• Provisioned throughput
• Reserved capacity
DynamoDB Auto Scaling
DynamoDB auto scaling actively manages throughput capacity for tables and global secondary indexes.
With auto scaling, you deﬁne a range (upper and lower limits) for read and write capacity units. You also
deﬁne a target utilization percentage within that range. DynamoDB auto scaling seeks to maintain your
target utilization, even as your application workload increases or decreases.
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With DynamoDB auto scaling, a table or a global secondary index can increase its provisioned read and
write capacity to handle sudden increases in traﬃc, without request throttling. When the workload
decreases, DynamoDB auto scaling can decrease the throughput so that you don't pay for unused
provisioned capacity.
Note
If you use the AWS Management Console to create a table or a global secondary index,
DynamoDB auto scaling is enabled by default.
You can manage auto scaling settings at any time by using the console, the AWS CLI, or one of
the AWS SDKs.
For more information, see Managing Throughput Capacity Automatically with DynamoDB Auto
Scaling (p. 298).
Provisioned Throughput
If you aren't using DynamoDB auto scaling, you have to manually deﬁne your throughput requirements.
Provisioned throughput is the maximum amount of capacity that an application can consume from a
table or index. If your application exceeds your provisioned throughput settings, it is subject to request
throttling.
For example, suppose that you want to read 80 items per second from a table. The items are 3 KB in
size, and you want strongly consistent reads. For this scenario, each read requires one provisioned read
capacity unit. To determine this, you divide the item size of the operation by 4 KB, and then round up to
the nearest whole number, as in this example:
• 3 KB / 4 KB = 0.75, or 1 read capacity unit
For this scenario, you have to set the table's provisioned read throughput to 80 read capacity units:
• 1 read capacity unit per item &times; 80 reads per second = 80 read capacity units
Now suppose that you want to write 100 items per second to your table, and that the items are 512
bytes in size. For this scenario, each write requires one provisioned write capacity unit. To determine this,
you divide the item size of the operation by 1 KB, and then round up to the nearest whole number:
• 512 bytes / 1 KB = 0.5, or 1
For this scenario, you would want to set the table's provisioned write throughput to 100 write capacity
units:
• 1 write capacity unit per item &times; 100 writes per second = 100 write capacity units
For more information see Item Sizes and Capacity Unit Consumption (p. 296).
Reserved Capacity
As a DynamoDB customer, you can purchase reserved capacity in advance, as described at Amazon
DynamoDB Pricing. With reserved capacity, you pay a one-time upfront fee and commit to a minimum
usage level over a period of time. By reserving your read and write capacity units ahead of time, you
realize signiﬁcant cost savings compared to on-demand provisioned throughput settings.
To manage reserved capacity, go to the DynamoDB console and choose Reserved Capacity.
Note
You can prevent users from viewing or purchasing reserved capacity, while still allowing them
to access the rest of the console. For more information, see &quot;Grant Permissions to Prevent
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Purchasing of Reserved Capacity Oﬀerings&quot; in Authentication and Access Control for Amazon
DynamoDB (p. 602).
Partitions and Data Distribution
DynamoDB stores data in partitions. A partition is an allocation of storage for a table, backed by solidstate drives (SSDs) and automatically replicated across multiple Availability Zones within an AWS Region.
Partition management is handled entirely by DynamoDB—you never have to manage partitions yourself.
When you create a table, the initial status of the table is CREATING. During this phase, DynamoDB
allocates suﬃcient partitions to the table so that it can handle your provisioned throughput
requirements. You can begin writing and reading table data after the table status changes to ACTIVE.
DynamoDB allocates additional partitions to a table in the following situations:
• If you increase the table's provisioned throughput settings beyond what the existing partitions can
support.
• If an existing partition ﬁlls to capacity and more storage space is required.
For more details, see Understand Partition Behavior (p. 662).
Partition management occurs automatically in the background and is transparent to your applications.
Your table remains available throughout and fully supports your provisioned throughput requirements.
Global secondary indexes in DynamoDB are also composed of partitions. The data in a GSI is stored
separately from the data in its base table, but index partitions behave in much the same way as table
partitions.
Data Distribution: Partition Key
If your table has a simple primary key (partition key only), DynamoDB stores and retrieves each item
based on its partition key value.
To write an item to the table, DynamoDB uses the value of the partition key as input to an internal hash
function. The output value from the hash function determines the partition in which the item will be
stored.
To read an item from the table, you must specify the partition key value for the item. DynamoDB uses
this value as input to its hash function, yielding the partition in which the item can be found.
The following diagram shows a table named Pets, which spans multiple partitions. The table's primary
key is AnimalType (only this key attribute is shown). DynamoDB uses its hash function to determine
where to store a new item, in this case based on the hash value of the string Dog. Note that the items are
not stored in sorted order. Each item's location is determined by the hash value of its partition key.
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Partitions and Data Distribution
Note
DynamoDB is optimized for uniform distribution of items across a table's partitions, no matter
how many partitions there may be. We recommend that you choose a partition key that can
have a large number of distinct values relative to the number of items in the table. For more
information, see Best Practices for Tables (p. 659).
Data Distribution: Partition Key and Sort Key
If the table has a composite primary key (partition key and sort key), DynamoDB calculates the hash
value of the partition key in the same way as described in Data Distribution: Partition Key (p. 18)—but
it stores all of the items with the same partition key value physically close together, ordered by sort key
value.
To write an item to the table, DynamoDB calculates the hash value of the partition key to determine
which partition should contain the item. In that partition, there could be several items with the same
partition key value, so DynamoDB stores the item among the others with the same partition key, in
ascending order by sort key.
To read an item from the table, you must specify its partition key value and sort key value. DynamoDB
calculates the partition key's hash value, yielding the partition in which the item can be found.
You can read multiple items from the table in a single operation (Query), provided that the items you
want have the same partition key value. DynamoDB returns all of the items with that partition key value.
Optionally, you can apply a condition to the sort key so that it returns only the items within a certain
range of values.
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From SQL to NoSQL
Suppose that the Pets table has a composite primary key consisting of AnimalType (partition key) and
Name (sort key). The following diagram shows DynamoDB writing an item with a partition key value of
Dog and a sort key value of Fido.
To read that same item from the Pets table, DynamoDB calculates the hash value of Dog, yielding the
partition in which these items are stored. DynamoDB then scans the sort key attribute values until it
ﬁnds Fido.
To read all of the items with an AnimalType of Dog, you can issue a Query operation without specifying
a sort key condition. By default, the items are be returned in the order that they are stored (that is, in
ascending order by sort key). Optionally, you can request descending order instead.
To query only some of the Dog items, you can apply a condition to the sort key (for example, only the
Dog items where Name is within the range A through K).
Note
In a DynamoDB table, there is no upper limit on the number of distinct sort key values per
partition key value. If you needed to store many billions of Dog items in the Pets table,
DynamoDB automatically allocates enough storage to handle this requirement.
From SQL to NoSQL
If you are an application developer, you might have some experience using relational database
management systems (RDBMS) and Structured Query Language (SQL). As you begin working with
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SQL or NoSQL?
Amazon DynamoDB, you will encounter many similarities, but also many things that are diﬀerent.
This section describes common database tasks, comparing and contrasting SQL statements with their
equivalent DynamoDB operations.
NoSQL is a term used to describe non-relational database systems that are highly available, scalable,
and optimized for high performance. Instead of the relational model, NoSQL databases (like DynamoDB)
use alternate models for data management, such as key-value pairs or document storage. For more
information, see http://aws.amazon.com/nosql.
Note
The SQL examples in this section are compatible with the MySQL relational database
management system.
The DynamoDB examples in this section show the name of the DynamoDB operation, along with
the parameters for that operation in JSON format. For code samples that use these operations,
see Getting Started with DynamoDB (p. 52).
Topics
• SQL or NoSQL? (p. 21)
• Accessing the Database (p. 22)
• Creating a Table (p. 24)
• Getting Information About a Table (p. 26)
• Writing Data To a Table (p. 27)
• Reading Data From a Table (p. 29)
• Managing Indexes (p. 34)
• Modifying Data in a Table (p. 37)
• Deleting Data from a Table (p. 38)
• Removing a Table (p. 39)
SQL or NoSQL?
Today's applications have more demanding requirements than ever before. For example, an online game
might start out with just a few users and a very small amount of data. However, if the game becomes
successful, it can easily outstrip the resources of the underlying database management system. It is not
uncommon for web-based applications to have hundreds, thousands, or millions of concurrent users,
with terabytes or more of new data generated per day. Databases for such applications must handle tens
(or hundreds) of thousands of reads and writes per second.
Amazon DynamoDB is well-suited for these kinds of workloads. As a developer, you can start with a small
amount of provisioned throughput and gradually increase it as your application becomes more popular.
DynamoDB scales seamlessly to handle very large amounts of data and very large numbers of users.
The following table shows some high-level diﬀerences between a relational database management
system (RDBMS) and DynamoDB:
Characteristic
Relational Database
Management System (RDBMS)
Amazon DynamoDB
Optimal Workloads
Ad hoc queries; data
warehousing; OLAP (online
analytical processing).
Web-scale applications,
including social networks,
gaming, media sharing, and IoT
(Internet of Things).
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Accessing the Database
Characteristic
Relational Database
Management System (RDBMS)
Amazon DynamoDB
Data Model
The relational model requires
a well-deﬁned schema, where
data is normalized into tables,
rows and columns. In addition,
all of the relationships are
deﬁned among tables, columns,
indexes, and other database
elements.
DynamoDB is schemaless. Every
table must have a primary key
to uniquely identify each data
item, but there are no similar
constraints on other non-key
attributes. DynamoDB can
manage structured or semistructured data, including JSON
documents.
Data Access
SQL (Structured Query
Language) is the standard for
storing and retrieving data.
Relational databases oﬀer a rich
set of tools for simplifying the
development of database-driven
applications, but all of these
tools use SQL.
You can use the AWS
Management Console or
the AWS CLI to work with
DynamoDB and perform ad
hoc tasks. Applications can
leverage the AWS software
development kits (SDKs) to work
with DynamoDB using objectbased, document-centric, or lowlevel interfaces.
Performance
Relational databases are
optimized for storage, so
performance generally
depends on the disk subsystem.
Developers and database
administrators must optimize
queries, indexes, and table
structures in order to achieve
peak performance.
DynamoDB is optimized for
compute, so performance
is mainly a function of the
underlying hardware and
network latency. As a managed
service, DynamoDB insulates
you and your applications from
these implementation details, so
that you can focus on designing
and building robust, highperformance applications.
Scaling
It is easiest to scale up with
faster hardware. It is also
possible for database tables to
span across multiple hosts in
a distributed system, but this
requires additional investment.
Relational databases have
maximum sizes for the number
and size of ﬁles, which imposes
upper limits on scalability.
DynamoDB is designed to scale
out using distributed clusters
of hardware. This design allows
increased throughput without
increased latency. Customers
specify their throughput
requirements, and DynamoDB
allocates suﬃcient resources
to meet those requirements.
There are no upper limits on the
number of items per table, nor
the total size of that table.
Accessing the Database
Before your application can access a database, it must be authenticated to ensure that the application is
allowed to use the database, and authorized so that the application can only perform actions for which it
has permissions.
The following diagram shows client interaction with a relational database, and with DynamoDB.
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Accessing the Database
The following table has more details about client interaction tasks:
Characteristic
Relational Database
Management System (RDBMS)
Amazon DynamoDB
Tools for Accessing the
Database
Most relational databases
provide a command line
interface (CLI), so that you can
enter ad hoc SQL statements
and see the results immediately.
In most cases, you write
application code. You can also
use the AWS Management
Console or the AWS Command
Line Interface (AWS CLI) to send
ad hoc requests to DynamoDB
and view the results.
Connecting to the Database
An application program
establishes and maintains a
network connection with the
database. When the application
is ﬁnished, it terminates the
connection.
DynamoDB is a web service, and
interactions with it are stateless.
Applications do not need to
maintain persistent network
connections. Instead, interaction
with DynamoDB occurs using
HTTP(S) requests and responses.
Authentication
An application cannot connect
to the database until it is
authenticated. The RDBMS can
perform the authentication
itself, or it can oﬄoad this task
to the host operating system or
a directory service.
Every request to DynamoDB
must be accompanied by a
cryptographic signature, which
authenticates that particular
request. The AWS SDKs provide
all of the logic necessary for
creating signatures and signing
requests. For more information,
see Signing AWS API Requests in
the AWS General Reference.
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Creating a Table
Characteristic
Relational Database
Management System (RDBMS)
Amazon DynamoDB
Authorization
Applications can only perform
actions for which they have
been authorized. Database
administrators or application
owners can use the SQL GRANT
and REVOKE statements to
control access to database
objects (such as tables), data
(such as rows within a table), or
the ability to issue certain SQL
statements.
In DynamoDB, authorization is
handled by AWS Identity and
Access Management (IAM). You
can write an IAM policy to grant
permissions on a DynamoDB
resource (such as a table), and
then allow IAM users and roles
to use that policy. IAM also
features ﬁne-grained access
control for individual data items
in DynamoDB tables. For more
information, see Authentication
and Access Control for Amazon
DynamoDB (p. 602).
Sending a Request
The application issues a SQL
statement for every database
operation that it wants to
perform. Upon receipt of the
SQL statement, the RDBMS
checks its syntax, creates a plan
for performing the operation,
and then executes the plan.
The application sends HTTP(S)
requests to DynamoDB. The
requests contain the name of
the DynamoDB operation to
perform, along with parameters.
DynamoDB executes the request
immediately.
Receiving a Response
The RDBMS returns the results
from the SQL statement. If there
is an error, the RDBMS returns
an error status and message.
DynamoDB returns an HTTP(S)
response containing the results
of the operation. If there is
an error, DynamoDB returns
an HTTP error status and
message(s).
Creating a Table
Tables are the fundamental data structures in relational databases and in DynamoDB. A relational
database management systems (RDBMS) requires you to deﬁne the table's schema when you create it. In
contrast, DynamoDB tables are schemaless—other than the primary key, you do not need to deﬁne any
attributes or data types at table creation time.
SQL
Use the CREATE TABLE statement to create a table, as shown in the following example.
CREATE TABLE Music (
Artist VARCHAR(20) NOT NULL,
SongTitle VARCHAR(30) NOT NULL,
AlbumTitle VARCHAR(25),
Year INT,
Price FLOAT,
Genre VARCHAR(10),
Tags TEXT,
PRIMARY KEY(Artist, SongTitle)
);
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The primary key for this table consists of Artist and SongTitle.
You must deﬁne all of the table's columns and data types, and the table's primary key. (You can use the
ALTER TABLE statement to change these deﬁnitions later, if necessary.)
Many SQL implementations let you deﬁne storage speciﬁcations for your table, as part of the CREATE
TABLE statement. Unless you indicate otherwise, the table is created with default storage settings. In a
production environment, a database administrator can help determine the optimal storage parameters.
DynamoDB
Use the CreateTable action to create a table, specifying parameters as shown following:
{
}
TableName : &quot;Music&quot;,
KeySchema: [
{
AttributeName: &quot;Artist&quot;,
KeyType: &quot;HASH&quot;, //Partition key
},
{
AttributeName: &quot;SongTitle&quot;,
KeyType: &quot;RANGE&quot; //Sort key
}
],
AttributeDefinitions: [
{
AttributeName: &quot;Artist&quot;,
AttributeType: &quot;S&quot;
},
{
AttributeName: &quot;SongTitle&quot;,
AttributeType: &quot;S&quot;
}
],
ProvisionedThroughput: {
ReadCapacityUnits: 1,
WriteCapacityUnits: 1
}
The primary key for this table consists of Artist (partition key) and SongTitle (sort key).
You must provide the following parameters to CreateTable:
• TableName – Name of the table.
• KeySchema – Attributes that are used for the primary key. For more information, see Tables, Items, and
Attributes (p. 2) and Primary Key (p. 5).
• AttributeDefinitions – Data types for the key schema attributes.
• ProvisionedThroughput – Number of reads and writes per second that you need for this table.
DynamoDB reserves suﬃcient storage and system resources so that your throughput requirements are
always met. You can use the UpdateTable action to change these later, if necessary. You do not need to
specify a table's storage requirements because storage allocation is managed entirely by DynamoDB.
Note
For code samples using CreateTable, see Getting Started with DynamoDB (p. 52).
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Getting Information About a Table
Getting Information About a Table
You can verify that a table has been created according to your speciﬁcations. In a relational database, all
of the table's schema is shown. DynamoDB tables are schemaless, so only the primary key attributes are
shown.
SQL
Most relational database management systems (RDBMS) allow you to describe a table's structure—
columns, data types, primary key deﬁnition, and so on. There is no standard way to do this in SQL.
However, many database systems provide a DESCRIBE command. Here is an example from MySQL:
DESCRIBE Music;
This returns the structure of your table, with all of the column names, data types, and sizes:
+------------+-------------+------+-----+---------+-------+
| Field
| Type
| Null | Key | Default | Extra |
+------------+-------------+------+-----+---------+-------+
| Artist
| varchar(20) | NO
| PRI | NULL
|
|
| SongTitle | varchar(30) | NO
| PRI | NULL
|
|
| AlbumTitle | varchar(25) | YES |
| NULL
|
|
| Year
| int(11)
| YES |
| NULL
|
|
| Price
| float
| YES |
| NULL
|
|
| Genre
| varchar(10) | YES |
| NULL
|
|
| Tags
| text
| YES |
| NULL
|
|
+------------+-------------+------+-----+---------+-------+
The primary key for this table consists of Artist and SongTitle.
DynamoDB
DynamoDB has a DescribeTable action, which is similar. The only parameter is the table name, as shown
following:
{
}
TableName : &quot;Music&quot;
The reply from DescribeTable looks like this:
{
&quot;Table&quot;: {
&quot;AttributeDefinitions&quot;: [
{
&quot;AttributeName&quot;: &quot;Artist&quot;,
&quot;AttributeType&quot;: &quot;S&quot;
},
{
&quot;AttributeName&quot;: &quot;SongTitle&quot;,
&quot;AttributeType&quot;: &quot;S&quot;
}
],
&quot;TableName&quot;: &quot;Music&quot;,
&quot;KeySchema&quot;: [
{
&quot;AttributeName&quot;: &quot;Artist&quot;,
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&quot;KeyType&quot;: &quot;HASH&quot;
},
{
}
//Partition key
&quot;AttributeName&quot;: &quot;SongTitle&quot;,
&quot;KeyType&quot;: &quot;RANGE&quot; //Sort key
],
...
DescribeTable also returns information. about indexes on the table, provisioned throughput settings, an
approximate item count, and other metadata.
Writing Data To a Table
Relational database tables contain rows of data. Rows are composed of columns.
DynamoDB tables contain items. Items are composed of attributes.
This section describes how to write one row (or item) to a table.
SQL
A table in a relational database is a two-dimensional data structure composed of rows and columns.
Some database management systems also provide support for semi-structured data, usually with native
JSON or XML data types. However, the implementation details vary among vendors.
In SQL, you use the INSERT statement to add a row to a table:
INSERT INTO Music
(Artist, SongTitle, AlbumTitle,
Year, Price, Genre,
Tags)
VALUES(
'No One You Know', 'Call Me Today', 'Somewhat Famous',
2015, 2.14, 'Country',
'{&quot;Composers&quot;: [&quot;Smith&quot;, &quot;Jones&quot;,&quot;Davis&quot;],&quot;LengthInSeconds&quot;: 214}'
);
The primary key for this table consists of Artist and SongTitle. You must specify values for these columns.
Note
In this example, we are using the Tags column to store semi-structured data about the songs in
the Music table. We have deﬁned the Tags column as type TEXT, which can store up to 65535
characters in MySQL.
DynamoDB
In Amazon DynamoDB, you use the PutItem action to add an item to a table:
{
TableName: &quot;Music&quot;,
Item: {
&quot;Artist&quot;:&quot;No One You Know&quot;,
&quot;SongTitle&quot;:&quot;Call Me Today&quot;,
&quot;AlbumTitle&quot;:&quot;Somewhat Famous&quot;,
&quot;Year&quot;: 2015,
&quot;Price&quot;: 2.14,
&quot;Genre&quot;: &quot;Country&quot;,
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}
}
&quot;Tags&quot;: {
&quot;Composers&quot;: [
&quot;Smith&quot;,
&quot;Jones&quot;,
&quot;Davis&quot;
],
&quot;LengthInSeconds&quot;: 214
}
The primary key for this table consists of Artist and SongTitle. You must specify values for these
attributes.
Here are some key things to know about this PutItem example:
• DynamoDB provide native support for documents, using JSON. This makes DynamoDB ideal for storing
semi-structured data, such as Tags. You can also retrieve and manipulate data from within JSON
documents.
• The Music table does not have any predeﬁned attributes, other than the primary key (Artist and
SongTitle).
• Most SQL databases are transaction-oriented. When you issue an INSERT statement, the data
modiﬁcations are not permanent until you issue a COMMIT statement. With Amazon DynamoDB, the
eﬀects of a PutItem action are permanent when DynamoDB replies with an HTTP 200 status code (OK).
Note
For code samples using PutItem, see Getting Started with DynamoDB (p. 52).
The following are some other PutItem examples.
{
}
{
}
{
TableName: &quot;Music&quot;,
Item: {
&quot;Artist&quot;: &quot;No One You Know&quot;,
&quot;SongTitle&quot;: &quot;My Dog Spot&quot;,
&quot;AlbumTitle&quot;:&quot;Hey Now&quot;,
&quot;Price&quot;: 1.98,
&quot;Genre&quot;: &quot;Country&quot;,
&quot;CriticRating&quot;: 8.4
}
TableName: &quot;Music&quot;,
Item: {
&quot;Artist&quot;: &quot;No One You Know&quot;,
&quot;SongTitle&quot;: &quot;Somewhere Down The Road&quot;,
&quot;AlbumTitle&quot;:&quot;Somewhat Famous&quot;,
&quot;Genre&quot;: &quot;Country&quot;,
&quot;CriticRating&quot;: 8.4,
&quot;Year&quot;: 1984
}
TableName: &quot;Music&quot;,
Item: {
&quot;Artist&quot;: &quot;The Acme Band&quot;,
&quot;SongTitle&quot;: &quot;Still In Love&quot;,
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}
{
}
}
&quot;AlbumTitle&quot;:&quot;The Buck Starts Here&quot;,
&quot;Price&quot;: 2.47,
&quot;Genre&quot;: &quot;Rock&quot;,
&quot;PromotionInfo&quot;: {
&quot;RadioStationsPlaying&quot;:[
&quot;KHCR&quot;, &quot;KBQX&quot;, &quot;WTNR&quot;, &quot;WJJH&quot;
],
&quot;TourDates&quot;: {
&quot;Seattle&quot;: &quot;20150625&quot;,
&quot;Cleveland&quot;: &quot;20150630&quot;
},
&quot;Rotation&quot;: &quot;Heavy&quot;
}
TableName: &quot;Music&quot;,
Item: {
&quot;Artist&quot;: &quot;The Acme Band&quot;,
&quot;SongTitle&quot;: &quot;Look Out, World&quot;,
&quot;AlbumTitle&quot;:&quot;The Buck Starts Here&quot;,
&quot;Price&quot;: 0.99,
&quot;Genre&quot;: &quot;Rock&quot;
}
Note
In addition to PutItem, Amazon DynamoDB supports a BatchWriteItem action for writing
multiple items at the same time.
Reading Data From a Table
With SQL, you use the SELECT statement to retrieve one or more rows from a table. You use the WHERE
clause to determine the data that is returned to you.
DynamoDB provides the following operations for reading data:
• GetItem – Retrieves a single item from a table. This is the most eﬃcient way to read a single item,
because it provides direct access to the physical location of the item. (DynamoDB also provides
BatchGetItem operation, allowing you to perform up to 100 GetItem calls in a single operation.)
• Query – Retrieves all of the items that have a speciﬁc partition key. Within those items, you can apply
a condition to the sort key and retrieve only a subset of the data. Query provides quick, eﬃcient
access to the partitions where the data is stored. (For more information, see Partitions and Data
Distribution (p. 18).)
• Scan – Retrieves all of the items in the speciﬁed table. (This operation should not be used with large
tables, because it can consume large amounts of system resources.)
Note
With a relational database, you can use the SELECT statement to join data from multiple tables
and return the results. Joins are fundamental to the relational model. To ensure that joins
execute eﬃciently, the database and its applications should be performance-tuned on an
ongoing basis.
DynamoDB is a non-relational NoSQL database, and does not support table joins. Instead,
applications read data from one table at a time.
The following sections describe diﬀerent use cases for reading data, and how to perform these tasks with
a relational database and with DynamoDB.
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Topics
• Reading an Item Using Its Primary Key (p. 30)
• Querying a Table (p. 31)
• Scanning a Table (p. 33)
Reading an Item Using Its Primary Key
One common access pattern for databases is to read a single item from a table. You have to specify the
primary key of the item you want.
SQL
In SQL, you use the SELECT statement to retrieve data from a table. You can request one or more
columns in the result (or all of them, if you use the * operator). The WHERE clause determines which row(s)
to return.
The following is a SELECT statement to retrieve a single row from the Music table. The WHERE clause
speciﬁes the primary key values.
SELECT *
FROM Music
WHERE Artist='No One You Know' AND SongTitle = 'Call Me Today'
You can modify this query to retrieve only a subset of the columns:
SELECT AlbumTitle, Year, Price
FROM Music
WHERE Artist='No One You Know' AND SongTitle = 'Call Me Today'
Note that the primary key for this table consists of Artist and SongTitle.
DynamoDB
DynamoDB provides the GetItem action for retrieving an item by its primary key. GetItem is highly
eﬃcient because it provides direct access to the physical location of the item. (For more information, see
Partitions and Data Distribution (p. 18).)
By default, GetItem returns the entire item with all of its attributes.
{
}
TableName: &quot;Music&quot;,
Key: {
&quot;Artist&quot;: &quot;No One You Know&quot;,
&quot;SongTitle&quot;: &quot;Call Me Today&quot;
}
You can add a ProjectionExpression parameter to return only some of the attributes:
{
TableName: &quot;Music&quot;,
Key: {
&quot;Artist&quot;: &quot;No One You Know&quot;,
&quot;SongTitle&quot;: &quot;Call Me Today&quot;
},
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}
&quot;ProjectionExpression&quot;: &quot;AlbumTitle, Year, Price&quot;
Note that the primary key for this table consists of Artist and SongTitle.
The DynamoDB GetItem action is very eﬃcient: It uses the primary key value(s) to determine the exact
storage location of the item in question, and retrieves it directly from there. The SQL SELECT statement is
similarly eﬃcient, in the case of retrieving items by primary key values.
The SQL SELECT statement supports many kinds of queries and table scans. DynamoDB provides similar
functionality with its Query and Scan actions, which are described in Querying a Table (p. 31) and
Scanning a Table (p. 33).
The SQL SELECT statement can perform table joins, allowing you to retrieve data from multiple
tables at the same time. Joins are most eﬀective where the database tables are normalized and the
relationships among the tables are clear. However, if you join too many tables in one SELECT statement
application performance can be aﬀected. You can work around such issues by using database replication,
materialized views, or query rewrites.
DynamoDB is a non-relational database. As such, it does not support table joins. If you are migrating an
existing application from a relational database to DynamoDB, you need to denormalize your data model
to eliminate the need for joins.
Note
For code samples using GetItem, see Getting Started with DynamoDB (p. 52).
Querying a Table
Another common access pattern is reading multiple items from a table, based on your query criteria.
SQL
The SQL SELECT statement lets you query on key columns, non-key columns, or any combination. The
WHERE clause determines which rows are returned, as shown in the following examples:
/* Return a single song, by primary key */
SELECT * FROM Music
WHERE Artist='No One You Know' AND SongTitle = 'Call Me Today';
/* Return all of the songs by an artist */
SELECT * FROM Music
WHERE Artist='No One You Know';
/* Return all of the songs by an artist, matching first part of title */
SELECT * FROM Music
WHERE Artist='No One You Know' AND SongTitle LIKE 'Call%';
/* Return all of the songs by an artist, with a particular word in the title...
...but only if the price is less than 1.00 */
SELECT * FROM Music
WHERE Artist='No One You Know' AND SongTitle LIKE '%Today%'
AND Price &lt; 1.00;
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Note that the primary key for this table consists of Artist and SongTitle.
DynamoDB
The DynamoDB Query action lets you retrieve data in a similar fashion. The Query action provides quick,
eﬃcient access to the physical locations where the data is stored. (For more information, see Partitions
and Data Distribution (p. 18).)
You can use Query with any table that has a composite primary key (partition key and sort key). You must
specify an equality condition for the partition key, and you can optionally provide another condition for
the sort key.
The KeyConditionExpression parameter speciﬁes the key values that you want to query. You can use an
optional FilterExpression to remove certain items from the results before they are returned to you.
In DynamoDB, you must use ExpressionAttributeValues as placeholders in expression parameters (such
as KeyConditionExpression and FilterExpression). This is analogous to the use of bind variables in
relational databases, where you substitute the actual values into the SELECT statement at runtime.
Note that the primary key for this table consists of Artist and SongTitle.
Here are some Query examples in DynamoDB:
// Return a single song, by primary key
{
}
TableName: &quot;Music&quot;,
KeyConditionExpression: &quot;Artist = :a and SongTitle = :t&quot;,
ExpressionAttributeValues: {
&quot;:a&quot;: &quot;No One You Know&quot;,
&quot;:t&quot;: &quot;Call Me Today&quot;
}
// Return all of the songs by an artist
{
}
TableName: &quot;Music&quot;,
KeyConditionExpression: &quot;Artist = :a&quot;,
ExpressionAttributeValues: {
&quot;:a&quot;: &quot;No One You Know&quot;
}
// Return all of the songs by an artist, matching first part of title
{
}
TableName: &quot;Music&quot;,
KeyConditionExpression: &quot;Artist = :a and begins_with(SongTitle, :t)&quot;,
ExpressionAttributeValues: {
&quot;:a&quot;: &quot;No One You Know&quot;,
&quot;:t&quot;: &quot;Call&quot;
}
// Return all of the songs by an artist, with a particular word in the title...
// ...but only if the price is less than 1.00
{
TableName: &quot;Music&quot;,
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}
KeyConditionExpression: &quot;Artist = :a and contains(SongTitle, :t)&quot;,
FilterExpression: &quot;price &lt; :p&quot;,
ExpressionAttributeValues: {
&quot;:a&quot;: &quot;No One You Know&quot;,
&quot;:t&quot;: &quot;Today&quot;,
&quot;:p&quot;: 1.00
}
Note
For code samples using Query, see Getting Started with DynamoDB (p. 52).
Scanning a Table
In SQL, a SELECT statement without a WHERE clause will return every row in a table. In DynamoDB, the
Scan operation does the same thing. In both cases, you can retrieve all of the items, or just some of
them.
Whether you are using a SQL or a NoSQL database, scans should be used sparingly because they can
consume large amounts of system resources. Sometimes a scan is appropriate (such as scanning a small
table) or unavoidable (such as performing a bulk export of data). However, as a general rule, you should
design your applications to avoid performing scans.
SQL
In SQL, you can scan a table and retrieve all of its data by using a SELECT statement without specifying
a WHERE clause. You can request one or more columns in the result. Or, you can request all of them if you
use the wildcard character (*).
Here are some examples:
/* Return all of the data in the table */
SELECT * FROM Music;
/* Return all of the values for Artist and Title */
SELECT Artist, Title FROM Music;
DynamoDB
DynamoDB provides a Scan action that works in a similar way. Here are some examples:
// Return all of the data in the table
{
TableName: &quot;Music&quot;
}
// Return all of the values for Artist and Title
{
TableName: &quot;Music&quot;,
ProjectionExpression: &quot;Artist, Title&quot;
}
The Scan action also provides a FilterExpression parameter, to discard items that you do not want to
appear in the results. A FilterExpression is applied after the entire table is scanned, but before the
results are returned to you. (This is not recommended with large tables: You are still charged for the
entire Scan, even if only a few matching items are returned.)
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Managing Indexes
Note
For code samples that use Scan, see Getting Started with DynamoDB (p. 52).
Managing Indexes
Indexes give you access to alternate query patterns, and can speed up queries. This section compares and
contrasts index creation and usage in SQL and DynamoDB.
Whether you are using a relational database or DynamoDB, you should be judicious with index creation.
Whenever a write occurs on a table, all of the table's indexes must be updated. In a write-heavy
environment with large tables, this can consume large amounts of system resources. In a read-only or
read-mostly environment, this is not as much of a concern—however, you should ensure that the indexes
are actually being used by your application, and not simply taking up space.
Topics
• Creating an Index (p. 34)
• Querying and Scanning an Index (p. 35)
Creating an Index
SQL
In a relational database, an index is a data structure that let you perform fast queries on diﬀerent
columns in a table. You can use the CREATE INDEX SQL statement to add an index to an existing table,
specifying the columns to be indexed. After the index has been created, you can query the data in the
table as usual, but now the database can use the index to quickly ﬁnd the speciﬁed rows in the table
instead of scanning the entire table.
After you create an index, the database maintains it for you. Whenever you modify data in the table, the
index is automatically modiﬁed to reﬂect changes in the table.
In MySQL, you can create an index like this:
CREATE INDEX GenreAndPriceIndex
ON Music (genre, price);
DynamoDB
In DynamoDB, you can create and use a secondary index for similar purposes.
Indexes in DynamoDB are diﬀerent from their relational counterparts. When you create a secondary
index, you must specify its key attributes – a partition key and a sort key. After you create the secondary
index, you can Query it or Scan it just as you would with a table. DynamoDB does not have a query
optimizer, so a secondary index is only used when you Query it or Scan it.
DynamoDB supports two diﬀerent kinds of indexes:
• Global secondary indexes – The primary key of the index can be any two attributes from its table.
• Local secondary indexes – The partition key of the index must be the same as the partition key of its
table. However, the sort key can be any other attribute.
DynamoDB ensures that the data in a secondary index is eventually consistent with its table. You can
request strongly consistent Query or Scan actions on a table or a local secondary index. However, global
secondary indexes only support eventual consistency.
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You can add a global secondary index to an existing table, using the UpdateTable action and specifying
GlobalSecondaryIndexUpdates:
{
}
TableName: &quot;Music&quot;,
AttributeDefinitions:[
{AttributeName: &quot;Genre&quot;, AttributeType: &quot;S&quot;},
{AttributeName: &quot;Price&quot;, AttributeType: &quot;N&quot;}
],
GlobalSecondaryIndexUpdates: [
{
Create: {
IndexName: &quot;GenreAndPriceIndex&quot;,
KeySchema: [
{AttributeName: &quot;Genre&quot;, KeyType: &quot;HASH&quot;}, //Partition key
{AttributeName: &quot;Price&quot;, KeyType: &quot;RANGE&quot;}, //Sort key
],
Projection: {
&quot;ProjectionType&quot;: &quot;ALL&quot;
},
ProvisionedThroughput: {
&quot;ReadCapacityUnits&quot;: 1,&quot;WriteCapacityUnits&quot;: 1
}
}
}
]
You must provide the following parameters to UpdateTable:
• TableName – The table that the index will be associated with.
• AttributeDefinitions – The data types for the key schema attributes of the index.
• GlobalSecondaryIndexUpdates – Details about the index you want to create:
• IndexName – A name for the index.
• KeySchema – The attributes that are used for the index primary key.
• Projection – Attributes from the table that are copied to the index. In this case, ALL means that all
of the attributes are copied.
• ProvisionedThroughput – The number of reads and writes per second that you need for this index.
(This is separate from the provisioned throughput settings of the table.)
Part of this operation involves backﬁlling data from the table into the new index. During backﬁlling, the
table remains available. However, the index is not ready until its Backfilling attribute changes from
true to false. You can use the DescribeTable action to view this attribute.
Note
For code samples that use UpdateTable, see Getting Started with DynamoDB (p. 52).
Querying and Scanning an Index
SQL
In a relational database, you do not work directly with indexes. Instead, you query tables by issuing
SELECT statements, and the query optimizer can make use of any indexes.
A query optimizer is a relational database management systems (RDBMS) component that evaluates the
available indexes, and determines whether they can be used to speed up a query. If the indexes can be
used to speed up a query, the RDBMS accesses the index ﬁrst and then uses it to locate the data in the
table.
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Managing Indexes
Here are some SQL statements that can use GenreAndPriceIndex to improve performance. We assume
that the Music table has enough data in it that the query optimizer decides to use this index, rather than
simply scanning the entire table.
/* All of the rock songs */
SELECT * FROM Music
WHERE Genre = 'Rock';
/* All of the cheap country songs */
SELECT Artist, SongTitle, Price FROM Music
WHERE Genre = 'Country' AND Price &lt; 0.50;
DynamoDB
In DynamoDB, you perform Query operations directly on the index, in the same way that you would do so
on a table. You must specify both TableName and IndexName.
The following are some queries on GenreAndPriceIndex in DynamoDB. (The key schema for this index
consists of Genre and Price.)
// All of the rock songs
{
};
TableName: &quot;Music&quot;,
IndexName: &quot;GenreAndPriceIndex&quot;,
KeyConditionExpression: &quot;Genre = :genre&quot;,
ExpressionAttributeValues: {
&quot;:genre&quot;: &quot;Rock&quot;
},
// All of the cheap country songs
{
};
TableName: &quot;Music&quot;,
IndexName: &quot;GenreAndPriceIndex&quot;,
KeyConditionExpression: &quot;Genre = :genre and Price &lt; :price&quot;,
ExpressionAttributeValues: {
&quot;:genre&quot;: &quot;Country&quot;,
&quot;:price&quot;: 0.50
},
ProjectionExpression: &quot;Artist, SongTitle, Price&quot;
This example uses a ProjectionExpression to indicate that we only want some of the attributes, rather
than all of them, to appear in the results.
You can also perform Scan operations on a secondary index, in the same way that you would do so on a
table. The following is a scan on GenreAndPriceIndex:
// Return all of the data in the index
{
}
TableName: &quot;Music&quot;,
IndexName: &quot;GenreAndPriceIndex&quot;
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Modifying Data in a Table
Modifying Data in a Table
The SQL language provides the UPDATE statement for modifying data. DynamoDB uses the UpdateItem
operation to accomplish similar tasks.
SQL
In SQL, you use the UPDATE statement to modify one or more rows. The SET clause speciﬁes new values
for one or more columns, and the WHERE clause determines which rows are modiﬁed. Here is an example:
UPDATE Music
SET RecordLabel = 'Global Records'
WHERE Artist = 'No One You Know' AND SongTitle = 'Call Me Today';
If no rows match the WHERE clause, the UPDATE statement has no eﬀect.
DynamoDB
In DynamoDB, you use the UpdateItem action to modify a single item. (If you want to modify multiple
items, you must use multiple UpdateItem operations.)
Here is an example:
{
}
TableName: &quot;Music&quot;,
Key: {
&quot;Artist&quot;:&quot;No One You Know&quot;,
&quot;SongTitle&quot;:&quot;Call Me Today&quot;
},
UpdateExpression: &quot;SET RecordLabel = :label&quot;,
ExpressionAttributeValues: {
&quot;:label&quot;: &quot;Global Records&quot;
}
You must specify the Key attributes of the item to be modiﬁed, and an UpdateExpression to specify
attribute values.
UpdateItem replaces the entire item, rather than replacing individual attributes.
UpdateItem behaves like an &quot;upsert&quot; operation: The item is updated if it exists in the table, but if not, a
new item is added (inserted).
UpdateItem supports conditional writes, where the operation succeeds only if a speciﬁc
ConditionExpression evaluates to true. For example, the following UpdateItem action does not perform
the update unless the price of the song is greater than or equal to 2.00:
{
TableName: &quot;Music&quot;,
Key: {
&quot;Artist&quot;:&quot;No One You Know&quot;,
&quot;SongTitle&quot;:&quot;Call Me Today&quot;
},
UpdateExpression: &quot;SET RecordLabel = :label&quot;,
ConditionExpression: &quot;Price &gt;= :p&quot;,
ExpressionAttributeValues: {
&quot;:label&quot;: &quot;Global Records&quot;,
&quot;:p&quot;: 2.00
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Deleting Data from a Table
}
}
UpdateItem also supports atomic counters, or attributes of type Number that can be incremented or
decremented. Atomic counters are similar in many ways to sequence generators, identity columns, or
auto-increment ﬁelds in SQL databases.
The following is an example of an UpdateItem action to initialize a new attribute (Plays) to keep track of
the number of times a song has been played:
{
}
TableName: &quot;Music&quot;,
Key: {
&quot;Artist&quot;:&quot;No One You Know&quot;,
&quot;SongTitle&quot;:&quot;Call Me Today&quot;
},
UpdateExpression: &quot;SET Plays = :val&quot;,
ExpressionAttributeValues: {
&quot;:val&quot;: 0
},
ReturnValues: &quot;UPDATED_NEW&quot;
The ReturnValues parameter is set to UPDATED_NEW, which returns the new values of any attributes that
were updated. In this case, it returns 0 (zero).
Whenever someone plays this song, we can use the following UpdateItem action to increment Plays by
one:
{
}
TableName: &quot;Music&quot;,
Key: {
&quot;Artist&quot;:&quot;No One You Know&quot;,
&quot;SongTitle&quot;:&quot;Call Me Today&quot;
},
UpdateExpression: &quot;SET Plays = Plays + :incr&quot;,
ExpressionAttributeValues: {
&quot;:incr&quot;: 1
},
ReturnValues: &quot;UPDATED_NEW&quot;
Note
For code samples using UpdateItem, see Getting Started with DynamoDB (p. 52).
Deleting Data from a Table
In SQL, the DELETE statement removes one or more rows from a table. DynamoDB uses the DeleteItem
operation to delete one item at a time.
SQL
In SQL, you use the DELETE statement to delete one or more rows. The WHERE clause determines the rows
that you want to modify. Here is an example:
DELETE FROM Music
WHERE Artist = 'The Acme Band' AND SongTitle = 'Look Out, World';
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You can modify the WHERE clause to delete multiple rows. For example, you could delete all of the songs
by a particular artist, as shown following:
DELETE FROM Music WHERE Artist = 'The Acme Band'
Note
If you omit the WHERE clause, the database attempts to delete all of the rows from the table.
DynamoDB
In DynamoDB, you use the DeleteItem action to delete data from a table, one item at a time. You must
specify the item's primary key values. Here is an example:
{
}
TableName: &quot;Music&quot;,
Key: {
Artist: &quot;The Acme Band&quot;,
SongTitle: &quot;Look Out, World&quot;
}
Note
In addition to DeleteItem, Amazon DynamoDB supports a BatchWriteItem action for deleting
multiple items at the same time.
DeleteItem supports conditional writes, where the operation succeeds only if a speciﬁc
ConditionExpression evaluates to true. For example, the following DeleteItem action deletes the item
only if it has a RecordLabel attribute:
{
}
TableName: &quot;Music&quot;,
Key: {
Artist: &quot;The Acme Band&quot;,
SongTitle: &quot;Look Out, World&quot;
},
ConditionExpression: &quot;attribute_exists(RecordLabel)&quot;
Note
For code samples using DeleteItem, see Getting Started with DynamoDB (p. 52).
Removing a Table
In SQL, you use the DROP TABLE statement to remove a table. In DynamoDB, you use the DeleteTable
operation.
SQL
When you no longer need a table and want to discard it permanently, you use the DROP TABLE statement
in SQL:
DROP TABLE Music;
After a table is dropped, it cannot be recovered. (Some relational databases do allow you to undo a DROP
TABLE operation, but this is vendor-speciﬁc functionality and it is not widely implemented.)
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DynamoDB
DynamoDB has a similar action: DeleteTable. In the following example, the table is permanently deleted:
{
}
TableName: &quot;Music&quot;
Note
For code samples using DeleteTable, see Getting Started with DynamoDB (p. 52).
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Setting Up DynamoDB Local (Downloadable Version)
Setting Up DynamoDB
In addition to the Amazon DynamoDB web service, AWS provides a downloadable version of DynamoDB
that you can run on your computer. The downloadable version lets you write and test applications locally
without accessing the DynamoDB web service.
The topics in this section describe how to set up DynamoDB (Downloadable Version) and the DynamoDB
web service).
Topics
• Setting Up DynamoDB Local (Downloadable Version) (p. 41)
• Setting Up DynamoDB (Web Service) (p. 46)
Setting Up DynamoDB Local (Downloadable
Version)
The downloadable version of DynamoDB lets you write and test applications without accessing the
DynamoDB web service. Instead, the database is self-contained on your computer. When you're ready to
deploy your application in production, you can make a few minor changes to the code so that it uses the
DynamoDB web service.
Having this local version helps you save on provisioned throughput, data storage, and data transfer fees.
In addition, you don't need an Internet connection while you're developing your application.
Topics
• Downloading and Running DynamoDB on Your Computer (p. 41)
• Setting the Local Endpoint (p. 44)
• Usage Notes (p. 44)
Downloading and Running DynamoDB on Your
Computer
The downloadable version of DynamoDB is provided as an executable .jar ﬁle. The application runs on
Windows, Linux, macOS X, and other platforms that support Java.
Follow these steps to set up and run DynamoDB on your computer:
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1.
Download DynamoDB for free using one of the following links:
Region
Download Links
Checksums
Asia Paciﬁc (Mumbai) Region
.tar.gz | .zip
.tar.gz.sha256 | .zip.sha256
Asia Paciﬁc (Singapore) Region
.tar.gz | .zip
.tar.gz.sha256 | .zip.sha256
Asia Paciﬁc (Tokyo) Region
.tar.gz | .zip
.tar.gz.sha256 | .zip.sha256
EU (Frankfurt) Region
.tar.gz | .zip
.tar.gz.sha256 | .zip.sha256
South America (S&atilde;o Paulo)
Region
.tar.gz | .zip
.tar.gz.sha256 | .zip.sha256
US West (Oregon) Region
.tar.gz | .zip
.tar.gz.sha256 | .zip.sha256
Downloadable DynamoDB is available on Apache Maven. For more information, see DynamoDB
(Downloadable Version) and Apache Maven (p. 42), later in this topic. DynamoDB is also available
as part of the AWS Toolkit for Eclipse. For more information, see AWS Toolkit For Eclipse.
Important
2.
3.
To run DynamoDB on your computer, you must have the Java Runtime Environment (JRE)
version 6.x or newer. The application doesn't run on older JRE versions.
After you download the archive, extract the contents and copy the extracted directory to a location
of your choice.
To start DynamoDB on your computer, open a command prompt window, navigate to the directory
where you extracted DynamoDBLocal.jar, and type the following command:
java -Djava.library.path=./DynamoDBLocal_lib -jar DynamoDBLocal.jar -sharedDb
Note
DynamoDB processes incoming requests until you stop it. To stop DynamoDB, type Ctrl+C at
the command prompt.
DynamoDB uses port 8000 by default. If port 8000 is unavailable, this command throws
an exception. For a complete list of DynamoDB runtime options, including -port , type this
command:
java -Djava.library.path=./DynamoDBLocal_lib -jar DynamoDBLocal.jar -help
After completing these steps, you can start writing applications.
DynamoDB (Downloadable Version) and Apache Maven
To use DynamoDB in your application as a dependency:
1.
2.
Download and install Apache Maven. For more information, see Downloading Apache Maven and
Installing Apache Maven.
Add the DynamoDB Maven repository to your application's Project Object Model (POM) ﬁle:
&lt;!--Dependency:--&gt;
&lt;dependencies&gt;
&lt;dependency&gt;
&lt;groupId&gt;com.amazonaws&lt;/groupId&gt;
&lt;artifactId&gt;DynamoDBLocal&lt;/artifactId&gt;
&lt;version&gt;[1.11,2.0)&lt;/version&gt;
&lt;/dependency&gt;
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&lt;/dependencies&gt;
&lt;!--Custom repository:--&gt;
&lt;repositories&gt;
&lt;repository&gt;
&lt;id&gt;dynamodb-local-oregon&lt;/id&gt;
&lt;name&gt;DynamoDB Local Release Repository&lt;/name&gt;
&lt;url&gt;https://s3-us-west-2.amazonaws.com/dynamodb-local/release&lt;/url&gt;
&lt;/repository&gt;
&lt;/repositories&gt;
Note
Alternatively, you can use one of the following repository URLs, depending on your region:
id
Repository URL
dynamodb-local-mumbai
https://s3.ap-south-1.amazonaws.com/
dynamodb-local-mumbai/release
dynamodb-local-singapore
https://s3-apsoutheast-1.amazonaws.com/dynamodblocal-singapore/release
dynamodb-local-tokyo
https://s3-apnortheast-1.amazonaws.com/dynamodblocal-tokyo/release
dynamodb-local-frankfurt
https://s3.eu-central-1.amazonaws.com/
dynamodb-local-frankfurt/release
dynamodb-local-sao-paulo
https://s3-sa-east-1.amazonaws.com/
dynamodb-local-sao-paulo/release
The aws-dynamodb-examples repository in GitHub contains examples for starting and stopping
DynamoDB Local inside a Java program and using DynamoDB Local in JUnit tests.
Command Line Options
You can use the following command line options with the downloadable version of DynamoDB:
• -cors value — Enables support for cross-origin resource sharing (CORS) for JavaScript. You must
provide a comma-separated &quot;allow&quot; list of speciﬁc domains. The default setting for -cors is an asterisk
(*), which allows public access.
• -dbPath value — The directory where DynamoDB writes its database ﬁle. If you don't specify this
option, the ﬁle is written to the current directory. You can't specify both -dbPath and -inMemory at
once.
• -delayTransientStatuses — Causes DynamoDB to introduce delays for certain operations. DynamoDB
(Downloadable Version) can perform some tasks almost instantaneously, such as create/update/
delete operations on tables and indexes. However, the DynamoDB service requires more time for these
tasks. Setting this parameter helps DynamoDB running on your computer simulate the behavior of
the DynamoDB web service more closely. (Currently, this parameter introduces delays only for global
secondary indexes that are in either CREATING or DELETING status.)
• -help — Prints a usage summary and options.
• -inMemory — DynamoDB runs in memory instead of using a database ﬁle. When you stop DynamoDB,
none of the data is saved. You can't specify both -dbPath and -inMemory at once.
• -optimizeDbBeforeStartup — Optimizes the underlying database tables before starting DynamoDB
on your computer. You also must specify -dbPath when you use this parameter.
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Setting the Local Endpoint
• -port value — The port number that DynamoDB uses to communicate with your application. If you
don't specify this option, the default port is 8000.
Note
DynamoDB uses port 8000 by default. If port 8000 is unavailable, this command throws an
exception. You can use the -port option to specify a diﬀerent port number. For a complete list
of DynamoDB runtime options, including -port , type this command:
java -Djava.library.path=./DynamoDBLocal_lib -jar DynamoDBLocal.jar -help
• -sharedDb — DynamoDB uses a single database ﬁle instead of separate ﬁles for each credential and
region. If you specify -sharedDb, all DynamoDB clients interact with the same set of tables regardless
of their region and credential conﬁguration.
Setting the Local Endpoint
By default, the AWS SDKs and tools use endpoints for the Amazon DynamoDB web service. To use the
SDKs and tools with the downloadable version of DynamoDB, you must specify the local endpoint:
http://localhost:8000
AWS Command Line Interface
You can use the AWS Command Line Interface to interact with downloadable DynamoDB. For example,
you can use it to perform all the steps in Creating Tables and Loading Sample Data (p. 280).
To access DynamoDB running locally, use the --endpoint-url parameter. The following is an example of
using the AWS CLI to list the tables in DynamoDB on your computer:
aws dynamodb list-tables --endpoint-url http://localhost:8000
Note
The AWS CLI can't use the downloadable version of DynamoDB as a default endpoint; therefore,
you must specify --endpoint-url with each AWS CLI command.
AWS SDKs
The way you specify an endpoint depends on the programming language and AWS SDK you're using. The
following sections describe how to do this:
• Java: Setting the AWS Region and Endpoint (p. 287)
• .NET: Setting the AWS Region and Endpoint (p. 289)
Note
For examples in other programming languages, see Getting Started with DynamoDB (p. 52).
Usage Notes
Except for the endpoint, applications that run with the downloadable version of DynamoDB should also
work with the DynamoDB web service. However, when using DynamoDB locally, you should be aware of
the following:
• If you use the -sharedDb option, DynamoDB creates a single database ﬁle named shared-localinstance.db. Every program that connects to DynamoDB accesses this ﬁle. If you delete the ﬁle, you
lose any data you have stored in it.
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Usage Notes
• If you omit -sharedDb, the database ﬁle is named myaccesskeyid_region.db, with the AWS access key
ID and region as they appear in your application conﬁguration. If you delete the ﬁle, you lose any data
you have stored in it.
• If you use the -inMemory option, DynamoDB doesn't write any database ﬁles at all. Instead, all data is
written to memory, and the data is not saved when you terminate DynamoDB.
• If you use the -optimizeDbBeforeStartup option, you must also specify the -dbPath parameter so that
DynamoDB can ﬁnd its database ﬁle.
• The AWS SDKs for DynamoDB require that your application conﬁguration specify an access key value
and an AWS region value. Unless you're using the -sharedDb or the -inMemory option, DynamoDB uses
these values to name the local database ﬁle.
These values don't have to be valid AWS values to run locally. However, you might ﬁnd it convenient
to use valid values so that you can run your code in the cloud later simply by changing the endpoint
you're using.
Diﬀerences Between Downloadable DynamoDB and the
DynamoDB Web Service
The downloadable version of DynamoDB is intended for development and testing purposes only. By
comparison, the DynamoDB web service is a managed service with scalability, availability, and durability
features that make it ideal for production use.
The downloadable version of DynamoDB diﬀers from the web service in the following ways:
• Regions and distinct AWS accounts are not supported at the client level.
• Provisioned throughput settings are ignored in downloadable DynamoDB, even though the
CreateTable operation requires them. For CreateTable, you can specify any numbers you want
for provisioned read and write throughput, even though these numbers are not used. You can call
UpdateTable as many times as you want per day. However, any changes to provisioned throughput
values are ignored.
• Scan operations are performed sequentially. Parallel scans are not supported. The Segment and
TotalSegments parameters of the Scan operation are ignored.
• The speed of read and write operations on table data is limited only by the speed of your computer.
CreateTable, UpdateTable, and DeleteTable operations occur immediately, and table state is always
ACTIVE. UpdateTable operations that change only the provisioned throughput settings on tables
or global secondary indexes occur immediately. If an UpdateTable operation creates or deletes any
global secondary indexes, then those indexes transition through normal states (such as CREATING and
DELETING, respectively) before they become an ACTIVE state. The table remains ACTIVE during this
time.
• Read operations are eventually consistent. However, due to the speed of DynamoDB running on your
computer, most reads appear to be strongly consistent.
• Consumed capacity units are not tracked. In operation responses, nulls are returned instead of capacity
units.
• Item collection metrics and item collection sizes are not tracked. In operation responses, nulls are
returned instead of item collection metrics.
• In DynamoDB, there is a 1 MB limit on data returned per result set. Both the DynamoDB web service
and the downloadable version enforce this limit. However, when querying an index, the DynamoDB
service calculates only the size of the projected key and attributes. By contrast, the downloadable
version of DynamoDB calculates the size of the entire item.
• If you're using DynamoDB Streams, the rate at which shards are created might diﬀer. In the DynamoDB
web service, shard creation behavior is partially inﬂuenced by table partition activity. When you
run DynamoDB locally, there is no table partitioning. In either case, shards are ephemeral, so your
application should not be dependent on shard behavior.
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Setting Up DynamoDB (Web Service)
Setting Up DynamoDB (Web Service)
To use the Amazon DynamoDB web service:
1. Sign up for AWS. (p. 46)
2. Get an AWS access key (p. 46) (used to access DynamoDB programmatically).
Note
If you plan to interact with DynamoDB only through the AWS Management Console, you
don't need an AWS access key, and you can skip ahead to Using the Console (p. 48).
3. Conﬁgure your credentials (p. 47) (used to access DynamoDB programmatically).
Signing Up for AWS
To use the DynamoDB service, you must have an AWS account. If you don't already have an account, you
are prompted to create one when you sign up. You're not charged for any AWS services that you sign up
for unless you use them.
To sign up for AWS
1.
Open https://aws.amazon.com/, and then choose Create an AWS Account.
Note
2.
This might be unavailable in your browser if you previously signed into the AWS
Management Console. In that case, choose Sign In to the Console, and then choose Create
a new AWS account.
Follow the online instructions.
Part of the sign-up procedure involves receiving a phone call and entering a PIN using the phone
keypad.
Getting an AWS Access Key
Before you can access DynamoDB programmatically or through the AWS Command Line Interface, you
must have an AWS access key. You don't need an access key if you plan to use the DynamoDB console
only.
To get the access key ID and secret access key for an IAM user
Access keys consist of an access key ID and secret access key, which are used to sign programmatic
requests that you make to AWS. If you don't have access keys, you can create them from the AWS
Management Console. We recommend that you use IAM access keys instead of AWS account root user
access keys. IAM lets you securely control access to AWS services and resources in your AWS account.
The only time that you can view or download the secret access keys is when you create the keys. You
cannot recover them later. However, you can create new access keys at any time. You must also have
permissions to perform the required IAM actions. For more information, see Delegating Permissions to
Administer IAM Users, Groups, and Credentials in the IAM User Guide.
1.
Open the IAM console.
2.
3.
4.
5.
In the navigation pane of the console, choose Users.
Choose your IAM user name (not the check box).
Choose the Security credentials tab and then choose Create access key.
To see the new access key, choose Show. Your credentials will look something like this:
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Conﬁguring Your Credentials
6.
• Access key ID: AKIAIOSFODNN7EXAMPLE
• Secret access key: wJalrXUtnFEMI/K7MDENG/bPxRﬁCYEXAMPLEKEY
To download the key pair, choose Download .csv ﬁle. Store the keys in a secure location.
Keep the keys conﬁdential in order to protect your account, and never email them. Do not share
them outside your organization, even if an inquiry appears to come from AWS or Amazon.com. No
one who legitimately represents Amazon will ever ask you for your secret key.
Related topics
• What Is IAM? in the IAM User Guide
• AWS Security Credentials in AWS General Reference
Conﬁguring Your Credentials
Before you can access DynamoDB programmatically or through the AWS CLI, you must conﬁgure your
credentials to enable authorization for your applications.
There are several ways to do this. For example, you can manually create the credentials ﬁle to store your
AWS access key ID and secret access key. You can also use the aws configure command of the AWS CLI
to automatically create the ﬁle. Alternatively, you can use environment variables. For more information
on conﬁguring your credentials, see the programming-speciﬁc AWS SDK developer guide.
To install and conﬁgure the AWS CLI, see Using the CLI (p. 49).
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Using the Console
Accessing DynamoDB
You can access Amazon DynamoDB using the AWS Management Console, the AWS Command Line
Interface (AWS CLI), or the DynamoDB API.
Topics
• Using the Console (p. 48)
• Using the CLI (p. 49)
• Using the API (p. 51)
Using the Console
You can access the AWS Management Console for DynamoDB here: https://console.aws.amazon.com/
dynamodb/home.
You can use the console to do the following in DynamoDB:
• Monitor recent alerts, total capacity, service health, and the latest DynamoDB news on the DynamoDB
dashboard.
• Create, update, and delete tables. The capacity calculator provides estimates of how many capacity
units to request based on the usage information you provide.
• Manage streams.
• View, add, update, and delete items that are stored in tables. Manage Time To Live (TTL) to deﬁne
when items in a table expire so that they can be automatically deleted from the database.
• Query and scan a table.
• Set up and view alarms to monitor your table's capacity usage. View your table's top monitoring
metrics on real-time graphs from CloudWatch.
• Modify a table's provisioned capacity.
• Create and delete global secondary indexes.
• Create triggers to connect DynamoDB streams to AWS Lambda functions.
• Apply tags to your resources to help organize and identify them.
• Purchase reserved capacity.
The console displays an introductory screen that prompts you to create your ﬁrst table. To view your
tables, from the navigation pane on the left side of the console, choose Tables.
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Using the CLI
Here's a high-level overview of the actions available per table within each navigation tab:
• Overview – View stream and table details, and manage streams and Time To Live (TTL).
• Items – Manage items and perform queries and scans.
• Metrics – Monitor CloudWatch metrics.
• Alarms – Manage CloudWatch alarms.
• Capacity – Modify a table's provisioned capacity.
• Indexes – Manage global secondary indexes.
• Triggers – Manage triggers to connect DynamoDB streams to Lambda functions.
• Access control – Set up ﬁne-grained access control with web identity federation.
• Tags – Apply tags to your resources to help organize and identify them.
Using the CLI
You can use the AWS Command Line Interface (AWS CLI) to control multiple AWS services from the
command line and automate them through scripts. You can use the AWS CLI for ad hoc operations, such
as creating a table. You can also use it to embed DynamoDB operations within utility scripts.
Before you can use the AWS CLI with DynamoDB, you must get an access key ID and secret access key. For
more information, see Getting an AWS Access Key (p. 46).
For a complete listing of all the commands available for DynamoDB in the AWS CLI, go to http://
docs.aws.amazon.com/cli/latest/reference/dynamodb/index.html.
Topics
• Downloading and Conﬁguring the AWS CLI (p. 49)
• Using the AWS CLI with DynamoDB (p. 49)
• Using the AWS CLI with Downloadable DynamoDB (p. 50)
Downloading and Conﬁguring the AWS CLI
The AWS CLI is available at http://aws.amazon.com/cli. It runs on Windows, macOS, or Linux. After you
download the AWS CLI, follow these steps to install and conﬁgure it:
1.
Go to the AWS Command Line Interface User Guide.
2.
Follow the instructions for Installing the AWS CLI and Conﬁguring the AWS CLI.
Using the AWS CLI with DynamoDB
The command line format consists of a DynamoDB operation name, followed by the parameters for that
operation. The AWS CLI supports a shorthand syntax for the parameter values, as well as JSON.
For example, the following command creates a table named Music. The partition key is Artist, and the
sort key is SongTitle. (For easier readability, long commands in this section are broken into separate
lines.)
aws dynamodb create-table \
--table-name Music \
--attribute-definitions \
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Using the AWS CLI with Downloadable DynamoDB
AttributeName=Artist,AttributeType=S \
AttributeName=SongTitle,AttributeType=S \
--key-schema AttributeName=Artist,KeyType=HASH AttributeName=SongTitle,KeyType=RANGE \
--provisioned-throughput ReadCapacityUnits=1,WriteCapacityUnits=1
The following commands add new items to the table. These examples use a combination of shorthand
syntax and JSON.
aws dynamodb put-item \
--table-name Music \
--item \
'{&quot;Artist&quot;: {&quot;S&quot;: &quot;No One You Know&quot;}, &quot;SongTitle&quot;: {&quot;S&quot;: &quot;Call Me Today&quot;},
&quot;AlbumTitle&quot;: {&quot;S&quot;: &quot;Somewhat Famous&quot;}}' \
--return-consumed-capacity TOTAL
aws dynamodb put-item \
--table-name Music \
--item '{ \
&quot;Artist&quot;: {&quot;S&quot;: &quot;Acme Band&quot;}, \
&quot;SongTitle&quot;: {&quot;S&quot;: &quot;Happy Day&quot;}, \
&quot;AlbumTitle&quot;: {&quot;S&quot;: &quot;Songs About Life&quot;} }' \
--return-consumed-capacity TOTAL
On the command line, it can be diﬃcult to compose valid JSON. However, the AWS CLI can read
JSON ﬁles. For example, consider the following JSON snippet, which is stored in a ﬁle named keyconditions.json:
{
}
&quot;Artist&quot;: {
&quot;AttributeValueList&quot;: [
{
&quot;S&quot;: &quot;No One You Know&quot;
}
],
&quot;ComparisonOperator&quot;: &quot;EQ&quot;
},
&quot;SongTitle&quot;: {
&quot;AttributeValueList&quot;: [
{
&quot;S&quot;: &quot;Call Me Today&quot;
}
],
&quot;ComparisonOperator&quot;: &quot;EQ&quot;
}
You can now issue a Query request using the AWS CLI. In this example, the contents of the keyconditions.json ﬁle are used for the --key-conditions parameter:
aws dynamodb query --table-name Music --key-conditions file://key-conditions.json
Using the AWS CLI with Downloadable DynamoDB
The AWS CLI can also interact with DynamoDB (Downloadable Version) that runs on your computer. To
enable this, add the following parameter to each command:
--endpoint-url http://localhost:8000
Here is an example that uses the AWS CLI to list the tables in a local database:
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Using the API
aws dynamodb list-tables --endpoint-url http://localhost:8000
If DynamoDB is using a port number other than the default (8000), modify the --endpoint-url value
accordingly.
Note
The AWS CLI can't use the downloadable version of DynamoDB as a default endpoint. Therefore,
you must specify --endpoint-url with each command.
Using the API
You can use the AWS Management Console and the AWS Command Line Interface to work interactively
with Amazon DynamoDB. However, to get the most out of DynamoDB, you can write application code
using the AWS SDKs.
The AWS SDKs provide broad support for DynamoDB in Java, JavaScript in the browser, .NET, Node.js,
PHP, Python, Ruby, C++, Go, Android, and iOS. To get started quickly with these languages, see Getting
Started with DynamoDB (p. 52).
Before you can use the AWS SDKs with DynamoDB, you must get an AWS access key ID and secret access
key. For more information, see Setting Up DynamoDB (Web Service) (p. 46).
For a high-level overview of DynamoDB application programming with the AWS SDKs, see Programming
with DynamoDB and the AWS SDKs (p. 180).
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Java and DynamoDB
Getting Started with DynamoDB
This section contains hands-on tutorials to help you learn about Amazon DynamoDB. We encourage
you to work through one of the language-speciﬁc tutorials. The sample code in these tutorials can run
against either the downloadable version of DynamoDB or the Amazon DynamoDB web service.
Note
AWS SDKs are available for a wide variety of languages. For a complete list, see Tools for
Amazon Web Services.
Topics
• Java and DynamoDB (p. 52)
• JavaScript and DynamoDB (p. 69)
• Node.js and DynamoDB (p. 89)
• .NET and DynamoDB (p. 103)
• PHP and DynamoDB (p. 132)
• Python and DynamoDB (p. 149)
• Ruby and DynamoDB (p. 164)
Java and DynamoDB
In this tutorial, you use the AWS SDK for Java to write simple programs to perform the following Amazon
DynamoDB operations:
• Create a table called Movies and load sample data in JSON format.
• Perform create, read, update, and delete operations on the table.
• Run simple queries.
The SDK for Java oﬀers several programming models for diﬀerent use cases. In this exercise, the Java
code uses the document model that provides a level of abstraction that makes it easier for you to work
with JSON documents.
You use the downloadable version of DynamoDB in this tutorial. For information about how to run the
same code against the DynamoDB web service, see the Summary (p. 68).
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Prerequisites
As you work through this tutorial, you can refer to the AWS SDK for Java API Reference.
Prerequisites
• Download and run DynamoDB on your computer. For more information, see Setting Up DynamoDB
Local (Downloadable Version) (p. 41).
DynamoDB (Downloadable Version) is also available as part of the AWS Toolkit for Eclipse. For more
information, see AWS Toolkit For Eclipse.
• Set up an AWS access key to use the AWS SDKs. For more information, see Setting Up DynamoDB (Web
Service) (p. 46).
• Set up the AWS SDK for Java:
• Install a Java development environment. If you are using the Eclipse IDE, install the AWS Toolkit for
Eclipse.
• Install the AWS SDK for Java.
• Set up your AWS security credentials for use with the SDK for Java.
For instructions, see Getting Started in the AWS SDK for Java Developer Guide.
Step 1: Create a Table
In this step, you create a table named Movies. The primary key for the table is composed of the following
attributes:
• year – The partition key. The ScalarAttributeType is N for number.
• title – The sort key. The ScalarAttributeType is S for string.
1.
Copy and paste the following program into your Java development environment:
// Copyright 2012-2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
// Licensed under the Apache License, Version 2.0.
package com.amazonaws.codesamples.gsg;
import java.util.Arrays;
import
import
import
import
import
import
import
import
import
import
com.amazonaws.client.builder.AwsClientBuilder;
com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
com.amazonaws.services.dynamodbv2.document.DynamoDB;
com.amazonaws.services.dynamodbv2.document.Table;
com.amazonaws.services.dynamodbv2.model.AttributeDefinition;
com.amazonaws.services.dynamodbv2.model.KeySchemaElement;
com.amazonaws.services.dynamodbv2.model.KeyType;
com.amazonaws.services.dynamodbv2.model.ProvisionedThroughput;
com.amazonaws.services.dynamodbv2.model.ScalarAttributeType;
public class MoviesCreateTable {
public static void main(String[] args) throws Exception {
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard()
.withEndpointConfiguration(new
AwsClientBuilder.EndpointConfiguration(&quot;http://localhost:8000&quot;, &quot;us-west-2&quot;))
.build();
DynamoDB dynamoDB = new DynamoDB(client);
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Step 2: Load Sample Data
String tableName = &quot;Movies&quot;;
try {
System.out.println(&quot;Attempting to create table; please wait...&quot;);
Table table = dynamoDB.createTable(tableName,
Arrays.asList(new KeySchemaElement(&quot;year&quot;, KeyType.HASH), // Partition
// key
new KeySchemaElement(&quot;title&quot;, KeyType.RANGE)), // Sort key
Arrays.asList(new AttributeDefinition(&quot;year&quot;, ScalarAttributeType.N),
new AttributeDefinition(&quot;title&quot;, ScalarAttributeType.S)),
new ProvisionedThroughput(10L, 10L));
table.waitForActive();
System.out.println(&quot;Success. Table status: &quot; +
table.getDescription().getTableStatus());
}
catch (Exception e) {
System.err.println(&quot;Unable to create table: &quot;);
System.err.println(e.getMessage());
}
}
}
Note
• You set the endpoint to indicate that you are creating the table in DynamoDB on your
computer.
• In the createTable call, you specify table name, primary key attributes, and its data
types.
• The ProvisionedThroughput parameter is required, but the downloadable version of
DynamoDB ignores it. (Provisioned throughput is beyond the scope of this exercise.)
2.
Compile and run the program.
To learn more about managing tables, see Working with Tables in DynamoDB (p. 290).
Step 2: Load Sample Data
In this step, you populate the Movies table with sample data.
Topics
• Step 2.1: Download the Sample Data File (p. 55)
• Step 2.2: Load the Sample Data into the Movies Table (p. 55)
This scenario uses a sample data ﬁle that contains information about a few thousand movies from the
Internet Movie Database (IMDb). The movie data is in JSON format, as shown in the following example.
For each movie, there is a year, a title, and a JSON map named info.
[
{
},
{
&quot;year&quot; : ... ,
&quot;title&quot; : ... ,
&quot;info&quot; : { ... }
&quot;year&quot; : ...,
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Step 2: Load Sample Data
},
&quot;title&quot; : ...,
&quot;info&quot; : { ... }
...
]
In the JSON data, note the following:
• You use the year and title as the primary key attribute values for the Movies table.
• You store the rest of the info values in a single attribute called info. This program illustrates how you
can store JSON in a DynamoDB attribute.
The following is an example of movie data:
{
&quot;year&quot; : 2013,
&quot;title&quot; : &quot;Turn It Down, Or Else!&quot;,
&quot;info&quot; : {
&quot;directors&quot; : [
&quot;Alice Smith&quot;,
&quot;Bob Jones&quot;
],
&quot;release_date&quot; : &quot;2013-01-18T00:00:00Z&quot;,
&quot;rating&quot; : 6.2,
&quot;genres&quot; : [
&quot;Comedy&quot;,
&quot;Drama&quot;
],
&quot;image_url&quot; : &quot;http://ia.media-imdb.com/images/N/
O9ERWAU7FS797AJ7LU8HN09AMUP908RLlo5JF90EWR7LJKQ7@@._V1_SX400_.jpg&quot;,
&quot;plot&quot; : &quot;A rock band plays their music at high volumes, annoying the neighbors.&quot;,
&quot;rank&quot; : 11,
&quot;running_time_secs&quot; : 5215,
&quot;actors&quot; : [
&quot;David Matthewman&quot;,
&quot;Ann Thomas&quot;,
&quot;Jonathan G. Neff&quot;
]
}
}
Step 2.1: Download the Sample Data File
1.
Download the sample data archive: moviedata.zip
2.
Extract the data ﬁle (moviedata.json) from the archive.
3.
Copy and paste the moviedata.json ﬁle into your current directory.
Step 2.2: Load the Sample Data into the Movies Table
After you download the sample data, you can run the following program to populate the Movies table.
1.
Copy and paste the following program into your Java development environment:
// Copyright 2012-2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
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Step 2: Load Sample Data
package com.amazonaws.codesamples.gsg;
import java.io.File;
import java.util.Iterator;
import
import
import
import
import
import
import
import
import
import
import
com.amazonaws.client.builder.AwsClientBuilder;
com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
com.amazonaws.services.dynamodbv2.document.DynamoDB;
com.amazonaws.services.dynamodbv2.document.Item;
com.amazonaws.services.dynamodbv2.document.Table;
com.fasterxml.jackson.core.JsonFactory;
com.fasterxml.jackson.core.JsonParser;
com.fasterxml.jackson.databind.JsonNode;
com.fasterxml.jackson.databind.ObjectMapper;
com.fasterxml.jackson.databind.node.ObjectNode;
public class MoviesLoadData {
public static void main(String[] args) throws Exception {
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard()
.withEndpointConfiguration(new
AwsClientBuilder.EndpointConfiguration(&quot;http://localhost:8000&quot;, &quot;us-west-2&quot;))
.build();
DynamoDB dynamoDB = new DynamoDB(client);
Table table = dynamoDB.getTable(&quot;Movies&quot;);
JsonParser parser = new JsonFactory().createParser(new File(&quot;moviedata.json&quot;));
JsonNode rootNode = new ObjectMapper().readTree(parser);
Iterator&lt;JsonNode&gt; iter = rootNode.iterator();
ObjectNode currentNode;
while (iter.hasNext()) {
currentNode = (ObjectNode) iter.next();
int year = currentNode.path(&quot;year&quot;).asInt();
String title = currentNode.path(&quot;title&quot;).asText();
try {
table.putItem(new Item().withPrimaryKey(&quot;year&quot;, year, &quot;title&quot;,
title).withJSON(&quot;info&quot;,
currentNode.path(&quot;info&quot;).toString()));
System.out.println(&quot;PutItem succeeded: &quot; + year + &quot; &quot; + title);
}
catch (Exception e) {
System.err.println(&quot;Unable to add movie: &quot; + year + &quot; &quot; + title);
System.err.println(e.getMessage());
break;
}
}
}
}
parser.close();
This program uses the open source Jackson library to process JSON. Jackson is included in the AWS
SDK for Java. You don't have to install it separately.
2.
Compile and run the program.
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Step 3: Create, Read, Update, and Delete an Item
Step 3: Create, Read, Update, and Delete an Item
In this step, you perform read and write operations on an item in the Movies table.
To learn more about reading and writing data, see Working with Items in DynamoDB (p. 327).
Topics
• Step 3.1: Create a New Item (p. 57)
• Step 3.2: Read an Item (p. 58)
• Step 3.3: Update an Item (p. 59)
• Step 3.4: Increment an Atomic Counter (p. 61)
• Step 3.5: Update an Item (Conditionally) (p. 62)
• Step 3.6: Delete an Item (p. 63)
Step 3.1: Create a New Item
In this step, you add a new item to the Movies table.
1.
Copy and paste the following program into your Java development environment.
// Copyright 2012-2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
// Licensed under the Apache License, Version 2.0.
package com.amazonaws.codesamples.gsg;
import java.util.HashMap;
import java.util.Map;
import
import
import
import
import
import
import
com.amazonaws.client.builder.AwsClientBuilder;
com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
com.amazonaws.services.dynamodbv2.document.DynamoDB;
com.amazonaws.services.dynamodbv2.document.Item;
com.amazonaws.services.dynamodbv2.document.PutItemOutcome;
com.amazonaws.services.dynamodbv2.document.Table;
public class MoviesItemOps01 {
public static void main(String[] args) throws Exception {
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard()
.withEndpointConfiguration(new
AwsClientBuilder.EndpointConfiguration(&quot;http://localhost:8000&quot;, &quot;us-west-2&quot;))
.build();
DynamoDB dynamoDB = new DynamoDB(client);
Table table = dynamoDB.getTable(&quot;Movies&quot;);
int year = 2015;
String title = &quot;The Big New Movie&quot;;
final Map&lt;String, Object&gt; infoMap = new HashMap&lt;String, Object&gt;();
infoMap.put(&quot;plot&quot;, &quot;Nothing happens at all.&quot;);
infoMap.put(&quot;rating&quot;, 0);
try {
System.out.println(&quot;Adding a new item...&quot;);
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Step 3: Create, Read, Update, and Delete an Item
PutItemOutcome outcome = table
.putItem(new Item().withPrimaryKey(&quot;year&quot;, year, &quot;title&quot;,
title).withMap(&quot;info&quot;, infoMap));
System.out.println(&quot;PutItem succeeded:\n&quot; + outcome.getPutItemResult());
}
catch (Exception e) {
System.err.println(&quot;Unable to add item: &quot; + year + &quot; &quot; + title);
System.err.println(e.getMessage());
}
}
}
Note
The primary key is required. This code adds an item that has primary key (year, title) and
info attributes. The info attribute stores sample JSON that provides more information
about the movie.
2.
Compile and run the program.
Step 3.2: Read an Item
In the previous program, you added the following item to the table:
{
}
year: 2015,
title: &quot;The Big New Movie&quot;,
info: {
plot: &quot;Nothing happens at all.&quot;,
rating: 0
}
You can use the getItem method to read the item from the Movies table. You must specify the primary
key values, so you can read any item from Movies if you know its year and title.
1.
Copy and paste the following program into your Java development environment:
// Copyright 2012-2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
// Licensed under the Apache License, Version 2.0.
package com.amazonaws.codesamples.gsg;
import
import
import
import
import
import
import
com.amazonaws.client.builder.AwsClientBuilder;
com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
com.amazonaws.services.dynamodbv2.document.DynamoDB;
com.amazonaws.services.dynamodbv2.document.Item;
com.amazonaws.services.dynamodbv2.document.Table;
com.amazonaws.services.dynamodbv2.document.spec.GetItemSpec;
public class MoviesItemOps02 {
public static void main(String[] args) throws Exception {
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard()
.withEndpointConfiguration(new
AwsClientBuilder.EndpointConfiguration(&quot;http://localhost:8000&quot;, &quot;us-west-2&quot;))
.build();
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Step 3: Create, Read, Update, and Delete an Item
DynamoDB dynamoDB = new DynamoDB(client);
Table table = dynamoDB.getTable(&quot;Movies&quot;);
int year = 2015;
String title = &quot;The Big New Movie&quot;;
GetItemSpec spec = new GetItemSpec().withPrimaryKey(&quot;year&quot;, year, &quot;title&quot;,
title);
try {
System.out.println(&quot;Attempting to read the item...&quot;);
Item outcome = table.getItem(spec);
System.out.println(&quot;GetItem succeeded: &quot; + outcome);
}
catch (Exception e) {
System.err.println(&quot;Unable to read item: &quot; + year + &quot; &quot; + title);
System.err.println(e.getMessage());
}
}
2.
}
Compile and run the program.
Step 3.3: Update an Item
You can use the updateItem method to modify an existing item. You can update values of existing
attributes, add new attributes, or remove attributes.
In this example, you perform the following updates:
• Change the value of the existing attributes (rating, plot).
• Add a new list attribute (actors) to the existing info map.
The item changes from this:
{
}
year: 2015,
title: &quot;The Big New Movie&quot;,
info: {
plot: &quot;Nothing happens at all.&quot;,
rating: 0
}
To the following:
{
}
year: 2015,
title: &quot;The Big New Movie&quot;,
info: {
plot: &quot;Everything happens all at once.&quot;,
rating: 5.5,
actors: [&quot;Larry&quot;, &quot;Moe&quot;, &quot;Curly&quot;]
}
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1.
Copy and paste the following program into your Java development environment:
// Copyright 2012-2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
// Licensed under the Apache License, Version 2.0.
package com.amazonaws.codesamples.gsg;
import java.util.Arrays;
import
import
import
import
import
import
import
import
import
com.amazonaws.client.builder.AwsClientBuilder;
com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
com.amazonaws.services.dynamodbv2.document.DynamoDB;
com.amazonaws.services.dynamodbv2.document.Table;
com.amazonaws.services.dynamodbv2.document.UpdateItemOutcome;
com.amazonaws.services.dynamodbv2.document.spec.UpdateItemSpec;
com.amazonaws.services.dynamodbv2.document.utils.ValueMap;
com.amazonaws.services.dynamodbv2.model.ReturnValue;
public class MoviesItemOps03 {
public static void main(String[] args) throws Exception {
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard()
.withEndpointConfiguration(new
AwsClientBuilder.EndpointConfiguration(&quot;http://localhost:8000&quot;, &quot;us-west-2&quot;))
.build();
DynamoDB dynamoDB = new DynamoDB(client);
Table table = dynamoDB.getTable(&quot;Movies&quot;);
int year = 2015;
String title = &quot;The Big New Movie&quot;;
UpdateItemSpec updateItemSpec = new UpdateItemSpec().withPrimaryKey(&quot;year&quot;,
year, &quot;title&quot;, title)
.withUpdateExpression(&quot;set info.rating = :r, info.plot=:p, info.actors=:a&quot;)
.withValueMap(new ValueMap().withNumber(&quot;:r&quot;, 5.5).withString(&quot;:p&quot;,
&quot;Everything happens all at once.&quot;)
.withList(&quot;:a&quot;, Arrays.asList(&quot;Larry&quot;, &quot;Moe&quot;, &quot;Curly&quot;)))
.withReturnValues(ReturnValue.UPDATED_NEW);
try {
System.out.println(&quot;Updating the item...&quot;);
UpdateItemOutcome outcome = table.updateItem(updateItemSpec);
System.out.println(&quot;UpdateItem succeeded:\n&quot; +
outcome.getItem().toJSONPretty());
}
}
}
catch (Exception e) {
System.err.println(&quot;Unable to update item: &quot; + year + &quot; &quot; + title);
System.err.println(e.getMessage());
}
Note
This program uses an UpdateExpression to describe all updates you want to perform on the
speciﬁed item.
The ReturnValues parameter instructs DynamoDB to return only the updated attributes
(UPDATED_NEW).
2.
Compile and run the program.
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Step 3.4: Increment an Atomic Counter
DynamoDB supports atomic counters, where you use the updateItem method to increment or decrement
the value of an existing attribute without interfering with other write requests. (All write requests are
applied in the order in which they are received.)
The following program shows how to increment the rating for a movie. Each time you run it, the
program increments this attribute by one.
1.
Copy and paste the following program into your Java development environment:
// Copyright 2012-2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
// Licensed under the Apache License, Version 2.0.
package com.amazonaws.codesamples.gsg;
import
import
import
import
import
import
import
import
import
com.amazonaws.client.builder.AwsClientBuilder;
com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
com.amazonaws.services.dynamodbv2.document.DynamoDB;
com.amazonaws.services.dynamodbv2.document.Table;
com.amazonaws.services.dynamodbv2.document.UpdateItemOutcome;
com.amazonaws.services.dynamodbv2.document.spec.UpdateItemSpec;
com.amazonaws.services.dynamodbv2.document.utils.ValueMap;
com.amazonaws.services.dynamodbv2.model.ReturnValue;
public class MoviesItemOps04 {
public static void main(String[] args) throws Exception {
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard()
.withEndpointConfiguration(new
AwsClientBuilder.EndpointConfiguration(&quot;http://localhost:8000&quot;, &quot;us-west-2&quot;))
.build();
DynamoDB dynamoDB = new DynamoDB(client);
Table table = dynamoDB.getTable(&quot;Movies&quot;);
int year = 2015;
String title = &quot;The Big New Movie&quot;;
UpdateItemSpec updateItemSpec = new UpdateItemSpec().withPrimaryKey(&quot;year&quot;,
year, &quot;title&quot;, title)
.withUpdateExpression(&quot;set info.rating = info.rating + :val&quot;)
.withValueMap(new ValueMap().withNumber(&quot;:val&quot;,
1)).withReturnValues(ReturnValue.UPDATED_NEW);
try {
System.out.println(&quot;Incrementing an atomic counter...&quot;);
UpdateItemOutcome outcome = table.updateItem(updateItemSpec);
System.out.println(&quot;UpdateItem succeeded:\n&quot; +
outcome.getItem().toJSONPretty());
}
2.
}
}
catch (Exception e) {
System.err.println(&quot;Unable to update item: &quot; + year + &quot; &quot; + title);
System.err.println(e.getMessage());
}
Compile and run the program.
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Step 3.5: Update an Item (Conditionally)
The following program shows how to use UpdateItem with a condition. If the condition evaluates to true,
the update succeeds; otherwise, the update is not performed.
In this case, the movie item is updated only if there are more than three actors.
1.
Copy and paste the following program into your Java development environment:
// Copyright 2012-2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
// Licensed under the Apache License, Version 2.0.
package com.amazonaws.codesamples.gsg;
import
import
import
import
import
import
import
import
import
import
com.amazonaws.client.builder.AwsClientBuilder;
com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
com.amazonaws.services.dynamodbv2.document.DynamoDB;
com.amazonaws.services.dynamodbv2.document.PrimaryKey;
com.amazonaws.services.dynamodbv2.document.Table;
com.amazonaws.services.dynamodbv2.document.UpdateItemOutcome;
com.amazonaws.services.dynamodbv2.document.spec.UpdateItemSpec;
com.amazonaws.services.dynamodbv2.document.utils.ValueMap;
com.amazonaws.services.dynamodbv2.model.ReturnValue;
public class MoviesItemOps05 {
public static void main(String[] args) throws Exception {
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard()
.withEndpointConfiguration(new
AwsClientBuilder.EndpointConfiguration(&quot;http://localhost:8000&quot;, &quot;us-west-2&quot;))
.build();
DynamoDB dynamoDB = new DynamoDB(client);
Table table = dynamoDB.getTable(&quot;Movies&quot;);
int year = 2015;
String title = &quot;The Big New Movie&quot;;
UpdateItemSpec updateItemSpec = new UpdateItemSpec()
.withPrimaryKey(new PrimaryKey(&quot;year&quot;, year, &quot;title&quot;,
title)).withUpdateExpression(&quot;remove info.actors[0]&quot;)
.withConditionExpression(&quot;size(info.actors) &gt; :num&quot;).withValueMap(new
ValueMap().withNumber(&quot;:num&quot;, 3))
.withReturnValues(ReturnValue.UPDATED_NEW);
// Conditional update (we expect this to fail)
try {
System.out.println(&quot;Attempting a conditional update...&quot;);
UpdateItemOutcome outcome = table.updateItem(updateItemSpec);
System.out.println(&quot;UpdateItem succeeded:\n&quot; +
outcome.getItem().toJSONPretty());
}
2.
}
}
catch (Exception e) {
System.err.println(&quot;Unable to update item: &quot; + year + &quot; &quot; + title);
System.err.println(e.getMessage());
}
Compile and run the program.
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The program should fail with the following message:
The conditional request failed
This is because the movie has three actors in it, but the condition is checking for greater than three
actors.
3.
Modify the program so that the ConditionExpression looks like this:
.withConditionExpression(&quot;size(info.actors) &gt;= :num&quot;)
The condition is now greater than or equal to 3 instead of greater than 3.
4.
Compile and run the program. The UpdateItem operation should now succeed.
Step 3.6: Delete an Item
You can use the deleteItem method to delete one item by specifying its primary key. You can optionally
provide a ConditionExpression to prevent the item from being deleted if the condition is not met.
In the following example, you try to delete a speciﬁc movie item if its rating is 5 or less.
1.
Copy and paste the following program into your Java development environment:
// Copyright 2012-2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
// Licensed under the Apache License, Version 2.0.
package com.amazonaws.codesamples.gsg;
import
import
import
import
import
import
import
import
com.amazonaws.client.builder.AwsClientBuilder;
com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
com.amazonaws.services.dynamodbv2.document.DynamoDB;
com.amazonaws.services.dynamodbv2.document.PrimaryKey;
com.amazonaws.services.dynamodbv2.document.Table;
com.amazonaws.services.dynamodbv2.document.spec.DeleteItemSpec;
com.amazonaws.services.dynamodbv2.document.utils.ValueMap;
public class MoviesItemOps06 {
public static void main(String[] args) throws Exception {
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard()
.withEndpointConfiguration(new
AwsClientBuilder.EndpointConfiguration(&quot;http://localhost:8000&quot;, &quot;us-west-2&quot;))
.build();
DynamoDB dynamoDB = new DynamoDB(client);
Table table = dynamoDB.getTable(&quot;Movies&quot;);
int year = 2015;
String title = &quot;The Big New Movie&quot;;
DeleteItemSpec deleteItemSpec = new DeleteItemSpec()
.withPrimaryKey(new PrimaryKey(&quot;year&quot;, year, &quot;title&quot;,
title)).withConditionExpression(&quot;info.rating &lt;= :val&quot;)
.withValueMap(new ValueMap().withNumber(&quot;:val&quot;, 5.0));
// Conditional delete (we expect this to fail)
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}
2.
}
try {
System.out.println(&quot;Attempting a conditional delete...&quot;);
table.deleteItem(deleteItemSpec);
System.out.println(&quot;DeleteItem succeeded&quot;);
}
catch (Exception e) {
System.err.println(&quot;Unable to delete item: &quot; + year + &quot; &quot; + title);
System.err.println(e.getMessage());
}
Compile and run the program.
The program should fail with the following message:
The conditional request failed
This is because the rating for this particular move is greater than 5.
3.
Modify the program to remove the condition in DeleteItemSpec.
DeleteItemSpec deleteItemSpec = new DeleteItemSpec()
.withPrimaryKey(new PrimaryKey(&quot;year&quot;, 2015, &quot;title&quot;, &quot;The Big New Movie&quot;));
4.
Compile and run the program. Now, the delete succeeds because you removed the condition.
Step 4: Query and Scan the Data
You can use the query method to retrieve data from a table. You must specify a partition key value. The
sort key is optional.
The primary key for the Movies table is composed of the following:
• year – The partition key. The attribute type is number.
• title – The sort key. The attribute type is string.
To ﬁnd all movies released during a year, you need to specify only the year. You can also provide the
title to retrieve a subset of movies based on some condition (on the sort key); for example, to ﬁnd
movies released in 2014 that have a title starting with the letter &quot;A&quot;.
In addition to query, there is also a scan method that can retrieve all of the table data.
To learn more about querying and scanning data, see Working with Queries (p. 410) and Working with
Scans (p. 427), respectively.
Topics
• Step 4.1: Query (p. 64)
• Step 4.2: Scan (p. 66)
Step 4.1: Query
The code included in this step performs the following queries:
• Retrieve all movies released in the year 1985.
• Retrieve all movies released in the year 1992, with a title beginning with the letter &quot;A&quot; through the
letter &quot;L&quot;.
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1.
Copy and paste the following program into your Java development environment:
// Copyright 2012-2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
// Licensed under the Apache License, Version 2.0.
package com.amazonaws.codesamples.gsg;
import java.util.HashMap;
import java.util.Iterator;
import
import
import
import
import
import
import
import
import
com.amazonaws.client.builder.AwsClientBuilder;
com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
com.amazonaws.services.dynamodbv2.document.DynamoDB;
com.amazonaws.services.dynamodbv2.document.Item;
com.amazonaws.services.dynamodbv2.document.ItemCollection;
com.amazonaws.services.dynamodbv2.document.QueryOutcome;
com.amazonaws.services.dynamodbv2.document.Table;
com.amazonaws.services.dynamodbv2.document.spec.QuerySpec;
public class MoviesQuery {
public static void main(String[] args) throws Exception {
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard()
.withEndpointConfiguration(new
AwsClientBuilder.EndpointConfiguration(&quot;http://localhost:8000&quot;, &quot;us-west-2&quot;))
.build();
DynamoDB dynamoDB = new DynamoDB(client);
Table table = dynamoDB.getTable(&quot;Movies&quot;);
HashMap&lt;String, String&gt; nameMap = new HashMap&lt;String, String&gt;();
nameMap.put(&quot;#yr&quot;, &quot;year&quot;);
HashMap&lt;String, Object&gt; valueMap = new HashMap&lt;String, Object&gt;();
valueMap.put(&quot;:yyyy&quot;, 1985);
QuerySpec querySpec = new QuerySpec().withKeyConditionExpression(&quot;#yr
= :yyyy&quot;).withNameMap(nameMap)
.withValueMap(valueMap);
ItemCollection&lt;QueryOutcome&gt; items = null;
Iterator&lt;Item&gt; iterator = null;
Item item = null;
try {
System.out.println(&quot;Movies from 1985&quot;);
items = table.query(querySpec);
iterator = items.iterator();
while (iterator.hasNext()) {
item = iterator.next();
System.out.println(item.getNumber(&quot;year&quot;) + &quot;: &quot; +
item.getString(&quot;title&quot;));
}
}
catch (Exception e) {
System.err.println(&quot;Unable to query movies from 1985&quot;);
System.err.println(e.getMessage());
}
valueMap.put(&quot;:yyyy&quot;, 1992);
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valueMap.put(&quot;:letter1&quot;, &quot;A&quot;);
valueMap.put(&quot;:letter2&quot;, &quot;L&quot;);
querySpec.withProjectionExpression(&quot;#yr, title, info.genres, info.actors[0]&quot;)
.withKeyConditionExpression(&quot;#yr = :yyyy and title between :letter1
and :letter2&quot;).withNameMap(nameMap)
.withValueMap(valueMap);
try {
System.out.println(&quot;Movies from 1992 - titles A-L, with genres and lead
actor&quot;);
items = table.query(querySpec);
iterator = items.iterator();
while (iterator.hasNext()) {
item = iterator.next();
System.out.println(item.getNumber(&quot;year&quot;) + &quot;: &quot; +
item.getString(&quot;title&quot;) + &quot; &quot; + item.getMap(&quot;info&quot;));
}
}
}
}
catch (Exception e) {
System.err.println(&quot;Unable to query movies from 1992:&quot;);
System.err.println(e.getMessage());
}
Note
• nameMap provides name substitution. This is used because year is a reserved
word in DynamoDB—you cannot use it directly in any expression, including
KeyConditionExpression. You use the expression attribute name #yr to address this.
• valueMap provides value substitution. This is used because you can't use literals in any
expression, including KeyConditionExpression. You use the expression attribute value
:yyyy to address this.
2.
First, you create the querySpec object, which describes the query parameters, and then you pass the
object to the query method.
Compile and run the program.
Note
The preceding program shows how to query a table by its primary key attributes. In DynamoDB,
you can optionally create one or more secondary indexes on a table, and query those indexes
in the same way that you query a table. Secondary indexes give your applications additional
ﬂexibility by allowing queries on non-key attributes. For more information, see Improving Data
Access with Secondary Indexes (p. 446).
Step 4.2: Scan
The scan method reads every item in the entire table, and returns all the data in the table. You can
provide an optional filter_expression so that only the items matching your criteria are returned.
However, the ﬁlter is applied only after the entire table has been scanned.
The following program scans the entire Movies table, which contains approximately 5,000 items. The
scan speciﬁes the optional ﬁlter to retrieve only the movies from the 1950s (approximately 100 items),
and discard all the others.
1.
Copy and paste the following program into your Java development environment:
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// Copyright 2012-2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
// Licensed under the Apache License, Version 2.0.
package com.amazonaws.codesamples.gsg;
import java.util.Iterator;
import
import
import
import
import
import
import
import
import
import
import
com.amazonaws.client.builder.AwsClientBuilder;
com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
com.amazonaws.services.dynamodbv2.document.DynamoDB;
com.amazonaws.services.dynamodbv2.document.Item;
com.amazonaws.services.dynamodbv2.document.ItemCollection;
com.amazonaws.services.dynamodbv2.document.ScanOutcome;
com.amazonaws.services.dynamodbv2.document.Table;
com.amazonaws.services.dynamodbv2.document.spec.ScanSpec;
com.amazonaws.services.dynamodbv2.document.utils.NameMap;
com.amazonaws.services.dynamodbv2.document.utils.ValueMap;
public class MoviesScan {
public static void main(String[] args) throws Exception {
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard()
.withEndpointConfiguration(new
AwsClientBuilder.EndpointConfiguration(&quot;http://localhost:8000&quot;, &quot;us-west-2&quot;))
.build();
DynamoDB dynamoDB = new DynamoDB(client);
Table table = dynamoDB.getTable(&quot;Movies&quot;);
ScanSpec scanSpec = new ScanSpec().withProjectionExpression(&quot;#yr, title,
info.rating&quot;)
.withFilterExpression(&quot;#yr between :start_yr and :end_yr&quot;).withNameMap(new
NameMap().with(&quot;#yr&quot;, &quot;year&quot;))
.withValueMap(new ValueMap().withNumber(&quot;:start_yr&quot;,
1950).withNumber(&quot;:end_yr&quot;, 1959));
try {
ItemCollection&lt;ScanOutcome&gt; items = table.scan(scanSpec);
Iterator&lt;Item&gt; iter = items.iterator();
while (iter.hasNext()) {
Item item = iter.next();
System.out.println(item.toString());
}
}
}
}
catch (Exception e) {
System.err.println(&quot;Unable to scan the table:&quot;);
System.err.println(e.getMessage());
}
In the code, note the following:
• ProjectionExpression speciﬁes the attributes you want in the scan result.
• FilterExpression speciﬁes a condition that returns only items that satisfy the condition. All other
items are discarded.
2.
Compile and run the program.
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Step 5: (Optional) Delete the Table
Note
You can also use the Scan operation with any secondary indexes that you created on the table.
For more information, see Improving Data Access with Secondary Indexes (p. 446).
Step 5: (Optional) Delete the Table
To delete the Movies table:
1.
Copy and paste the following program into your Java development environment:
// Copyright 2012-2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
// Licensed under the Apache License, Version 2.0.
package com.amazonaws.codesamples.gsg;
import
import
import
import
import
com.amazonaws.client.builder.AwsClientBuilder;
com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
com.amazonaws.services.dynamodbv2.document.DynamoDB;
com.amazonaws.services.dynamodbv2.document.Table;
public class MoviesDeleteTable {
public static void main(String[] args) throws Exception {
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard()
.withEndpointConfiguration(new
AwsClientBuilder.EndpointConfiguration(&quot;http://localhost:8000&quot;, &quot;us-west-2&quot;))
.build();
DynamoDB dynamoDB = new DynamoDB(client);
Table table = dynamoDB.getTable(&quot;Movies&quot;);
try {
System.out.println(&quot;Attempting to delete table; please wait...&quot;);
table.delete();
table.waitForDelete();
System.out.print(&quot;Success.&quot;);
}
2.
}
}
catch (Exception e) {
System.err.println(&quot;Unable to delete table: &quot;);
System.err.println(e.getMessage());
}
Compile and run the program.
Summary
In this tutorial, you created the Movies table in DynamoDB on your computer and performed basic
operations. The downloadable version of DynamoDB is useful during application development and
testing. However, when you're ready to run your application in a production environment, you must
modify your code so that it uses the Amazon DynamoDB web service.
Modifying the Code to Use the DynamoDB Service
To use the DynamoDB service, you must change the endpoint in your application.
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JavaScript and DynamoDB
1.
Remove the following import:
import com.amazonaws.client.builder.AwsClientBuilder;
2.
Next, go to AmazonDynamoDB in the code:
AmazonDynamoDB client =
AmazonDynamoDBClientBuilder.standard().withEndpointConfiguration(
new AwsClientBuilder.EndpointConfiguration(&quot;http://localhost:8000&quot;, &quot;us-west-2&quot;))
.build();
3.
Now modify the client so that it accesses an AWS region instead of a speciﬁc endpoint:
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard()
.withRegion(Regions.REGION)
.build();
For example, if you want to access the us-west-2 region, you would do this:
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard()
.withRegion(Regions.US_WEST_2)
.build();
Instead of using DynamoDB on your computer, the program now uses the Amazon DynamoDB web
service endpoint in US West (Oregon).
Amazon DynamoDB is available in several regions worldwide. For the complete list, see Regions and
Endpoints in the AWS General Reference. For more information about setting regions and endpoints in
your code, see AWS Region Selection in the AWS SDK for Java Developer Guide.
JavaScript and DynamoDB
In this tutorial, you use JavaScript to write simple programs to perform the following Amazon
DynamoDB operations:
• Create a table called Movies and load sample data in JSON format.
• Perform create, read, update, and delete operations on the table.
• Run simple queries.
You use the downloadable version of DynamoDB in this tutorial. For information about how to run the
same code against the DynamoDB web service, see the Summary (p. 88).
As you work through this tutorial, you can refer to the AWS SDK for JavaScript API Reference.
Prerequisites
• Download and run DynamoDB on your computer. For more information, see Setting Up DynamoDB
Local (Downloadable Version) (p. 41).
• Set up an AWS access key to use AWS SDKs. For more information, see Setting Up DynamoDB (Web
Service) (p. 46).
• Set up the AWS SDK for JavaScript. To do this, add or modify the following script tag to your HTML
pages:
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Step 1: Create a Table
&lt;script src=&quot;https://sdk.amazonaws.com/js/aws-sdk-2.7.16.min.js&quot;&gt;&lt;/script&gt;
Note
The version of AWS SDK for JavaScript might have been updated. For the latest version, see
the AWS SDK for JavaScript API Reference.
• Enable cross-origin resource sharing (CORS) so your computer's browser can communicate with the
downloadable version of DynamoDB.
To enable CORS
1.
Download the free ModHeader Chrome browser extension (or any other browser extension that
allows you to modify HTTP response headers).
2.
Run the ModHeader Chrome browser extension, and add an HTTP response header with the name
set to &quot;Access-Control-Allow-Origin&quot; and a value of &quot;null&quot; or &quot;*&quot;.
Important
3.
This conﬁguration is required only while running this tutorial program for JavaScript
on your computer. After you ﬁnish the tutorial, you should disable or remove this
conﬁguration.
You can now run the JavaScript tutorial program ﬁles.
If you prefer to run a complete version of the JavaScript tutorial program instead of performing step-bystep instructions, do the following:
1.
2.
3.
Download the following ﬁle: MoviesJavaScript.zip.
Extract the ﬁle MoviesJavaScript.html from the archive.
Modify the MoviesJavaScript.html ﬁle to use your endpoint.
4.
Run the MoviesJavaScript.html ﬁle.
Step 1: Create a Table
In this step, you create a table named Movies. The primary key for the table is composed of the following
attributes:
• year – The partition key. The AttributeType is N for number.
• title – The sort key. The AttributeType is S for string.
1.
Copy and paste the following program into a ﬁle named MoviesCreateTable.html:
&lt;html&gt;
&lt;head&gt;
&lt;script src=&quot;https://sdk.amazonaws.com/js/aws-sdk-2.7.16.min.js&quot;&gt;&lt;/script&gt;
&lt;script&gt;
AWS.config.update({
region: &quot;us-west-2&quot;,
endpoint: 'http://localhost:8000',
// accessKeyId default can be used while using the downloadable version of DynamoDB.
// For security reasons, do not store AWS Credentials in your files. Use Amazon
Cognito instead.
accessKeyId: &quot;fakeMyKeyId&quot;,
// secretAccessKey default can be used while using the downloadable version of
DynamoDB.
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// For security reasons, do not store AWS Credentials in your files. Use Amazon
Cognito instead.
secretAccessKey: &quot;fakeSecretAccessKey&quot;
});
var dynamodb = new AWS.DynamoDB();
function createMovies() {
var params = {
TableName : &quot;Movies&quot;,
KeySchema: [
{ AttributeName: &quot;year&quot;, KeyType: &quot;HASH&quot;},
{ AttributeName: &quot;title&quot;, KeyType: &quot;RANGE&quot; }
],
AttributeDefinitions: [
{ AttributeName: &quot;year&quot;, AttributeType: &quot;N&quot; },
{ AttributeName: &quot;title&quot;, AttributeType: &quot;S&quot; }
],
ProvisionedThroughput: {
ReadCapacityUnits: 5,
WriteCapacityUnits: 5
}
};
dynamodb.createTable(params, function(err, data) {
if (err) {
document.getElementById('textarea').innerHTML = &quot;Unable to create table: &quot;
+ &quot;\n&quot; + JSON.stringify(err, undefined, 2);
} else {
document.getElementById('textarea').innerHTML = &quot;Created table: &quot; + &quot;\n&quot; +
JSON.stringify(data, undefined, 2);
}
});
}
&lt;/script&gt;
&lt;/head&gt;
&lt;body&gt;
&lt;input id=&quot;createTableButton&quot; type=&quot;button&quot; value=&quot;Create Table&quot;
onclick=&quot;createMovies();&quot; /&gt;
&lt;br&gt;&lt;br&gt;
&lt;textarea readonly id= &quot;textarea&quot; style=&quot;width:400px; height:800px&quot;&gt;&lt;/textarea&gt;
&lt;/body&gt;
&lt;/html&gt;
Note
• You set the endpoint to indicate that you are creating the table in DynamoDB on your
computer.
• In the createMovies function, you specify the table name, primary key attributes, and its
data types.
• The ProvisionedThroughput parameter is required, but the downloadable version of
DynamoDB ignores it. (Provisioned throughput is beyond the scope of this tutorial.)
2.
Open the MoviesCreateTable.html ﬁle in your browser.
3.
Choose Create Table.
To learn more about managing tables, see Working with Tables in DynamoDB (p. 290).
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Step 2: Load Sample Data
In this step, you populate the Movies table with sample data.
Topics
• Step 2.1: Download the Sample Data File (p. 73)
• Step 2.2: Load the Sample Data into the Movies Table (p. 73)
This scenario uses a sample data ﬁle that contains information about a few thousand movies from the
Internet Movie Database (IMDb). The movie data is in JSON format, as shown in the following example.
For each movie, there is a year, a title, and a JSON map named info.
[
{
},
{
},
&quot;year&quot; : ... ,
&quot;title&quot; : ... ,
&quot;info&quot; : { ... }
&quot;year&quot; : ...,
&quot;title&quot; : ...,
&quot;info&quot; : { ... }
...
]
In the JSON data, note the following:
• The year and title are used as the primary key attribute values for the Movies table.
• The rest of the info values are stored in a single attribute called info. This program illustrates how
you can store JSON in a DynamoDB attribute.
The following is an example of movie data:
{
&quot;year&quot; : 2013,
&quot;title&quot; : &quot;Turn It Down, Or Else!&quot;,
&quot;info&quot; : {
&quot;directors&quot; : [
&quot;Alice Smith&quot;,
&quot;Bob Jones&quot;
],
&quot;release_date&quot; : &quot;2013-01-18T00:00:00Z&quot;,
&quot;rating&quot; : 6.2,
&quot;genres&quot; : [
&quot;Comedy&quot;,
&quot;Drama&quot;
],
&quot;image_url&quot; : &quot;http://ia.media-imdb.com/images/N/
O9ERWAU7FS797AJ7LU8HN09AMUP908RLlo5JF90EWR7LJKQ7@@._V1_SX400_.jpg&quot;,
&quot;plot&quot; : &quot;A rock band plays their music at high volumes, annoying the neighbors.&quot;,
&quot;rank&quot; : 11,
&quot;running_time_secs&quot; : 5215,
&quot;actors&quot; : [
&quot;David Matthewman&quot;,
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}
}
]
&quot;Ann Thomas&quot;,
&quot;Jonathan G. Neff&quot;
Step 2.1: Download the Sample Data File
1.
Download the sample data archive: moviedata.zip
2.
Extract the data ﬁle (moviedata.json) from the archive.
3.
Copy and paste the moviedata.json ﬁle into your current directory.
Step 2.2: Load the Sample Data into the Movies Table
After you download the sample data, you can run the following program to populate the Movies table.
1.
Copy and paste the following program into a ﬁle named MoviesLoadData.html:
&lt;html&gt;
&lt;head&gt;
&lt;script src=&quot;https://sdk.amazonaws.com/js/aws-sdk-2.7.16.min.js&quot;&gt;&lt;/script&gt;
&lt;script type=&quot;text/javascript&quot;&gt;
AWS.config.update({
region: &quot;us-west-2&quot;,
endpoint: 'http://localhost:8000',
// accessKeyId default can be used while using the downloadable version of DynamoDB.
// For security reasons, do not store AWS Credentials in your files. Use Amazon
Cognito instead.
accessKeyId: &quot;fakeMyKeyId&quot;,
// secretAccessKey default can be used while using the downloadable version of
DynamoDB.
// For security reasons, do not store AWS Credentials in your files. Use Amazon
Cognito instead.
secretAccessKey: &quot;fakeSecretAccessKey&quot;
});
var docClient = new AWS.DynamoDB.DocumentClient();
function processFile(evt) {
document.getElementById('textarea').innerHTML = &quot;&quot;;
document.getElementById('textarea').innerHTML += &quot;Importing movies into DynamoDB.
Please wait...&quot; + &quot;\n&quot;;
var file = evt.target.files[0];
if (file) {
var r = new FileReader();
r.onload = function(e) {
var contents = e.target.result;
var allMovies = JSON.parse(contents);
allMovies.forEach(function (movie) {
document.getElementById('textarea').innerHTML += &quot;Processing: &quot; +
movie.title + &quot;\n&quot;;
var params = {
TableName: &quot;Movies&quot;,
Item: {
&quot;year&quot;: movie.year,
&quot;title&quot;: movie.title,
&quot;info&quot;: movie.info
}
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};
docClient.put(params, function (err, data) {
if (err) {
document.getElementById('textarea').innerHTML += &quot;Unable to add
movie: &quot; + count + movie.title + &quot;\n&quot;;
document.getElementById('textarea').innerHTML += &quot;Error JSON: &quot;
+ JSON.stringify(err) + &quot;\n&quot;;
} else {
document.getElementById('textarea').innerHTML += &quot;PutItem
succeeded: &quot; + movie.title + &quot;\n&quot;;
textarea.scrollTop = textarea.scrollHeight;
}
});
});
};
r.readAsText(file);
} else {
alert(&quot;Could not read movie data file&quot;);
}
}
&lt;/script&gt;
&lt;/head&gt;
&lt;body&gt;
&lt;input type=&quot;file&quot; id=&quot;fileinput&quot; accept='application/json'/&gt;
&lt;br&gt;&lt;br&gt;
&lt;textarea readonly id= &quot;textarea&quot; style=&quot;width:400px; height:800px&quot;&gt;&lt;/textarea&gt;
&lt;script&gt;
document.getElementById('fileinput').addEventListener('change', processFile,
false);
&lt;/script&gt;
&lt;/body&gt;
&lt;/html&gt;
2.
Open the MoviesLoadData.html ﬁle in your browser.
3.
Choose Browse, and load the moviedata.json ﬁle.
Step 3: Create, Read, Update, and Delete an Item
In this step, you perform read and write operations on an item in the Movies table.
To learn more about reading and writing data, see Working with Items in DynamoDB (p. 327).
Topics
• Step 3.1: Create a New Item (p. 74)
• Step 3.2: Read an Item (p. 76)
• Step 3.3: Update an Item (p. 77)
• Step 3.4: Increment an Atomic Counter (p. 79)
• Step 3.5: Update an Item (Conditionally) (p. 80)
• Step 3.6: Delete an Item (p. 81)
Step 3.1: Create a New Item
In this step, you add a new item to the Movies table.
1.
Copy and paste the following program into a ﬁle named MoviesItemOps01.html:
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&lt;html&gt;
&lt;head&gt;
&lt;script src=&quot;https://sdk.amazonaws.com/js/aws-sdk-2.7.16.min.js&quot;&gt;&lt;/script&gt;
&lt;script&gt;
AWS.config.update({
region: &quot;us-west-2&quot;,
endpoint: 'http://localhost:8000',
// accessKeyId default can be used while using the downloadable version of DynamoDB.
// For security reasons, do not store AWS Credentials in your files. Use Amazon
Cognito instead.
accessKeyId: &quot;fakeMyKeyId&quot;,
// secretAccessKey default can be used while using the downloadable version of
DynamoDB.
// For security reasons, do not store AWS Credentials in your files. Use Amazon
Cognito instead.
secretAccessKey: &quot;fakeSecretAccessKey&quot;
});
var docClient = new AWS.DynamoDB.DocumentClient();
function createItem() {
var params = {
TableName :&quot;Movies&quot;,
Item:{
&quot;year&quot;: 2015,
&quot;title&quot;: &quot;The Big New Movie&quot;,
&quot;info&quot;:{
&quot;plot&quot;: &quot;Nothing happens at all.&quot;,
&quot;rating&quot;: 0
}
}
};
docClient.put(params, function(err, data) {
if (err) {
document.getElementById('textarea').innerHTML = &quot;Unable to add item: &quot; +
&quot;\n&quot; + JSON.stringify(err, undefined, 2);
} else {
document.getElementById('textarea').innerHTML = &quot;PutItem succeeded: &quot; +
&quot;\n&quot; + JSON.stringify(data, undefined, 2);
}
});
}
&lt;/script&gt;
&lt;/head&gt;
&lt;body&gt;
&lt;input id=&quot;createItem&quot; type=&quot;button&quot; value=&quot;Create Item&quot; onclick=&quot;createItem();&quot; /&gt;
&lt;br&gt;&lt;br&gt;
&lt;textarea readonly id= &quot;textarea&quot; style=&quot;width:400px; height:800px&quot;&gt;&lt;/textarea&gt;
&lt;/body&gt;
&lt;/html&gt;
Note
The primary key is required. This code adds an item that has a primary key (year, title)
and info attributes. The info attribute stores sample JSON that provides more information
about the movie.
2.
Open the MoviesItemOps01.html ﬁle in your browser.
3.
Choose Create Item.
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Step 3.2: Read an Item
In the previous program, you added the following item to the table:
{
}
year: 2015,
title: &quot;The Big New Movie&quot;,
info: {
plot: &quot;Nothing happens at all.&quot;,
rating: 0
}
You can use the get method to read the item from the Movies table. You must specify the primary key
values, so you can read any item from Movies if you know its year and title.
1.
Copy and paste the following program into a ﬁle named MoviesItemOps02.html:
&lt;html&gt;
&lt;head&gt;
&lt;script src=&quot;https://sdk.amazonaws.com/js/aws-sdk-2.7.16.min.js&quot;&gt;&lt;/script&gt;
&lt;script&gt;
AWS.config.update({
region: &quot;us-west-2&quot;,
endpoint: 'http://localhost:8000',
// accessKeyId default can be used while using the downloadable version of DynamoDB.
// For security reasons, do not store AWS Credentials in your files. Use Amazon
Cognito instead.
accessKeyId: &quot;fakeMyKeyId&quot;,
// secretAccessKey default can be used while using the downloadable version of
DynamoDB.
// For security reasons, do not store AWS Credentials in your files. Use Amazon
Cognito instead.
secretAccessKey: &quot;fakeSecretAccessKey&quot;
});
var docClient = new AWS.DynamoDB.DocumentClient();
function readItem() {
var table = &quot;Movies&quot;;
var year = 2015;
var title = &quot;The Big New Movie&quot;;
var params = {
TableName: table,
Key:{
&quot;year&quot;: year,
&quot;title&quot;: title
}
};
docClient.get(params, function(err, data) {
if (err) {
document.getElementById('textarea').innerHTML = &quot;Unable to read item: &quot; +
&quot;\n&quot; + JSON.stringify(err, undefined, 2);
} else {
document.getElementById('textarea').innerHTML = &quot;GetItem succeeded: &quot; +
&quot;\n&quot; + JSON.stringify(data, undefined, 2);
}
});
}
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&lt;/script&gt;
&lt;/head&gt;
&lt;body&gt;
&lt;input id=&quot;readItem&quot; type=&quot;button&quot; value=&quot;Read Item&quot; onclick=&quot;readItem();&quot; /&gt;
&lt;br&gt;&lt;br&gt;
&lt;textarea readonly id= &quot;textarea&quot; style=&quot;width:400px; height:800px&quot;&gt;&lt;/textarea&gt;
&lt;/body&gt;
&lt;/html&gt;
2.
3.
Open the MoviesItemOps02.html ﬁle in your browser.
Choose Read Item.
Step 3.3: Update an Item
You can use the update method to modify an item. You can update values of existing attributes, add new
attributes, or remove attributes.
In this example, you perform the following updates:
• Change the value of the existing attributes (rating, plot).
• Add a new list attribute (actors) to the existing info map.
The item changes from this:
{
}
year: 2015,
title: &quot;The Big New Movie&quot;,
info: {
plot: &quot;Nothing happens at all.&quot;,
rating: 0
}
To the following:
{
}
1.
year: 2015,
title: &quot;The Big New Movie&quot;,
info: {
plot: &quot;Everything happens all at once.&quot;,
rating: 5.5,
actors: [&quot;Larry&quot;, &quot;Moe&quot;, &quot;Curly&quot;]
}
Copy and paste the following program into a ﬁle named MoviesItemOps03.html:
&lt;html&gt;
&lt;head&gt;
&lt;script src=&quot;https://sdk.amazonaws.com/js/aws-sdk-2.7.16.min.js&quot;&gt;&lt;/script&gt;
&lt;script&gt;
AWS.config.update({
region: &quot;us-west-2&quot;,
endpoint: 'http://localhost:8000',
// accessKeyId default can be used while using the downloadable version of DynamoDB.
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// For security reasons, do not store AWS Credentials in your files. Use Amazon
Cognito instead.
accessKeyId: &quot;fakeMyKeyId&quot;,
// secretAccessKey default can be used while using the downloadable version of
DynamoDB.
// For security reasons, do not store AWS Credentials in your files. Use Amazon
Cognito instead.
secretAccessKey: &quot;fakeSecretAccessKey&quot;
});
var docClient = new AWS.DynamoDB.DocumentClient();
function updateItem() {
var table = &quot;Movies&quot;;
var year = 2015;
var title = &quot;The Big New Movie&quot;;
var params = {
TableName:table,
Key:{
&quot;year&quot;: year,
&quot;title&quot;: title
},
UpdateExpression: &quot;set info.rating = :r, info.plot=:p, info.actors=:a&quot;,
ExpressionAttributeValues:{
&quot;:r&quot;:5.5,
&quot;:p&quot;:&quot;Everything happens all at once.&quot;,
&quot;:a&quot;:[&quot;Larry&quot;, &quot;Moe&quot;, &quot;Curly&quot;]
},
ReturnValues:&quot;UPDATED_NEW&quot;
};
docClient.update(params, function(err, data) {
if (err) {
document.getElementById('textarea').innerHTML = &quot;Unable to update item: &quot; +
&quot;\n&quot; + JSON.stringify(err, undefined, 2);
} else {
document.getElementById('textarea').innerHTML = &quot;UpdateItem succeeded: &quot; +
&quot;\n&quot; + JSON.stringify(data, undefined, 2);
}
});
}
&lt;/script&gt;
&lt;/head&gt;
&lt;body&gt;
&lt;input id=&quot;updateItem&quot; type=&quot;button&quot; value=&quot;Update Item&quot; onclick=&quot;updateItem();&quot; /&gt;
&lt;br&gt;&lt;br&gt;
&lt;textarea readonly id= &quot;textarea&quot; style=&quot;width:400px; height:800px&quot;&gt;&lt;/textarea&gt;
&lt;/body&gt;
&lt;/html&gt;
Note
This program uses UpdateExpression to describe all updates you want to perform on the
speciﬁed item.
The ReturnValues parameter instructs DynamoDB to return only the updated attributes
(&quot;UPDATED_NEW&quot;).
2.
Open the MoviesItemOps03.html ﬁle in your browser.
3.
Choose Update Item.
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Step 3.4: Increment an Atomic Counter
DynamoDB supports atomic counters, where you use the update method to increment or decrement the
value of an attribute without interfering with other write requests. (All write requests are applied in the
order in which they are received.)
The following program shows how to increment the rating for a movie. Each time you run it, the
program increments this attribute by one.
1.
Copy and paste the following program into a ﬁle named MoviesItemOps04.html:
&lt;html&gt;
&lt;head&gt;
&lt;script src=&quot;https://sdk.amazonaws.com/js/aws-sdk-2.7.16.min.js&quot;&gt;&lt;/script&gt;
&lt;script&gt;
AWS.config.update({
region: &quot;us-west-2&quot;,
endpoint: 'http://localhost:8000',
// accessKeyId default can be used while using the downloadable version of DynamoDB.
// For security reasons, do not store AWS Credentials in your files. Use Amazon
Cognito instead.
accessKeyId: &quot;fakeMyKeyId&quot;,
// secretAccessKey default can be used while using the downloadable version of
DynamoDB.
// For security reasons, do not store AWS Credentials in your files. Use Amazon
Cognito instead.
secretAccessKey: &quot;fakeSecretAccessKey&quot;
});
var docClient = new AWS.DynamoDB.DocumentClient();
function increaseRating() {
var table = &quot;Movies&quot;;
var year = 2015;
var title = &quot;The Big New Movie&quot;;
var params = {
TableName:table,
Key:{
&quot;year&quot;: year,
&quot;title&quot;: title
},
UpdateExpression: &quot;set info.rating = info.rating + :val&quot;,
ExpressionAttributeValues:{
&quot;:val&quot;:1
},
ReturnValues:&quot;UPDATED_NEW&quot;
};
docClient.update(params, function(err, data) {
if (err) {
document.getElementById('textarea').innerHTML = &quot;Unable to update rating: &quot;
+ &quot;\n&quot; + JSON.stringify(err, undefined, 2);
} else {
document.getElementById('textarea').innerHTML = &quot;Increase Rating succeeded:
&quot; + &quot;\n&quot; + JSON.stringify(data, undefined, 2);
}
});
}
&lt;/script&gt;
&lt;/head&gt;
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&lt;body&gt;
&lt;input id=&quot;increaseRating&quot; type=&quot;button&quot; value=&quot;Increase Rating&quot;
onclick=&quot;increaseRating();&quot; /&gt;
&lt;br&gt;&lt;br&gt;
&lt;textarea readonly id= &quot;textarea&quot; style=&quot;width:400px; height:800px&quot;&gt;&lt;/textarea&gt;
&lt;/body&gt;
&lt;/html&gt;
2.
Open the MoviesItemOps04.html ﬁle in your browser.
3.
Choose Increase Rating.
Step 3.5: Update an Item (Conditionally)
The following program shows how to use UpdateItem with a condition. If the condition evaluates to true,
the update succeeds; otherwise, the update is not performed.
In this case, the item is updated only if there are more than three actors in the movie.
1.
Copy and paste the following program into a ﬁle named MoviesItemOps05.html:
&lt;html&gt;
&lt;head&gt;
&lt;script src=&quot;https://sdk.amazonaws.com/js/aws-sdk-2.7.16.min.js&quot;&gt;&lt;/script&gt;
&lt;script&gt;
AWS.config.update({
region: &quot;us-west-2&quot;,
endpoint: 'http://localhost:8000',
// accessKeyId default can be used while using the downloadable version of DynamoDB.
// For security reasons, do not store AWS Credentials in your files. Use Amazon
Cognito instead.
accessKeyId: &quot;fakeMyKeyId&quot;,
// secretAccessKey default can be used while using the downloadable version of
DynamoDB.
// For security reasons, do not store AWS Credentials in your files. Use Amazon
Cognito instead.
secretAccessKey: &quot;fakeSecretAccessKey&quot;
});
var docClient = new AWS.DynamoDB.DocumentClient();
function conditionalUpdate() {
var table = &quot;Movies&quot;;
var year = 2015;
var title = &quot;The Big New Movie&quot;;
// Conditional update (will fail)
var params = {
TableName:table,
Key:{
&quot;year&quot;: year,
&quot;title&quot;: title
},
UpdateExpression: &quot;remove info.actors[0]&quot;,
ConditionExpression: &quot;size(info.actors) &gt; :num&quot;,
ExpressionAttributeValues:{
&quot;:num&quot;:3
},
ReturnValues:&quot;UPDATED_NEW&quot;
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};
docClient.update(params, function(err, data) {
if (err) {
document.getElementById('textarea').innerHTML = &quot;The conditional update
failed: &quot; + &quot;\n&quot; + JSON.stringify(err, undefined, 2);
} else {
document.getElementById('textarea').innerHTML = &quot;The conditional update
succeeded: &quot; + &quot;\n&quot; + JSON.stringify(data, undefined, 2);
}
});
}
&lt;/script&gt;
&lt;/head&gt;
&lt;body&gt;
&lt;input id=&quot;conditionalUpdate&quot; type=&quot;button&quot; value=&quot;Conditional Update&quot;
onclick=&quot;conditionalUpdate();&quot; /&gt;
&lt;br&gt;&lt;br&gt;
&lt;textarea readonly id= &quot;textarea&quot; style=&quot;width:400px; height:800px&quot;&gt;&lt;/textarea&gt;
&lt;/body&gt;
&lt;/html&gt;
2.
Open the MoviesItemOps05.html ﬁle in your browser.
3.
Choose Conditional Update.
The program should fail with the following message:
The conditional update failed
This is because the movie has three actors in it, but the condition is checking for greater than three
actors.
4.
Modify the program so that the ConditionExpression looks like this:
ConditionExpression: &quot;size(info.actors) &gt;= :num&quot;,
The condition is now greater than or equal to 3 instead of greater than 3.
5.
Run the program again. The updateItem operation should now succeed.
Step 3.6: Delete an Item
You can use the delete method to delete one item by specifying its primary key. You can optionally
provide a ConditionExpression to prevent the item from being deleted if the condition is not met.
In the following example, you try to delete a speciﬁc movie item if its rating is 5 or less.
1.
Copy and paste the following program into a ﬁle named MoviesItemOps06.html:
&lt;html&gt;
&lt;head&gt;
&lt;script src=&quot;https://sdk.amazonaws.com/js/aws-sdk-2.7.16.min.js&quot;&gt;&lt;/script&gt;
&lt;script&gt;
AWS.config.update({
region: &quot;us-west-2&quot;,
endpoint: 'http://localhost:8000',
// accessKeyId default can be used while using the downloadable version of DynamoDB.
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// For security reasons, do not store AWS Credentials in your files. Use Amazon
Cognito instead.
accessKeyId: &quot;fakeMyKeyId&quot;,
// secretAccessKey default can be used while using the downloadable version of
DynamoDB.
// For security reasons, do not store AWS Credentials in your files. Use Amazon
Cognito instead.
secretAccessKey: &quot;fakeSecretAccessKey&quot;
});
var docClient = new AWS.DynamoDB.DocumentClient();
function conditionalDelete() {
var table = &quot;Movies&quot;;
var year = 2015;
var title = &quot;The Big New Movie&quot;;
var params = {
TableName:table,
Key:{
&quot;year&quot;:year,
&quot;title&quot;:title
},
ConditionExpression:&quot;info.rating &lt;= :val&quot;,
ExpressionAttributeValues: {
&quot;:val&quot;: 5.0
}
};
docClient.delete(params, function(err, data) {
if (err) {
document.getElementById('textarea').innerHTML = &quot;The conditional delete
failed: &quot; + &quot;\n&quot; + JSON.stringify(err, undefined, 2);
} else {
document.getElementById('textarea').innerHTML = &quot;The conditional delete
succeeded: &quot; + &quot;\n&quot; + JSON.stringify(data, undefined, 2);
}
});
}
&lt;/script&gt;
&lt;/head&gt;
&lt;body&gt;
&lt;input id=&quot;conditionalDelete&quot; type=&quot;button&quot; value=&quot;Conditional Delete&quot;
onclick=&quot;conditionalDelete();&quot; /&gt;
&lt;br&gt;&lt;br&gt;
&lt;textarea readonly id= &quot;textarea&quot; style=&quot;width:400px; height:800px&quot;&gt;&lt;/textarea&gt;
&lt;/body&gt;
&lt;/html&gt;
2.
Open the MoviesItemOps06.html ﬁle on your browser.
3.
Choose Conditional Delete.
The program should fail with the following message:
The conditional delete failed
This is because the rating for this particular movie is greater than 5.
4.
Modify the program to remove the condition from params.
var params = {
TableName:table,
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};
5.
Key:{
&quot;title&quot;:title,
&quot;year&quot;:year
}
Run the program again. The delete succeeds because you removed the condition.
Step 4: Query and Scan the Data
You can use the query method to retrieve data from a table. You must specify a partition key value; the
sort key is optional.
The primary key for the Movies table is composed of the following:
• year – The partition key. The attribute type is number. • title – The sort key. The attribute type is string.
To ﬁnd all movies released during a year, you need to specify only the year. You can also provide the
title to retrieve a subset of movies based on some condition (on the sort key); for example, to ﬁnd
movies released in 2014 that have a title starting with the letter &quot;A&quot;.
In addition to query, there is also a scan method that can retrieve all the table data.
To learn more about querying and scanning data, see Working with Queries (p. 410) and Working with
Scans (p. 427), respectively.
Topics
• Step 4.1: Query - All Movies Released in a Year (p. 83)
• Step 4.2: Query - All Movies Released in a Year with Certain Titles (p. 85)
• Step 4.3: Scan (p. 86)
Step 4.1: Query - All Movies Released in a Year
The program included in this step retrieves all movies released in the year 1985.
1.
Copy and paste the following program into a ﬁle named MoviesQuery01.html:
&lt;html&gt;
&lt;head&gt;
&lt;script src=&quot;https://sdk.amazonaws.com/js/aws-sdk-2.7.16.min.js&quot;&gt;&lt;/script&gt;
&lt;script&gt;
AWS.config.update({
region: &quot;us-west-2&quot;,
endpoint: 'http://localhost:8000',
// accessKeyId default can be used while using the downloadable version of DynamoDB.
// For security reasons, do not store AWS Credentials in your files. Use Amazon
Cognito instead.
accessKeyId: &quot;fakeMyKeyId&quot;,
// secretAccessKey default can be used while using the downloadable version of
DynamoDB.
// For security reasons, do not store AWS Credentials in your files. Use Amazon
Cognito instead.
secretAccessKey: &quot;fakeSecretAccessKey&quot;
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});
var docClient = new AWS.DynamoDB.DocumentClient();
function queryData() {
document.getElementById('textarea').innerHTML += &quot;Querying for movies from 1985.&quot;;
var params = {
TableName : &quot;Movies&quot;,
KeyConditionExpression: &quot;#yr = :yyyy&quot;,
ExpressionAttributeNames:{
&quot;#yr&quot;: &quot;year&quot;
},
ExpressionAttributeValues: {
&quot;:yyyy&quot;:1985
}
};
docClient.query(params, function(err, data) {
if (err) {
document.getElementById('textarea').innerHTML += &quot;Unable to query. Error: &quot;
+ &quot;\n&quot; + JSON.stringify(err, undefined, 2);
} else {
document.getElementById('textarea').innerHTML += &quot;Querying for movies from
1985: &quot; + &quot;\n&quot; + JSON.stringify(data, undefined, 2);
}
});
}
&lt;/script&gt;
&lt;/head&gt;
&lt;body&gt;
&lt;input id=&quot;queryData&quot; type=&quot;button&quot; value=&quot;Query&quot; onclick=&quot;queryData();&quot; /&gt;
&lt;br&gt;&lt;br&gt;
&lt;textarea readonly id= &quot;textarea&quot; style=&quot;width:400px; height:800px&quot;&gt;&lt;/textarea&gt;
&lt;/body&gt;
&lt;/html&gt;
Note
ExpressionAttributeNames provides name substitution. This is used because year is
a reserved word in DynamoDB—you can't use it directly in any expression, including
KeyConditionExpression. For this reason, you use the expression attribute name #yr.
ExpressionAttributeValues provides value substitution. This is used because you can't use
literals in any expression, including KeyConditionExpression. For this reason, you use the
expression attribute value :yyyy.
2.
Open the MoviesQuery01.html ﬁle in your browser.
3.
Choose Query.
Note
The preceding program shows how to query a table by its primary key attributes. In DynamoDB,
you can optionally create one or more secondary indexes on a table, and query those indexes
in the same way that you query a table. Secondary indexes give your applications additional
ﬂexibility by allowing queries on non-key attributes. For more information, see Improving Data
Access with Secondary Indexes (p. 446).
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Step 4.2: Query - All Movies Released in a Year with Certain
Titles
The program included in this step retrieves all movies released in year 1992, with title beginning with
the letter &quot;A&quot; through the letter &quot;L&quot;.
1.
Copy and paste the following program into a ﬁle named MoviesQuery02.html:
&lt;html&gt;
&lt;head&gt;
&lt;script src=&quot;https://sdk.amazonaws.com/js/aws-sdk-2.7.16.min.js&quot;&gt;&lt;/script&gt;
&lt;script&gt;
AWS.config.update({
region: &quot;us-west-2&quot;,
endpoint: 'http://localhost:8000',
// accessKeyId default can be used while using the downloadable version of DynamoDB.
// For security reasons, do not store AWS Credentials in your files. Use Amazon
Cognito instead.
accessKeyId: &quot;fakeMyKeyId&quot;,
// secretAccessKey default can be used while using the downloadable version of
DynamoDB.
// For security reasons, do not store AWS Credentials in your files. Use Amazon
Cognito instead.
secretAccessKey: &quot;fakeSecretAccessKey&quot;
});
var docClient = new AWS.DynamoDB.DocumentClient();
function queryData() {
document.getElementById('textarea').innerHTML += &quot;Querying for movies from 1985.&quot;;
var params = {
TableName : &quot;Movies&quot;,
ProjectionExpression:&quot;#yr, title, info.genres, info.actors[0]&quot;,
KeyConditionExpression: &quot;#yr = :yyyy and title between :letter1 and :letter2&quot;,
ExpressionAttributeNames:{
&quot;#yr&quot;: &quot;year&quot;
},
ExpressionAttributeValues: {
&quot;:yyyy&quot;:1992,
&quot;:letter1&quot;: &quot;A&quot;,
&quot;:letter2&quot;: &quot;L&quot;
}
};
docClient.query(params, function(err, data) {
if (err) {
document.getElementById('textarea').innerHTML += &quot;Unable to query. Error: &quot;
+ &quot;\n&quot; + JSON.stringify(err, undefined, 2);
} else {
document.getElementById('textarea').innerHTML += &quot;Querying for movies
from 1992 - titles A-L, with genres and lead actor: &quot; + &quot;\n&quot; + JSON.stringify(data,
undefined, 2);
}
});
}
&lt;/script&gt;
&lt;/head&gt;
&lt;body&gt;
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&lt;input id=&quot;queryData&quot; type=&quot;button&quot; value=&quot;Query&quot; onclick=&quot;queryData();&quot; /&gt;
&lt;br&gt;&lt;br&gt;
&lt;textarea readonly id= &quot;textarea&quot; style=&quot;width:400px; height:800px&quot;&gt;&lt;/textarea&gt;
&lt;/body&gt;
&lt;/html&gt;
2.
Open the MoviesQuery02.html ﬁle on your browser.
3.
Choose Query.
Step 4.3: Scan
The scan method reads every item in the entire table, and returns all the data in the table. You can
provide an optional filter_expression, so that only the items matching your criteria are returned.
However, the ﬁlter is applied only after the entire table has been scanned.
The following program scans the entire Movies table, which contains approximately 5,000 items. The
scan speciﬁes the optional ﬁlter to retrieve only the movies from the 1950s (approximately 100 items),
and discard all the others.
1.
Copy and paste the following program into a ﬁle named MoviesScan.html:
&lt;html&gt;
&lt;head&gt;
&lt;script src=&quot;https://sdk.amazonaws.com/js/aws-sdk-2.7.16.min.js&quot;&gt;&lt;/script&gt;
&lt;script&gt;
AWS.config.update({
region: &quot;us-west-2&quot;,
endpoint: 'http://localhost:8000',
// accessKeyId default can be used while using the downloadable version of DynamoDB.
// For security reasons, do not store AWS Credentials in your files. Use Amazon
Cognito instead.
accessKeyId: &quot;fakeMyKeyId&quot;,
// secretAccessKey default can be used while using the downloadable version of
DynamoDB.
// For security reasons, do not store AWS Credentials in your files. Use Amazon
Cognito instead.
secretAccessKey: &quot;fakeSecretAccessKey&quot;
});
var docClient = new AWS.DynamoDB.DocumentClient();
function scanData() {
document.getElementById('textarea').innerHTML += &quot;Scanning Movies table.&quot; + &quot;\n&quot;;
var params = {
TableName: &quot;Movies&quot;,
ProjectionExpression: &quot;#yr, title, info.rating&quot;,
FilterExpression: &quot;#yr between :start_yr and :end_yr&quot;,
ExpressionAttributeNames: {
&quot;#yr&quot;: &quot;year&quot;,
},
ExpressionAttributeValues: {
&quot;:start_yr&quot;: 1950,
&quot;:end_yr&quot;: 1959
}
};
docClient.scan(params, onScan);
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function onScan(err, data) {
if (err) {
document.getElementById('textarea').innerHTML += &quot;Unable to scan the table:
&quot; + &quot;\n&quot; + JSON.stringify(err, undefined, 2);
} else {
// Print all the movies
document.getElementById('textarea').innerHTML += &quot;Scan succeeded. &quot; +
&quot;\n&quot;;
data.Items.forEach(function(movie) {
document.getElementById('textarea').innerHTML += movie.year + &quot;: &quot; +
movie.title + &quot; - rating: &quot; + movie.info.rating + &quot;\n&quot;;
});
// Continue scanning if we have more movies (per scan 1MB limitation)
document.getElementById('textarea').innerHTML += &quot;Scanning for more...&quot; +
&quot;\n&quot;;
}
}
}
params.ExclusiveStartKey = data.LastEvaluatedKey;
docClient.scan(params, onScan);
&lt;/script&gt;
&lt;/head&gt;
&lt;body&gt;
&lt;input id=&quot;scanData&quot; type=&quot;button&quot; value=&quot;Scan&quot; onclick=&quot;scanData();&quot; /&gt;
&lt;br&gt;&lt;br&gt;
&lt;textarea readonly id= &quot;textarea&quot; style=&quot;width:400px; height:800px&quot;&gt;&lt;/textarea&gt;
&lt;/body&gt;
&lt;/html&gt;
In the code, note the following:
• ProjectionExpression speciﬁes the attributes you want in the scan result.
• FilterExpression speciﬁes a condition that returns only items that satisfy the condition. All other
items are discarded.
2.
Open the MoviesScan.html ﬁle in your browser.
3.
Choose Scan.
Note
You can also use the Scan operation with any secondary indexes that you create on the table.
For more information, see Improving Data Access with Secondary Indexes (p. 446).
Step 5: (Optional): Delete the Table
To delete the Movies table:
1.
Copy and paste the following program into a ﬁle named MoviesDeleteTable.html:
&lt;html&gt;
&lt;head&gt;
&lt;script src=&quot;https://sdk.amazonaws.com/js/aws-sdk-2.7.16.min.js&quot;&gt;&lt;/script&gt;
&lt;script&gt;
AWS.config.update({
region: &quot;us-west-2&quot;,
endpoint: 'http://localhost:8000',
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Summary
// accessKeyId default can be used while using the downloadable version of DynamoDB.
// For security reasons, do not store AWS Credentials in your files. Use Amazon
Cognito instead.
accessKeyId: &quot;fakeMyKeyId&quot;,
// secretAccessKey default can be used while using the downloadable version of
DynamoDB.
// For security reasons, do not store AWS Credentials in your files. Use Amazon
Cognito instead.
secretAccessKey: &quot;fakeSecretAccessKey&quot;
});
var dynamodb = new AWS.DynamoDB();
function deleteMovies() {
var params = {
TableName : &quot;Movies&quot;
};
dynamodb.deleteTable(params, function(err, data) {
if (err) {
document.getElementById('textarea').innerHTML = &quot;Unable to delete table: &quot;
+ &quot;\n&quot; + JSON.stringify(err, undefined, 2);
} else {
document.getElementById('textarea').innerHTML = &quot;Table deleted.&quot;;
}
});
}
&lt;/script&gt;
&lt;/head&gt;
&lt;body&gt;
&lt;input id=&quot;deleteTableButton&quot; type=&quot;button&quot; value=&quot;Delete Table&quot;
onclick=&quot;deleteMovies();&quot; /&gt;
&lt;br&gt;&lt;br&gt;
&lt;textarea readonly id= &quot;textarea&quot; style=&quot;width:400px; height:800px&quot;&gt;&lt;/textarea&gt;
&lt;/body&gt;
&lt;/html&gt;
2.
Open the MoviesDeleteTable.html ﬁle in your browser.
3.
Choose Delete Table.
Summary
In this tutorial, you created the Movies table in DynamoDB on your computer and performed basic
operations. The downloadable version of DynamoDB is useful during application development and
testing. However, when you're ready to run your application in a production environment, you must
modify your code so that it uses the Amazon DynamoDB web service.
Updating the AWS Conﬁguration Region to Use the DynamoDB
Web Service
To use the DynamoDB web service, you must update the Region in your application. You also have
to make sure that Amazon Cognito is available in that same Region so that your browser scripts can
authenticate successfully.
AWS.config.update({region: &quot;aws-region&quot;});
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For example, if you want to use the us-west-2 region, set the following region:
AWS.config.update({region: &quot;us-west-2&quot;});
The program now uses the Amazon DynamoDB web service region in US West (Oregon).
DynamoDB is available in several regions worldwide. For the complete list, see Regions and Endpoints in
the AWS General Reference. For more information about setting regions and endpoints in your code, see
Setting the Region in the AWS SDK for JavaScript Getting Started Guide.
Conﬁguring AWS Credentials in Your Files Using Amazon
Cognito
The recommended way to obtain AWS credentials for your web and mobile applications is to use Amazon
Cognito. Amazon Cognito helps you avoid hardcoding your AWS credentials on your ﬁles. Amazon
Cognito uses AWS Identity and Access Management (IAM) roles to generate temporary credentials for
your application's authenticated and unauthenticated users.
For more information, see Conﬁgure AWS Credentials in Your Files Using Amazon Cognito (p. 686).
Node.js and DynamoDB
In this tutorial, you use the AWS SDK for JavaScript to write simple programs to perform the following
Amazon DynamoDB operations:
• Create a table called Movies and load sample data in JSON format.
• Perform create, read, update, and delete operations on the table.
• Run simple queries.
You use the downloadable version of DynamoDB in this tutorial. For information about how to run the
same code against the DynamoDB web service, see the Summary (p. 103).
As you work through this tutorial, you can refer to the AWS SDK for JavaScript API Reference.
Prerequisites
• Download and run DynamoDB on your computer. For more information, see Setting Up DynamoDB
Local (Downloadable Version) (p. 41).
• Set up an AWS access key to use the AWS SDKs. For more information, see Setting Up DynamoDB (Web
Service) (p. 46).
• Set up the AWS SDK for JavaScript:
• Go to http://nodejs.org and install Node.js.
• Go to https://aws.amazon.com/sdk-for-node-js and install the AWS SDK for JavaScript.
For more information, see the AWS SDK for JavaScript Getting Started Guide.
Step 1: Create a Table
In this step, you create a table named Movies. The primary key for the table is composed of the following
attributes:
• year – The partition key. The AttributeType is N for number.
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Step 2: Load Sample Data
• title – The sort key. The AttributeType is S for string.
1.
Copy and paste the following program into a ﬁle named MoviesCreateTable.js.
var AWS = require(&quot;aws-sdk&quot;);
AWS.config.update({
region: &quot;us-west-2&quot;,
endpoint: &quot;http://localhost:8000&quot;
});
var dynamodb = new AWS.DynamoDB();
var params = {
TableName : &quot;Movies&quot;,
KeySchema: [
{ AttributeName: &quot;year&quot;, KeyType: &quot;HASH&quot;}, //Partition key
{ AttributeName: &quot;title&quot;, KeyType: &quot;RANGE&quot; } //Sort key
],
AttributeDefinitions: [
{ AttributeName: &quot;year&quot;, AttributeType: &quot;N&quot; },
{ AttributeName: &quot;title&quot;, AttributeType: &quot;S&quot; }
],
ProvisionedThroughput: {
ReadCapacityUnits: 10,
WriteCapacityUnits: 10
}
};
dynamodb.createTable(params, function(err, data) {
if (err) {
console.error(&quot;Unable to create table. Error JSON:&quot;, JSON.stringify(err, null,
2));
} else {
console.log(&quot;Created table. Table description JSON:&quot;, JSON.stringify(data,
null, 2));
}
});
Note
• You set the endpoint to indicate that you are creating the table in DynamoDB on your
computer.
• In the createTable call, you specify table name, primary key attributes, and its data
types.
• The ProvisionedThroughput parameter is required, but the downloadable version of
DynamoDB ignores it. (Provisioned throughput is beyond the scope of this exercise.)
2.
To run the program, type the following command:
node MoviesCreateTable.js
To learn more about managing tables, see Working with Tables in DynamoDB (p. 290).
Step 2: Load Sample Data
In this step, you populate the Movies table with sample data.
Topics
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Step 2: Load Sample Data
• Step 2.1: Download the Sample Data File (p. 92)
• Step 2.2: Load the Sample Data into the Movies Table (p. 92)
We use a sample data ﬁle that contains information about a few thousand movies from the Internet
Movie Database (IMDb). The movie data is in JSON format, as shown in the following example. For each
movie, there is a year, a title, and a JSON map named info.
[
{
},
{
},
&quot;year&quot; : ... ,
&quot;title&quot; : ... ,
&quot;info&quot; : { ... }
&quot;year&quot; : ...,
&quot;title&quot; : ...,
&quot;info&quot; : { ... }
...
]
In the JSON data, note the following:
• The year and title are used as the primary key attribute values for the Movies table.
• The rest of the info values are stored in a single attribute called info. This program illustrates how
you can store JSON in a DynamoDB attribute.
The following is an example of movie data:
{
&quot;year&quot; : 2013,
&quot;title&quot; : &quot;Turn It Down, Or Else!&quot;,
&quot;info&quot; : {
&quot;directors&quot; : [
&quot;Alice Smith&quot;,
&quot;Bob Jones&quot;
],
&quot;release_date&quot; : &quot;2013-01-18T00:00:00Z&quot;,
&quot;rating&quot; : 6.2,
&quot;genres&quot; : [
&quot;Comedy&quot;,
&quot;Drama&quot;
],
&quot;image_url&quot; : &quot;http://ia.media-imdb.com/images/N/
O9ERWAU7FS797AJ7LU8HN09AMUP908RLlo5JF90EWR7LJKQ7@@._V1_SX400_.jpg&quot;,
&quot;plot&quot; : &quot;A rock band plays their music at high volumes, annoying the neighbors.&quot;,
&quot;rank&quot; : 11,
&quot;running_time_secs&quot; : 5215,
&quot;actors&quot; : [
&quot;David Matthewman&quot;,
&quot;Ann Thomas&quot;,
&quot;Jonathan G. Neff&quot;
]
}
}
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Step 3: Create, Read, Update, and Delete an Item
Step 2.1: Download the Sample Data File
1.
Download the sample data archive: moviedata.zip
2.
Extract the data ﬁle (moviedata.json) from the archive.
3.
Copy and paste the moviedata.json ﬁle into your current directory.
Step 2.2: Load the Sample Data into the Movies Table
After you download the sample data, you can run the following program to populate the Movies table.
1.
Copy and paste the following program into a ﬁle named MoviesLoadData.js:
var AWS = require(&quot;aws-sdk&quot;);
var fs = require('fs');
AWS.config.update({
region: &quot;us-west-2&quot;,
endpoint: &quot;http://localhost:8000&quot;
});
var docClient = new AWS.DynamoDB.DocumentClient();
console.log(&quot;Importing movies into DynamoDB. Please wait.&quot;);
var allMovies = JSON.parse(fs.readFileSync('moviedata.json', 'utf8'));
allMovies.forEach(function(movie) {
var params = {
TableName: &quot;Movies&quot;,
Item: {
&quot;year&quot;: movie.year,
&quot;title&quot;: movie.title,
&quot;info&quot;: movie.info
}
};
docClient.put(params, function(err, data) {
if (err) {
console.error(&quot;Unable to add movie&quot;, movie.title, &quot;. Error JSON:&quot;,
JSON.stringify(err, null, 2));
} else {
console.log(&quot;PutItem succeeded:&quot;, movie.title);
}
});
});
2.
To run the program, type the following command:
node MoviesLoadData.js
Step 3: Create, Read, Update, and Delete an Item
In this step, you perform read and write operations on an item in the Movies table.
To learn more about reading and writing data, see Working with Items in DynamoDB (p. 327).
Topics
• Step 3.1: Create a New Item (p. 93)
• Step 3.2: Read an Item (p. 93)
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Step 3: Create, Read, Update, and Delete an Item
• Step 3.3: Update an Item (p. 94)
• Step 3.4: Increment an Atomic Counter (p. 96)
• Step 3.5: Update an Item (Conditionally) (p. 97)
• Step 3.6: Delete an Item (p. 98)
Step 3.1: Create a New Item
In this step, you add a new item to the Movies table.
1.
Copy and paste the following program into a ﬁle named MoviesItemOps01.js:
var AWS = require(&quot;aws-sdk&quot;);
AWS.config.update({
region: &quot;us-west-2&quot;,
endpoint: &quot;http://localhost:8000&quot;
});
var docClient = new AWS.DynamoDB.DocumentClient();
var table = &quot;Movies&quot;;
var year = 2015;
var title = &quot;The Big New Movie&quot;;
var params = {
TableName:table,
Item:{
&quot;year&quot;: year,
&quot;title&quot;: title,
&quot;info&quot;:{
&quot;plot&quot;: &quot;Nothing happens at all.&quot;,
&quot;rating&quot;: 0
}
}
};
console.log(&quot;Adding a new item...&quot;);
docClient.put(params, function(err, data) {
if (err) {
console.error(&quot;Unable to add item. Error JSON:&quot;, JSON.stringify(err, null, 2));
} else {
console.log(&quot;Added item:&quot;, JSON.stringify(data, null, 2));
}
});
Note
The primary key is required. This code adds an item that has a primary key (year, title)
and info attributes. The info attribute stores sample JSON that provides more information
about the movie.
2.
To run the program, type the following command:
node MoviesItemOps01.js
Step 3.2: Read an Item
In the previous program, you added the following item to the table:
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{
}
year: 2015,
title: &quot;The Big New Movie&quot;,
info: {
plot: &quot;Nothing happens at all.&quot;,
rating: 0
}
You can use the get method to read the item from the Movies table. You must specify the primary key
values, so you can read any item from Movies if you know its year and title.
1.
Copy and paste the following program into a ﬁle named MoviesItemOps02.js:
var AWS = require(&quot;aws-sdk&quot;);
AWS.config.update({
region: &quot;us-west-2&quot;,
endpoint: &quot;http://localhost:8000&quot;
});
var docClient = new AWS.DynamoDB.DocumentClient()
var table = &quot;Movies&quot;;
var year = 2015;
var title = &quot;The Big New Movie&quot;;
var params = {
TableName: table,
Key:{
&quot;year&quot;: year,
&quot;title&quot;: title
}
};
docClient.get(params, function(err, data) {
if (err) {
console.error(&quot;Unable to read item. Error JSON:&quot;, JSON.stringify(err, null,
2));
} else {
console.log(&quot;GetItem succeeded:&quot;, JSON.stringify(data, null, 2));
}
});
2.
To run the program, type the following command:
node MoviesItemOps02.js
Step 3.3: Update an Item
You can use the update method to modify an existing item. You can update values of existing attributes,
add new attributes, or remove attributes.
In this example, you perform the following updates:
• Change the value of the existing attributes (rating, plot).
• Add a new list attribute (actors) to the existing info map.
The item changes from this:
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{
}
year: 2015,
title: &quot;The Big New Movie&quot;,
info: {
plot: &quot;Nothing happens at all.&quot;,
rating: 0
}
To the following:
{
}
1.
year: 2015,
title: &quot;The Big New Movie&quot;,
info: {
plot: &quot;Everything happens all at once.&quot;,
rating: 5.5,
actors: [&quot;Larry&quot;, &quot;Moe&quot;, &quot;Curly&quot;]
}
Copy and paste the following program into a ﬁle named MoviesItemOps03.js:
var AWS = require(&quot;aws-sdk&quot;);
AWS.config.update({
region: &quot;us-west-2&quot;,
endpoint: &quot;http://localhost:8000&quot;
});
var docClient = new AWS.DynamoDB.DocumentClient()
var table = &quot;Movies&quot;;
var year = 2015;
var title = &quot;The Big New Movie&quot;;
// Update the item, unconditionally,
var params = {
TableName:table,
Key:{
&quot;year&quot;: year,
&quot;title&quot;: title
},
UpdateExpression: &quot;set info.rating = :r, info.plot=:p, info.actors=:a&quot;,
ExpressionAttributeValues:{
&quot;:r&quot;:5.5,
&quot;:p&quot;:&quot;Everything happens all at once.&quot;,
&quot;:a&quot;:[&quot;Larry&quot;, &quot;Moe&quot;, &quot;Curly&quot;]
},
ReturnValues:&quot;UPDATED_NEW&quot;
};
console.log(&quot;Updating the item...&quot;);
docClient.update(params, function(err, data) {
if (err) {
console.error(&quot;Unable to update item. Error JSON:&quot;, JSON.stringify(err, null,
2));
} else {
console.log(&quot;UpdateItem succeeded:&quot;, JSON.stringify(data, null, 2));
}
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});
Note
This program uses UpdateExpression to describe all updates you want to perform on the
speciﬁed item.
The ReturnValues parameter instructs DynamoDB to return only the updated attributes
(&quot;UPDATED_NEW&quot;).
2.
To run the program, type the following command:
node MoviesItemOps03.js
Step 3.4: Increment an Atomic Counter
DynamoDB supports atomic counters, where you use the update method to increment or decrement
the value of an existing attribute without interfering with other write requests. (All write requests are
applied in the order in which they are received.)
The following program shows how to increment the rating for a movie. Each time you run it, the
program increments this attribute by one.
1.
Copy and paste the following program into a ﬁle named MoviesItemOps04.js:
var AWS = require(&quot;aws-sdk&quot;);
AWS.config.update({
region: &quot;us-west-2&quot;,
endpoint: &quot;http://localhost:8000&quot;
});
var docClient = new AWS.DynamoDB.DocumentClient()
var table = &quot;Movies&quot;;
var year = 2015;
var title = &quot;The Big New Movie&quot;;
// Increment an atomic counter
var params = {
TableName:table,
Key:{
&quot;year&quot;: year,
&quot;title&quot;: title
},
UpdateExpression: &quot;set info.rating = info.rating + :val&quot;,
ExpressionAttributeValues:{
&quot;:val&quot;:1
},
ReturnValues:&quot;UPDATED_NEW&quot;
};
console.log(&quot;Updating the item...&quot;);
docClient.update(params, function(err, data) {
if (err) {
console.error(&quot;Unable to update item. Error JSON:&quot;, JSON.stringify(err, null,
2));
} else {
console.log(&quot;UpdateItem succeeded:&quot;, JSON.stringify(data, null, 2));
}
});
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2.
To run the program, type the following command:
node MoviesItemOps04.js
Step 3.5: Update an Item (Conditionally)
The following program shows how to use UpdateItem with a condition. If the condition evaluates to true,
the update succeeds; otherwise, the update is not performed.
In this case, the item is updated only if there are more than three actors in the movie.
1.
Copy and paste the following program into a ﬁle named MoviesItemOps05.js:
var AWS = require(&quot;aws-sdk&quot;);
AWS.config.update({
region: &quot;us-west-2&quot;,
endpoint: &quot;http://localhost:8000&quot;
});
var docClient = new AWS.DynamoDB.DocumentClient()
var table = &quot;Movies&quot;;
var year = 2015;
var title = &quot;The Big New Movie&quot;;
// Conditional update (will fail)
var params = {
TableName:table,
Key:{
&quot;year&quot;: year,
&quot;title&quot;: title
},
UpdateExpression: &quot;remove info.actors[0]&quot;,
ConditionExpression: &quot;size(info.actors) &gt; :num&quot;,
ExpressionAttributeValues:{
&quot;:num&quot;:3
},
ReturnValues:&quot;UPDATED_NEW&quot;
};
console.log(&quot;Attempting a conditional update...&quot;);
docClient.update(params, function(err, data) {
if (err) {
console.error(&quot;Unable to update item. Error JSON:&quot;, JSON.stringify(err, null,
2));
} else {
console.log(&quot;UpdateItem succeeded:&quot;, JSON.stringify(data, null, 2));
}
});
2.
To run the program, type the following command:
node MoviesItemOps05.js
The program should fail with the following message:
The conditional request failed
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This is because the movie has three actors in it, but the condition is checking for greater than three
actors.
3.
Modify the program so that the ConditionExpression looks like this:
ConditionExpression: &quot;size(info.actors) &gt;= :num&quot;,
The condition is now greater than or equal to 3 instead of greater than 3.
4.
Run the program again. The updateItem operation should now succeed.
Step 3.6: Delete an Item
You can use the delete method to delete one item by specifying its primary key. You can optionally
provide a ConditionExpression to prevent the item from being deleted if the condition is not met.
In the following example, you try to delete a speciﬁc movie item if its rating is 5 or less.
1.
Copy and paste the following program into a ﬁle named MoviesItemOps06.js:
var AWS = require(&quot;aws-sdk&quot;);
AWS.config.update({
region: &quot;us-west-2&quot;,
endpoint: &quot;http://localhost:8000&quot;
});
var docClient = new AWS.DynamoDB.DocumentClient();
var table = &quot;Movies&quot;;
var year = 2015;
var title = &quot;The Big New Movie&quot;;
var params = {
TableName:table,
Key:{
&quot;year&quot;:year,
&quot;title&quot;:title
},
ConditionExpression:&quot;info.rating &lt;= :val&quot;,
ExpressionAttributeValues: {
&quot;:val&quot;: 5.0
}
};
console.log(&quot;Attempting a conditional delete...&quot;);
docClient.delete(params, function(err, data) {
if (err) {
console.error(&quot;Unable to delete item. Error JSON:&quot;, JSON.stringify(err, null,
2));
} else {
console.log(&quot;DeleteItem succeeded:&quot;, JSON.stringify(data, null, 2));
}
});
2.
To run the program, type the following command:
node MoviesItemOps06.js
The program should fail with the following message:
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The conditional request failed
This is because the rating for this particular movie is greater than 5.
3.
Modify the program to remove the condition from params.
var params = {
TableName:table,
Key:{
&quot;title&quot;:title,
&quot;year&quot;:year
}
};
4.
Run the program again. Now, the delete succeeds because you removed the condition.
Step 4: Query and Scan the Data
You can use the query method to retrieve data from a table. You must specify a partition key value; the
sort key is optional.
The primary key for the Movies table is composed of the following:
• year – The partition key. The attribute type is number. • title – The sort key. The attribute type is string.
To ﬁnd all movies released during a year, you need to specify only the year. You can also provide the
title to retrieve a subset of movies based on some condition (on the sort key); for example, to ﬁnd
movies released in 2014 that have a title starting with the letter &quot;A&quot;.
In addition to query, there is also a scan method that can retrieve all the table data.
To learn more about querying and scanning data, see Working with Queries (p. 410) and Working with
Scans (p. 427), respectively.
Topics
• Step 4.1: Query - All Movies Released in a Year (p. 99)
• Step 4.2: Query - All Movies Released in a Year with Certain Titles (p. 100)
• Step 4.3: Scan (p. 101)
Step 4.1: Query - All Movies Released in a Year
The program included in this step retrieves all movies released in the year 1985.
1.
Copy and paste the following program into a ﬁle named MoviesQuery01.js:
var AWS = require(&quot;aws-sdk&quot;);
AWS.config.update({
region: &quot;us-west-2&quot;,
endpoint: &quot;http://localhost:8000&quot;
});
var docClient = new AWS.DynamoDB.DocumentClient();
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console.log(&quot;Querying for movies from 1985.&quot;);
var params = {
TableName : &quot;Movies&quot;,
KeyConditionExpression: &quot;#yr = :yyyy&quot;,
ExpressionAttributeNames:{
&quot;#yr&quot;: &quot;year&quot;
},
ExpressionAttributeValues: {
&quot;:yyyy&quot;:1985
}
};
docClient.query(params, function(err, data) {
if (err) {
console.error(&quot;Unable to query. Error:&quot;, JSON.stringify(err, null, 2));
} else {
console.log(&quot;Query succeeded.&quot;);
data.Items.forEach(function(item) {
console.log(&quot; -&quot;, item.year + &quot;: &quot; + item.title);
});
}
});
Note
ExpressionAttributeNames provides name substitution. We use this because year is a
reserved word in DynamoDB—you cannot use it directly in any expression, including
KeyConditionExpression. We use the expression attribute name #yr to address this.
ExpressionAttributeValues provides value substitution. We use this because you cannot
use literals in any expression, including KeyConditionExpression. We use the expression
attribute value :yyyy to address this.
2.
To run the program, type the following command:
node MoviesQuery01.js
Note
The preceding program shows how to query a table by its primary key attributes. In DynamoDB,
you can optionally create one or more secondary indexes on a table, and query those indexes
in the same way that you query a table. Secondary indexes give your applications additional
ﬂexibility by allowing queries on non-key attributes. For more information, see Improving Data
Access with Secondary Indexes (p. 446).
Step 4.2: Query - All Movies Released in a Year with Certain
Titles
The program included in this step retrieves all movies released in year 1992, with title beginning with
the letter &quot;A&quot; through the letter &quot;L&quot;.
1.
Copy and paste the following program into a ﬁle named MoviesQuery02.js:
var AWS = require(&quot;aws-sdk&quot;);
AWS.config.update({
region: &quot;us-west-2&quot;,
endpoint: &quot;http://localhost:8000&quot;
});
var docClient = new AWS.DynamoDB.DocumentClient();
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console.log(&quot;Querying for movies from 1992 - titles A-L, with genres and lead actor&quot;);
var params = {
TableName : &quot;Movies&quot;,
ProjectionExpression:&quot;#yr, title, info.genres, info.actors[0]&quot;,
KeyConditionExpression: &quot;#yr = :yyyy and title between :letter1 and :letter2&quot;,
ExpressionAttributeNames:{
&quot;#yr&quot;: &quot;year&quot;
},
ExpressionAttributeValues: {
&quot;:yyyy&quot;:1992,
&quot;:letter1&quot;: &quot;A&quot;,
&quot;:letter2&quot;: &quot;L&quot;
}
};
docClient.query(params, function(err, data) {
if (err) {
console.log(&quot;Unable to query. Error:&quot;, JSON.stringify(err, null, 2));
} else {
console.log(&quot;Query succeeded.&quot;);
data.Items.forEach(function(item) {
console.log(&quot; -&quot;, item.year + &quot;: &quot; + item.title
+ &quot; ... &quot; + item.info.genres
+ &quot; ... &quot; + item.info.actors[0]);
});
}
});
2.
To run the program, type the following command:
node MoviesQuery02.js
Step 4.3: Scan
The scan method reads every item in the table, and returns all the data in the table. You can provide an
optional filter_expression, so that only the items matching your criteria are returned. However, the
ﬁlter is only applied after the entire table has been scanned.
The following program scans the entire Movies table, which contains approximately 5,000 items. The
scan speciﬁes the optional ﬁlter to retrieve only the movies from the 1950s (approximately 100 items),
and discard all of the others.
1.
Copy and paste the following program into a ﬁle named MoviesScan.js:
var AWS = require(&quot;aws-sdk&quot;);
AWS.config.update({
region: &quot;us-west-2&quot;,
endpoint: &quot;http://localhost:8000&quot;
});
var docClient = new AWS.DynamoDB.DocumentClient();
var params = {
TableName: &quot;Movies&quot;,
ProjectionExpression: &quot;#yr, title, info.rating&quot;,
FilterExpression: &quot;#yr between :start_yr and :end_yr&quot;,
ExpressionAttributeNames: {
&quot;#yr&quot;: &quot;year&quot;,
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};
},
ExpressionAttributeValues: {
&quot;:start_yr&quot;: 1950,
&quot;:end_yr&quot;: 1959
}
console.log(&quot;Scanning Movies table.&quot;);
docClient.scan(params, onScan);
function onScan(err, data) {
if (err) {
console.error(&quot;Unable to scan the table. Error JSON:&quot;, JSON.stringify(err,
null, 2));
} else {
// print all the movies
console.log(&quot;Scan succeeded.&quot;);
data.Items.forEach(function(movie) {
console.log(
movie.year + &quot;: &quot;,
movie.title, &quot;- rating:&quot;, movie.info.rating);
});
}
}
// continue scanning if we have more movies, because
// scan can retrieve a maximum of 1MB of data
if (typeof data.LastEvaluatedKey != &quot;undefined&quot;) {
console.log(&quot;Scanning for more...&quot;);
params.ExclusiveStartKey = data.LastEvaluatedKey;
docClient.scan(params, onScan);
}
In the code, note the following:
• ProjectionExpression speciﬁes the attributes you want in the scan result.
• FilterExpression speciﬁes a condition that returns only items that satisfy the condition. All other
items are discarded.
2.
To run the program, type the following command:
node MoviesScan.js
Note
You can also use the Scan operation with any secondary indexes that you have created on the
table. For more information, see Improving Data Access with Secondary Indexes (p. 446).
Step 5: (Optional): Delete the Table
To delete the Movies table:
1.
Copy and paste the following program into a ﬁle named MoviesDeleteTable.js:
var AWS = require(&quot;aws-sdk&quot;);
AWS.config.update({
region: &quot;us-west-2&quot;,
endpoint: &quot;http://localhost:8000&quot;
});
var dynamodb = new AWS.DynamoDB();
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Summary
var params = {
TableName : &quot;Movies&quot;
};
dynamodb.deleteTable(params, function(err, data) {
if (err) {
console.error(&quot;Unable to delete table. Error JSON:&quot;, JSON.stringify(err, null,
2));
} else {
console.log(&quot;Deleted table. Table description JSON:&quot;, JSON.stringify(data,
null, 2));
}
});
2.
To run the program, type the following command:
node MoviesDeleteTable.js
Summary
In this tutorial, you created the Movies table in DynamoDB on your computer and performed basic
operations. The downloadable version of DynamoDB is useful during application development and
testing. However, when you're ready to run your application in a production environment, you must
modify your code so that it uses the Amazon DynamoDB web service.
Modifying the Code to Use the DynamoDB Service
To use the DynamoDB service, you must change the endpoint in your application. To do this, modify the
code as follows:
AWS.config.update({endpoint: &quot;https://dynamodb.aws-region.amazonaws.com&quot;});
For example, if you want to use the us-west-2 Region, you set the following endpoint:
AWS.config.update({endpoint: &quot;https://dynamodb.us-west-2.amazonaws.com&quot;});
Instead of using DynamoDB on your computer, the program now uses the DynamoDB web service
endpoint in US West (Oregon).
Amazon DynamoDB is available in several Regions worldwide. For the complete list, see Regions and
Endpoints in the AWS General Reference. For more information about setting Regions and endpoints in
your code, see Setting the Region in the AWS SDK for JavaScript Developer Guide.
.NET and DynamoDB
In this tutorial, you use the AWS SDK for .NET to write simple programs to perform the following
Amazon DynamoDB operations:
• Create a table called Movies using a utility program written in C#, and load sample data in JSON
format.
• Perform create, read, update, and delete operations on the table.
• Run simple queries.
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Prerequisites
The DynamoDB module of the AWS SDK for .NET oﬀers several programming models for diﬀerent use
cases. In this exercise, the C# code uses both the document model, which provides a level of abstraction
that is often convenient, and also the low-level API, which handles nested attributes more eﬀectively. For
information about the document model API, see .NET: Document Model (p. 232). For information about
the low-level API, see Working with Tables: .NET (p. 321).
You use the downloadable version of DynamoDB in this tutorial. For more information about how to run
the same code against the DynamoDB service in the cloud, see the Summary (p. 131).
Prerequisites
• Use a computer that is running a recent version of Windows and a current version of Microsoft Visual
Studio. If you don't have Visual Studio installed, you can download a free copy of the Community
edition from the Microsoft Visual Studio website.
• Download and run DynamoDB (Downloadable Version). For more information, see Setting Up
DynamoDB Local (Downloadable Version) (p. 41).
• Set up an AWS access key to use the AWS SDKs. For more information, see Setting Up DynamoDB (Web
Service) (p. 46).
• Set up a security proﬁle for DynamoDB in Visual Studio. For step-by-step instructions, see .NET Code
Samples (p. 287).
• In Visual Studio, create a new project called DynamoDB_intro using the Console Application template
in the Installed/Templates/Visual C#/ node. This is the project you use throughout this tutorial.
Note
The following tutorial does not work with .NET core because it does not support synchronous
methods. For more information, see AWS Asynchronous APIs for .NET.
• Install the NuGet package for the DynamoDB module of the AWS SDK for .NET, version 3, into your
DynamoDB_intro project. To do this, in Visual Studio, open the NuGet Package Manager Console from
the Tools menu. Then type the following command at the PM&gt; prompt:
PM&gt; Install-Package AWSSDK.DynamoDBv2
Step 1: Create a Table
The document model in the AWS SDK for .NET doesn't provide for creating tables, so you have to use the
low-level APIs. For more information, see Working with Tables: .NET (p. 321).
In this step, you create a table named Movies. The primary key for the table is composed of the following
attributes:
• year – The partition key. The AttributeType is N for number.
• title – The sort key. The AttributeType is S for string.
1.
Copy and paste the following program into the Program.cs ﬁle, replacing its current contents:
using
using
using
using
System;
System.Collections.Generic;
System.IO;
System.Text;
using
using
using
using
Amazon;
Amazon.DynamoDBv2;
Amazon.DynamoDBv2.Model;
Amazon.DynamoDBv2.DocumentModel;
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namespace DynamoDB_intro
{
class Program
{
public static void Main(string[] args)
{
// First, set up a DynamoDB client for DynamoDB Local
AmazonDynamoDBConfig ddbConfig = new AmazonDynamoDBConfig();
ddbConfig.ServiceURL = &quot;http://localhost:8000&quot;;
AmazonDynamoDBClient client;
try
{
client = new AmazonDynamoDBClient(ddbConfig);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: failed to create a DynamoDB client; &quot; +
ex.Message);
PauseForDebugWindow();
return;
}
// Build a 'CreateTableRequest' for the new table
CreateTableRequest createRequest = new CreateTableRequest
{
TableName = &quot;Movies&quot;,
AttributeDefinitions = new List&lt;AttributeDefinition&gt;()
{
new AttributeDefinition
{
AttributeName = &quot;year&quot;,
AttributeType = &quot;N&quot;
},
new AttributeDefinition
{
AttributeName = &quot;title&quot;,
AttributeType = &quot;S&quot;
}
},
KeySchema = new List&lt;KeySchemaElement&gt;()
{
new KeySchemaElement
{
AttributeName = &quot;year&quot;,
KeyType = &quot;HASH&quot;
},
new KeySchemaElement
{
AttributeName = &quot;title&quot;,
KeyType = &quot;RANGE&quot;
}
},
};
// Provisioned-throughput settings are required even though
// the local test version of DynamoDB ignores them
createRequest.ProvisionedThroughput = new ProvisionedThroughput(1, 1);
// Using the DynamoDB client, make a synchronous CreateTable request
CreateTableResponse createResponse;
try
{
createResponse = client.CreateTable(createRequest);
}
catch (Exception ex)
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{
ex.Message);
}
Console.WriteLine(&quot;\n Error: failed to create the new table; &quot; +
PauseForDebugWindow();
return;
// Report the status of the new table...
Console.WriteLine(&quot;\n\n Created the \&quot;Movies\&quot; table successfully!\n
Status of the new table: '{0}'&quot;, createResponse.TableDescription.TableStatus);
}
}
}
public static void PauseForDebugWindow()
{
// Keep the console open if in Debug mode...
Console.Write(&quot;\n\n ...Press any key to continue&quot;);
Console.ReadKey();
Console.WriteLine();
}
Note
• In the AmazonDynamoDBConfig, you set the ServiceURL to &quot;http://localhost:8000&quot; to create
the table in the downloadable version of DynamoDB running on your computer.
• In the CreateTableRequest, you specify the table name, along with primary key attributes
and their data types.
• The partition-key portion of the primary key, which determines the logical partition
where DynamoDB stores an item, is identiﬁed in its KeySchemaElement in the
CreateTableRequest as having KeyType &quot;HASH&quot;.
• The sort-key portion of the primary key, which determines the ordering of items
having the same partition-key value, is identiﬁed in its KeySchemaElement in the
CreateTableRequest as having KeyType &quot;RANGE&quot;.
• The ProvisionedThroughput ﬁeld is required, even though the downloadable version of
DynamoDB ignores it.
2.
Compile and run the program.
To learn more about managing tables, see Working with Tables in DynamoDB (p. 290).
Step 2: Load Sample Data
In this step, you populate the Movies table with sample data.
Topics
• Step 2.1: Download the Sample Data File (p. 107)
• Step 2.2: Load the Sample Data into the Movies Table (p. 107)
This scenario uses a sample data ﬁle that contains information about a few thousand movies from the
Internet Movie Database (IMDb).
The movie data is encoded as JSON. For each movie, the JSON deﬁnes a year name-value pair, a title
name-value pair, and a complex info object, as shown in the following example:
{
&quot;year&quot; : 2013,
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&quot;title&quot; : &quot;Turn It Down, Or Else!&quot;,
&quot;info&quot; : {
&quot;directors&quot; : [
&quot;Alice Smith&quot;,
&quot;Bob Jones&quot;
],
&quot;release_date&quot; : &quot;2013-01-18T00:00:00Z&quot;,
&quot;rating&quot; : 6.2,
&quot;genres&quot; : [
&quot;Comedy&quot;,
&quot;Drama&quot;
],
&quot;image_url&quot; : &quot;http://ia.media-imdb.com/images/N/
O9ERWAU7FS797AJ7LU8HN09AMUP908RLlo5JF90EWR7LJKQ7@@._V1_SX400_.jpg&quot;,
&quot;plot&quot; : &quot;A rock band plays their music at high volumes, annoying the neighbors.&quot;,
&quot;rank&quot; : 11,
&quot;running_time_secs&quot; : 5215,
&quot;actors&quot; : [
&quot;David Matthewman&quot;,
&quot;Ann Thomas&quot;,
&quot;Jonathan G. Neff&quot;
]
}
}
Step 2.1: Download the Sample Data File
1.
2.
3.
Download the sample data archive: moviedata.zip
Extract the data ﬁle (moviedata.json) from the archive.
Copy and paste themoviedata.json ﬁle into the bin/Debug folder of your DynamoDB_intro Visual
Studio project.
Step 2.2: Load the Sample Data into the Movies Table
Build a program that loads movie data into the table you created in Step 1.
1.
This program uses the open source Newtonsoft Json.NET library for deserializing JSON data,
licensed under the MIT License (MIT) (see https://github.com/JamesNK/Newtonsoft.Json/blob/
master/LICENSE.md).
To load the Json.NET library into your project, in Visual Studio, open the NuGet Package Manager
Console from the Tools menu. Then type the following command at the PM&gt; prompt:
PM&gt; Install-Package Newtonsoft.Json
2.
Copy and paste the following program into the Program.cs ﬁle, replacing its current contents:
using
using
using
using
using
System;
System.Collections.Generic;
System.IO;
System.Linq;
System.Text;
using
using
using
using
Amazon;
Amazon.DynamoDBv2;
Amazon.DynamoDBv2.Model;
Amazon.DynamoDBv2.DocumentModel;
using Newtonsoft;
using Newtonsoft.Json;
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using Newtonsoft.Json.Linq;
namespace DynamoDB_intro
{
class Program
{
public static Table GetTableObject(string tableName)
{
// First, set up a DynamoDB client for DynamoDB Local
AmazonDynamoDBConfig ddbConfig = new AmazonDynamoDBConfig();
ddbConfig.ServiceURL = &quot;http://localhost:8000&quot;;
AmazonDynamoDBClient client;
try
{
client = new AmazonDynamoDBClient(ddbConfig);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: failed to create a DynamoDB client; &quot; +
ex.Message);
return (null);
}
// Now, create a Table object for the specified table
Table table;
try
{
table = Table.LoadTable(client, tableName);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: failed to load the 'Movies' table; &quot; +
ex.Message);
return (null);
}
return (table);
}
public static void Main(string[] args)
{
// First, read in the JSON data from the moviedate.json file
StreamReader sr = null;
JsonTextReader jtr = null;
JArray movieArray = null;
try
{
sr = new StreamReader(&quot;moviedata.json&quot;);
jtr = new JsonTextReader(sr);
movieArray = (JArray)JToken.ReadFrom(jtr);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: could not read from the 'moviedata.json'
file, because: &quot; + ex.Message);
PauseForDebugWindow();
return;
}
finally
{
if (jtr != null)
jtr.Close();
if (sr != null)
sr.Close();
}
// Get a Table object for the table that you created in Step 1
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Table table = GetTableObject(&quot;Movies&quot;);
if (table == null)
{
PauseForDebugWindow();
return;
}
// Load the movie data into the table (this could take some time)
Console.Write(&quot;\n
Now writing {0:#,##0} movie records from moviedata.json
(might take 15 minutes)...\n
...completed: &quot;, movieArray.Count);
for (int i = 0, j = 99; i &lt; movieArray.Count; i++)
{
try
{
string itemJson = movieArray[i].ToString();
Document doc = Document.FromJson(itemJson);
table.PutItem(doc);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\nError: Could not write the movie record
#{0:#,##0}, because {1}&quot;, i, ex.Message);
PauseForDebugWindow();
return;
}
if (i &gt;= j)
{
j++;
Console.Write(&quot;{0,5:#,##0}, &quot;, j);
if (j % 1000 == 0)
Console.Write(&quot;\n
&quot;);
j += 99;
}
}
Console.WriteLine(&quot;\n
Finished writing all movie records to DynamoDB!&quot;);
PauseForDebugWindow();
}
}
3.
}
public static void PauseForDebugWindow()
{
// Keep the console open if in Debug mode...
Console.Write(&quot;\n\n ...Press any key to continue&quot;);
Console.ReadKey();
Console.WriteLine();
}
Now compile the project, leaving it in Debug mode, and run it.
Step 3: Create, Read, Update, and Delete an Item
In this step, you perform read and write operations on an item in the Movies table.
To learn more about reading and writing data, see Working with Items in DynamoDB (p. 327).
Topics
• Step 3.1: Create a New Item (p. 110)
• Step 3.2: Read an Item (p. 111)
• Step 3.3: Update an Item (p. 113)
• Step 3.4: Increment an Atomic Counter (p. 116)
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• Step 3.5: Update an Item (Conditionally) (p. 118)
• Step 3.6: Delete an Item (p. 120)
Step 3.1: Create a New Item
In this step, you add a new item to the Movies table.
1.
Copy and paste the following program into the Program.cs ﬁle, replacing its current contents:
using
using
using
using
System;
System.Collections.Generic;
System.Linq;
System.Text;
using
using
using
using
Amazon;
Amazon.DynamoDBv2;
Amazon.DynamoDBv2.Model;
Amazon.DynamoDBv2.DocumentModel;
namespace DynamoDB_intro
{
class Program
{
static void Main(string[] args)
{
// Get a Table object for the table that you created in Step 1
Table table = GetTableObject(&quot;Movies&quot;);
if (table == null)
{
PauseForDebugWindow();
return;
}
table
// Create a Document representing the movie item to be written to the
Document document = new Document();
document[&quot;year&quot;] = 2015;
document[&quot;title&quot;] = &quot;The Big New Movie&quot;;
document[&quot;info&quot;] = Document.FromJson(&quot;{\&quot;plot\&quot; : \&quot;Nothing happens at all.
\&quot;,\&quot;rating\&quot; : 0}&quot;);
// Use Table.PutItem to write the document item to the table
try
{
table.PutItem(document);
Console.WriteLine(&quot;\nPutItem succeeded.\n&quot;);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: Table.PutItem failed because: &quot; +
ex.Message);
PauseForDebugWindow();
return;
}
}
public static Table GetTableObject(string tableName)
{
// First, set up a DynamoDB client for DynamoDB Local
AmazonDynamoDBConfig ddbConfig = new AmazonDynamoDBConfig();
ddbConfig.ServiceURL = &quot;http://localhost:8000&quot;;
AmazonDynamoDBClient client;
try
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{
client = new AmazonDynamoDBClient(ddbConfig);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: failed to create a DynamoDB client; &quot; +
ex.Message);
return (null);
}
// Now, create a Table object for the specified table
Table table = null;
try
{
table = Table.LoadTable(client, tableName);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: failed to load the 'Movies' table; &quot; +
ex.Message);
return (null);
}
return (table);
}
}
}
public static void PauseForDebugWindow()
{
// Keep the console open if in Debug mode...
Console.Write(&quot;\n\n ...Press any key to continue&quot;);
Console.ReadKey();
Console.WriteLine();
}
Note
The primary key is required. In this table, the primary key is a composite of both a partitionkey attribute (year) and a sort-key attribute (title).
This code writes an item to the table that has the two primary key attributes (year + title)
and a complex info attribute that stores more information about the movie.
2.
Compile and run the program.
Step 3.2: Read an Item
In the previous program, you added the following item to the table:
{
}
year: 2015,
title: &quot;The Big New Movie&quot;,
info: {
plot: &quot;Nothing happens at all.&quot;,
rating: 0
}
You can use the GetItem method to read the item from the Movies table. You must specify the primary
key values so that you can read any item from Movies if you know its year and title.
1.
Copy and paste the following program into the Program.cs ﬁle, replacing its current contents:
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using
using
using
using
System;
System.Collections.Generic;
System.Linq;
System.Text;
using
using
using
using
Amazon;
Amazon.DynamoDBv2;
Amazon.DynamoDBv2.Model;
Amazon.DynamoDBv2.DocumentModel;
namespace DynamoDB_intro
{
class Program
{
static void Main(string[] args)
{
// Get a Table object for the table that you created in Step 1
Table table = GetTableObject(&quot;Movies&quot;);
if (table == null)
{
PauseForDebugWindow();
return;
}
try
{
Document document = table.GetItem(2015, &quot;The Big New Movie&quot;);
if (document != null)
Console.WriteLine(&quot;\nGetItem succeeded: \n&quot; +
document.ToJsonPretty());
else
Console.WriteLine(&quot;\nGetItem succeeded, but the item was not
found&quot;);
}
catch (Exception e)
{
Console.WriteLine(e.Message);
}
}
public static Table GetTableObject(string tableName)
{
// First, set up a DynamoDB client for DynamoDB Local
AmazonDynamoDBConfig ddbConfig = new AmazonDynamoDBConfig();
ddbConfig.ServiceURL = &quot;http://localhost:8000&quot;;
AmazonDynamoDBClient client;
try
{
client = new AmazonDynamoDBClient(ddbConfig);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: failed to create a DynamoDB client; &quot; +
ex.Message);
return (null);
}
// Now, create a Table object for the specified table
Table table = null;
try
{
table = Table.LoadTable(client, tableName);
}
catch (Exception ex)
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{
ex.Message);
}
}
2.
}
Console.WriteLine(&quot;\n Error: failed to load the 'Movies' table; &quot; +
return (null);
}
return (table);
public static void PauseForDebugWindow()
{
// Keep the console open if in Debug mode...
Console.Write(&quot;\n\n ...Press any key to continue&quot;);
Console.ReadKey();
Console.WriteLine();
}
Compile and run the program.
Step 3.3: Update an Item
You can use the UpdateItem method to modify an existing item. You can update values of existing
attributes, add new attributes, or remove attributes.
In this example, you perform the following updates:
• Change the value of the existing attributes (rating, plot).
• Add a new list attribute (actors) to the existing info map.
The item changes from this:
{
}
year: 2015,
title: &quot;The Big New Movie&quot;,
info: {
plot: &quot;Nothing happens at all.&quot;,
rating: 0
}
To the following:
{
}
1.
year: 2015,
title: &quot;The Big New Movie&quot;,
info: {
plot: &quot;Everything happens all at once.&quot;,
rating: 5.5,
actors: [&quot;Larry&quot;, &quot;Moe&quot;, &quot;Curly&quot;]
}
Copy and paste the following program into the Program.cs ﬁle, replacing its current contents:
using
using
using
using
System;
System.Collections.Generic;
System.Linq;
System.Text;
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using System.Threading.Tasks;
using
using
using
using
Amazon;
Amazon.DynamoDBv2;
Amazon.DynamoDBv2.Model;
Amazon.DynamoDBv2.DocumentModel;
namespace DynamoDB_intro
{
class Program
{
static void Main(string[] args)
{
// Get an AmazonDynamoDBClient for the local database
AmazonDynamoDBClient client = GetLocalClient();
if (client == null)
{
PauseForDebugWindow();
return;
}
= :a&quot;,
// Create an UpdateItemRequest to modify two existing nested attributes
// and add a new one
UpdateItemRequest updateRequest = new UpdateItemRequest()
{
TableName = &quot;Movies&quot;,
Key = new Dictionary&lt;string, AttributeValue&gt;
{
{ &quot;year&quot;, new AttributeValue {
N = &quot;2015&quot;
} },
{ &quot;title&quot;, new AttributeValue {
S = &quot;The Big New Movie&quot;
}}
},
ExpressionAttributeValues = new Dictionary&lt;string, AttributeValue&gt;
{
{ &quot;:r&quot;, new AttributeValue {
N = &quot;5.5&quot;
} },
{ &quot;:p&quot;, new AttributeValue {
S = &quot;Everything happens all at once!&quot;
} },
{ &quot;:a&quot;, new AttributeValue {
SS = { &quot;Larry&quot;,&quot;Moe&quot;,&quot;Curly&quot; }
} }
},
UpdateExpression = &quot;SET info.rating = :r, info.plot = :p, info.actors
};
ReturnValues = &quot;UPDATED_NEW&quot;
// Use AmazonDynamoDBClient.UpdateItem to update the specified attributes
UpdateItemResponse uir = null;
try
{
uir = client.UpdateItem(updateRequest);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\nError: UpdateItem failed, because: &quot; +
ex.Message);
if (uir != null)
Console.WriteLine(&quot;
Status code was &quot; +
uir.HttpStatusCode.ToString());
PauseForDebugWindow();
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}
succeeded
}
return;
// Get the item from the table and display it to validate that the update
DisplayMovieItem(client, &quot;2015&quot;, &quot;The Big New Movie&quot;);
public static AmazonDynamoDBClient GetLocalClient()
{
// First, set up a DynamoDB client for DynamoDB Local
AmazonDynamoDBConfig ddbConfig = new AmazonDynamoDBConfig();
ddbConfig.ServiceURL = &quot;http://localhost:8000&quot;;
AmazonDynamoDBClient client;
try
{
client = new AmazonDynamoDBClient(ddbConfig);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: failed to create a DynamoDB client; &quot; +
ex.Message);
return (null);
}
return (client);
}
public static
string title)
{
// Create
Primitive
Primitive
void DisplayMovieItem(AmazonDynamoDBClient client, string year,
Primitives for the HASH and RANGE portions of the primary key
hash = new Primitive(year, true);
range = new Primitive(title, false);
Table table = null;
try
{
table = Table.LoadTable(client, &quot;Movies&quot;);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: failed to load the 'Movies' table; &quot; +
ex.Message);
return;
}
Document document = table.GetItem(hash, range);
Console.WriteLine(&quot;\n The movie record looks like this: \n&quot; +
document.ToJsonPretty());
}
}
}
public static void PauseForDebugWindow()
{
// Keep the console open if in Debug mode...
Console.Write(&quot;\n\n ...Press any key to continue&quot;);
Console.ReadKey();
Console.WriteLine();
}
Note
Because the document model in the AWS SDK for .NET doesn't support updating
nested attributes, you must use the AmazonDynamoDBClient.UpdateItem API instead of
Table.UpdateItem to update attributes under the top-level info attribute.
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To do this, create an UpdateItemRequest that speciﬁes the item you want to update and the
new values you want to set.
• The UpdateExpression is what deﬁnes all the updates to be performed on the speciﬁed
item.
• By setting the ReturnValues ﬁeld to &quot;UPDATED_NEW&quot;, you are requesting that DynamoDB
return only the updated attributes in the response.
2.
Compile and run the program.
Step 3.4: Increment an Atomic Counter
DynamoDB supports atomic counters, where you use the UpdateItem method to increment or decrement
the value of an existing attribute without interfering with other write requests. (All write requests are
applied in the order in which they are received.)
The following program increments the rating for a movie. Each time you run it, the program increments
this attribute by one. Again, it is the UpdateExpression that determines what happens:
UpdateExpression = &quot;SET info.rating = info.rating + :inc&quot;,
1.
Copy and paste the following program into the Program.cs ﬁle, replacing its current contents:
using
using
using
using
using
System;
System.Collections.Generic;
System.Linq;
System.Text;
System.Threading.Tasks;
using
using
using
using
Amazon;
Amazon.DynamoDBv2;
Amazon.DynamoDBv2.Model;
Amazon.DynamoDBv2.DocumentModel;
namespace DynamoDB_intro
{
class Program
{
static void Main(string[] args)
{
// Get an AmazonDynamoDBClient for the local database
AmazonDynamoDBClient client = GetLocalClient();
if (client == null)
{
PauseForDebugWindow();
return;
}
// Create an UpdateItemRequest to modify two existing nested attributes
// and add a new one
UpdateItemRequest updateRequest = new UpdateItemRequest()
{
TableName = &quot;Movies&quot;,
Key = new Dictionary&lt;string, AttributeValue&gt;
{
{ &quot;year&quot;, new AttributeValue {
N = &quot;2015&quot;
} },
{ &quot;title&quot;, new AttributeValue {
S = &quot;The Big New Movie&quot;
}}
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},
{
},
};
ExpressionAttributeValues = new Dictionary&lt;string, AttributeValue&gt;
{ &quot;:inc&quot;, new AttributeValue {
N = &quot;1&quot;
} }
UpdateExpression = &quot;SET info.rating = info.rating + :inc&quot;,
ReturnValues = &quot;UPDATED_NEW&quot;
// Use AmazonDynamoDBClient.UpdateItem to update the specified attributes
UpdateItemResponse uir = null;
try
{
uir = client.UpdateItem(updateRequest);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\nError: UpdateItem failed, because &quot; +
ex.Message);
if (uir != null)
Console.WriteLine(&quot;
Status code was: &quot; +
uir.HttpStatusCode.ToString());
PauseForDebugWindow();
return;
}
succeeded
}
// Get the item from the table and display it to validate that the update
DisplayMovieItem(client, &quot;2015&quot;, &quot;The Big New Movie&quot;);
public static AmazonDynamoDBClient GetLocalClient()
{
// First, set up a DynamoDB client for DynamoDB Local
AmazonDynamoDBConfig ddbConfig = new AmazonDynamoDBConfig();
ddbConfig.ServiceURL = &quot;http://localhost:8000&quot;;
AmazonDynamoDBClient client;
try
{
client = new AmazonDynamoDBClient(ddbConfig);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: failed to create a DynamoDB client; &quot; +
ex.Message);
return (null);
}
return (client);
}
public static
string title)
{
// Create
Primitive
Primitive
void DisplayMovieItem(AmazonDynamoDBClient client, string year,
Primitives for the HASH and RANGE portions of the primary key
hash = new Primitive(year, true);
range = new Primitive(title, false);
Table table = null;
try
{
table = Table.LoadTable(client, &quot;Movies&quot;);
}
catch (Exception ex)
{
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ex.Message);
Console.WriteLine(&quot;\n Error: failed to load the 'Movies' table; &quot; +
return;
}
Document document = table.GetItem(hash, range);
Console.WriteLine(&quot;\n The movie record looks like this: \n&quot; +
document.ToJsonPretty());
}
}
2.
}
public static void PauseForDebugWindow()
{
// Keep the console open if in Debug mode...
Console.Write(&quot;\n\n ...Press any key to continue&quot;);
Console.ReadKey();
Console.WriteLine();
}
Compile and run the program.
Step 3.5: Update an Item (Conditionally)
The following program shows how to use UpdateItem with a condition. If the condition evaluates to true,
the update succeeds; otherwise, the update is not performed.
In this case, the item is only updated if there are more than three actors in the movie.
1.
Copy and paste the following program into the Program.cs ﬁle, replacing its current contents:
using
using
using
using
using
System;
System.Collections.Generic;
System.Linq;
System.Text;
System.Threading.Tasks;
using
using
using
using
Amazon;
Amazon.DynamoDBv2;
Amazon.DynamoDBv2.Model;
Amazon.DynamoDBv2.DocumentModel;
namespace DynamoDB_intro
{
class Program
{
static void Main(string[] args)
{
// Get an AmazonDynamoDBClient for the local database
AmazonDynamoDBClient client = GetLocalClient();
if (client == null)
{
PauseForDebugWindow();
return;
}
// Create an UpdateItemRequest to modify two existing nested attributes
// and add a new one
UpdateItemRequest updateRequest = new UpdateItemRequest()
{
TableName = &quot;Movies&quot;,
Key = new Dictionary&lt;string, AttributeValue&gt;
{
{ &quot;year&quot;, new AttributeValue {
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},
{
},
};
N = &quot;2015&quot;
} },
{ &quot;title&quot;, new AttributeValue {
S = &quot;The Big New Movie&quot;
} }
ExpressionAttributeValues = new Dictionary&lt;string, AttributeValue&gt;
{ &quot;:n&quot;, new AttributeValue {
N = &quot;3&quot;
} }
ConditionExpression = &quot;size(info.actors) &gt; :n&quot;,
UpdateExpression = &quot;REMOVE info.actors&quot;,
ReturnValues = &quot;UPDATED_NEW&quot;
// Use AmazonDynamoDBClient.UpdateItem to update the specified attributes
UpdateItemResponse uir = null;
try
{
uir = client.UpdateItem(updateRequest);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\nError: UpdateItem failed, because:\n
&quot; +
ex.Message);
if (uir != null)
Console.WriteLine(&quot;
Status code was &quot; +
uir.HttpStatusCode.ToString());
PauseForDebugWindow();
return;
}
if (uir.HttpStatusCode != System.Net.HttpStatusCode.OK)
{
PauseForDebugWindow();
return;
}
succeeded
}
// Get the item from the table and display it to validate that the update
DisplayMovieItem(client, &quot;2015&quot;, &quot;The Big New Movie&quot;);
public static AmazonDynamoDBClient GetLocalClient()
{
// First, set up a DynamoDB client for DynamoDB Local
AmazonDynamoDBConfig ddbConfig = new AmazonDynamoDBConfig();
ddbConfig.ServiceURL = &quot;http://localhost:8000&quot;;
AmazonDynamoDBClient client;
try
{
client = new AmazonDynamoDBClient(ddbConfig);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: failed to create a DynamoDB client; &quot; +
ex.Message);
return (null);
}
return (client);
}
public static void DisplayMovieItem(AmazonDynamoDBClient client, string year,
string title)
{
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// Create Primitives for the HASH and RANGE portions of the primary key
Primitive hash = new Primitive(year, true);
Primitive range = new Primitive(title, false);
Table table = null;
try
{
table = Table.LoadTable(client, &quot;Movies&quot;);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: failed to load the 'Movies' table; &quot; +
ex.Message);
return;
}
Document document = table.GetItem(hash, range);
Console.WriteLine(&quot;\n The movie record looks like this: \n&quot; +
document.ToJsonPretty());
}
}
2.
}
public static void PauseForDebugWindow()
{
// Keep the console open if in Debug mode...
Console.Write(&quot;\n\n ...Press any key to continue&quot;);
Console.ReadKey();
Console.WriteLine();
}
Compile and run the program.
The program should fail with the following message:
The conditional request failed
This is because the movie has three actors in it, but the condition is checking for greater than three
actors.
3.
Modify the program so that the number of actors that the ConditionExpression uses is 2 instead of
3:
{ &quot;:n&quot;, new AttributeValue { N = &quot;2&quot; } }
The condition now speciﬁes that the number of actors must be greater than 2.
4.
When you compile and run the program now, the UpdateItem operation should succeed.
Step 3.6: Delete an Item
You can use the Table.DeleteItem operation to delete an item by specifying its primary key. You can
optionally provide a condition in the DeleteItemOperationConfig parameter, to prevent the item from
being deleted if the condition is not met.
In the following example, you try to delete a speciﬁc movie item if its rating is 5 or less.
1.
Copy and paste the following program into the Program.cs ﬁle, replacing its current contents:
using
using
using
using
System;
System.Collections.Generic;
System.Linq;
System.Text;
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using System.Threading.Tasks;
using
using
using
using
Amazon;
Amazon.DynamoDBv2;
Amazon.DynamoDBv2.Model;
Amazon.DynamoDBv2.DocumentModel;
namespace DynamoDB_intro
{
class Program
{
static void Main(string[] args)
{
// Get a Table object for the table that you created in Step 1
Table table = GetTableObject(&quot;Movies&quot;);
if (table == null)
return;
&lt;= :val&quot;;
// Create the condition
DeleteItemOperationConfig opConfig = new DeleteItemOperationConfig();
lopConfig.ConditionalExpression = new Expression();
opConfig.ConditionalExpression.ExpressionAttributeValues[&quot;:val&quot;] = &quot;5.0&quot;;
opConfig.ConditionalExpression.ExpressionStatement = &quot;info.rating
// Delete this item
try
{
table.DeleteItem(2015, &quot;The Big New Movie&quot;, opConfig);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: Could not delete the movie item with
year={0}, title=\&quot;{1}\&quot;\n
Reason: {2}.&quot;,
2015, &quot;The Big New Movie&quot;, ex.Message);
}
// Try to retrieve it, to see if it has been deleted
Document document = table.GetItem(2015, &quot;The Big New Movie&quot;);
if (document == null)
Console.WriteLine(&quot;\n The movie item with year={0}, title=\&quot;{1}\&quot; has
been deleted.&quot;,
2015, &quot;The Big New Movie&quot;);
else
Console.WriteLine(&quot;\nRead back the item: \n&quot; +
document.ToJsonPretty());
}
// Keep the console open if in Debug mode...
Console.Write(&quot;\n\n ...Press any key to continue&quot;);
Console.ReadKey();
Console.WriteLine();
public static Table GetTableObject(string tableName)
{
// First, set up a DynamoDB client for DynamoDB Local
AmazonDynamoDBConfig ddbConfig = new AmazonDynamoDBConfig();
ddbConfig.ServiceURL = &quot;http://localhost:8000&quot;;
AmazonDynamoDBClient client;
try
{
client = new AmazonDynamoDBClient(ddbConfig);
}
catch (Exception ex)
{
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ex.Message);
}
Console.WriteLine(&quot;\n Error: failed to create a DynamoDB client; &quot; +
return (null);
// Now, create a Table object for the specified table
Table table = null;
try
{
table = Table.LoadTable(client, tableName);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: failed to load the 'Movies' table; &quot; +
ex.Message);
return (null);
}
return (table);
}
}
}
2.
Compile and run the program.
The program should fail with the following message:
The conditional request failed
This is because the rating for this particular move is greater than 5.
3.
Modify the program to remove the DeleteItemOperationConfig named opConfig from the call to
table.DeleteItem:
try { table.DeleteItem( 2015, &quot;The Big New Movie&quot; ); }
4.
Compile and run the program. Now, the delete succeeds because you removed the condition.
Step 4: Query and Scan the Data
You can use the Query method to retrieve data from a table. You must specify a partition key value; the
sort key is optional.
The primary key for the Movies table is composed of the following:
• year – The partition key. The attribute type is number. • title – The sort key. The attribute type is string.
To ﬁnd all movies released during a year, you need to specify only the year partition-key attribute. You
can add the title sort-key attribute to retrieve a subset of movies based on some condition (on the sortkey attribute), such as ﬁnding movies released in 2014 that have a title starting with the letter &quot;A&quot;.
In addition to Query, there is also a Scan method that can retrieve all of the table data.
To learn more about querying and scanning data, see Working with Queries (p. 410) and Working with
Scans (p. 427), respectively.
Topics
• Step 4.1: Query (p. 123)
• Step 4.2: Scan (p. 127)
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Step 4.1: Query
The C# code included in this step performs the following queries:
• Retrieves all movies release in year 1985.
• Retrieves all movies released in year 1992, with title beginning with the letter &quot;A&quot; through the letter
&quot;L&quot;.
1.
Copy and paste the following program into the Program.cs ﬁle, replacing its current contents:
using
using
using
using
using
System;
System.Collections.Generic;
System.Linq;
System.Text;
System.Threading.Tasks;
using
using
using
using
Amazon;
Amazon.DynamoDBv2;
Amazon.DynamoDBv2.Model;
Amazon.DynamoDBv2.DocumentModel;
namespace DynamoDB_intro
{
class Program
{
static string commaSep = &quot;, &quot;;
static string movieFormatString = &quot;
\&quot;{0}\&quot;, lead actor: {1}, genres: {2}&quot;;
static void Main(string[] args)
{
// Get an AmazonDynamoDBClient for the local DynamoDB database
AmazonDynamoDBClient client = GetLocalClient();
// Get a Table object for the table that you created in Step 1
Table table = GetTableObject(client, &quot;Movies&quot;);
if (table == null)
{
PauseForDebugWindow();
return;
}
*/
/*----------------------------------------------------------------------* 4.1.1: Call Table.Query to initiate a query for all movies with
*
year == 1985, using an empty filter expression.
*-----------------------------------------------------------------------
Search search;
try
{
search = table.Query(1985, new Expression());
}
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: 1985 query failed because: &quot; +
ex.Message);
PauseForDebugWindow();
return;
}
// Display the titles of the movies returned by this query
List&lt;Document&gt; docList = new List&lt;Document&gt;();
Console.WriteLine(&quot;\n All movies released in 1985:&quot; +
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do
{
ex.Message);
&quot;\n-----------------------------------------------&quot;);
try { docList = search.GetNextSet(); }
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: Search.GetNextStep failed because: &quot; +
break;
}
foreach (var doc in docList)
Console.WriteLine(&quot;
&quot; + doc[&quot;title&quot;]);
} while (!search.IsDone);
*/
{ 1992 });
/*----------------------------------------------------------------------* 4.1.2a: Call Table.Query to initiate a query for all movies where
*
year equals 1992 AND title is between &quot;B&quot; and &quot;Hzzz&quot;,
*
returning the lead actor and genres of each.
*----------------------------------------------------------------------Primitive y_1992 = new Primitive(&quot;1992&quot;, true);
QueryOperationConfig config = new QueryOperationConfig();
config.Filter = new QueryFilter();
config.Filter.AddCondition(&quot;year&quot;, QueryOperator.Equal, new DynamoDBEntry[]
config.Filter.AddCondition(&quot;title&quot;, QueryOperator.Between, new
DynamoDBEntry[] { &quot;B&quot;, &quot;Hzz&quot; });
config.AttributesToGet = new List&lt;string&gt; { &quot;title&quot;, &quot;info&quot; };
config.Select = SelectValues.SpecificAttributes;
try
{
search = table.Query(config);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: 1992 query failed because: &quot; +
ex.Message);
PauseForDebugWindow();
return;
}
// Display the movie information returned by this query
Console.WriteLine(&quot;\n\n Movies released in 1992 with titles between \&quot;B\&quot;
and \&quot;Hzz\&quot; (Document Model):&quot; +
&quot;\n-----------------------------------------------------------------------------&quot;);
docList = new List&lt;Document&gt;();
Document infoDoc;
do
{
try
{
docList = search.GetNextSet();
}
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: Search.GetNextStep failed because: &quot; +
ex.Message);
break;
}
foreach (var doc in docList)
{
infoDoc = doc[&quot;info&quot;].AsDocument();
Console.WriteLine(movieFormatString,
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doc[&quot;title&quot;],
infoDoc[&quot;actors&quot;].AsArrayOfString()[0],
string.Join(commaSep,
infoDoc[&quot;genres&quot;].AsArrayOfString()));
}
} while (!search.IsDone);
*/
and :Tzz&quot;,
/*----------------------------------------------------------------------* 4.1.2b: Call AmazonDynamoDBClient.Query to initiate a query for all
*
movies where year equals 1992 AND title is between M and Tzz,
*
returning the genres and the lead actor of each.
*----------------------------------------------------------------------QueryRequest qRequest = new QueryRequest
{
TableName = &quot;Movies&quot;,
ExpressionAttributeNames = new Dictionary&lt;string, string&gt;
{
{ &quot;#yr&quot;, &quot;year&quot; }
},
ExpressionAttributeValues = new Dictionary&lt;string, AttributeValue&gt;
{
{ &quot;:y_1992&quot;, new AttributeValue {
N = &quot;1992&quot;
} },
{ &quot;:M&quot;,
new AttributeValue {
S = &quot;M&quot;
} },
{ &quot;:Tzz&quot;,
new AttributeValue {
S = &quot;Tzz&quot;
} }
},
KeyConditionExpression = &quot;#yr = :y_1992 and title between :M
};
ProjectionExpression = &quot;title, info.actors[0], info.genres&quot;
QueryResponse qResponse;
try
{
qResponse = client.Query(qRequest);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: Low-level query failed, because: &quot; +
ex.Message);
PauseForDebugWindow();
return;
}
// Display the movie information returned by this query
Console.WriteLine(&quot;\n\n Movies released in 1992 with titles between \&quot;M\&quot;
and \&quot;Tzz\&quot; (low-level):&quot; +
&quot;\n-------------------------------------------------------------------------&quot;);
foreach (Dictionary&lt;string, AttributeValue&gt; item in qResponse.Items)
{
Dictionary&lt;string, AttributeValue&gt; info = item[&quot;info&quot;].M;
Console.WriteLine(movieFormatString,
item[&quot;title&quot;].S,
info[&quot;actors&quot;].L[0].S,
GetDdbListAsString(info[&quot;genres&quot;].L));
}
}
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public static string GetDdbListAsString(List&lt;AttributeValue&gt; strList)
{
StringBuilder sb = new StringBuilder();
string str = null;
AttributeValue av;
for (int i = 0; i &lt; strList.Count; i++)
{
av = strList[i];
if (av.S != null)
str = av.S;
else if (av.N != null)
str = av.N;
else if (av.SS != null)
str = string.Join(commaSep, av.SS.ToArray());
else if (av.NS != null)
str = string.Join(commaSep, av.NS.ToArray());
if (str != null)
{
if (i &gt; 0)
sb.Append(commaSep);
sb.Append(str);
}
}
return (sb.ToString());
}
public static AmazonDynamoDBClient GetLocalClient()
{
// First, set up a DynamoDB client for DynamoDB Local
AmazonDynamoDBConfig ddbConfig = new AmazonDynamoDBConfig();
ddbConfig.ServiceURL = &quot;http://localhost:8000&quot;;
AmazonDynamoDBClient client;
try
{
client = new AmazonDynamoDBClient(ddbConfig);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: failed to create a DynamoDB client; &quot; +
ex.Message);
return (null);
}
return (client);
}
public static Table GetTableObject(AmazonDynamoDBClient client, string
tableName)
{
Table table = null;
try
{
table = Table.LoadTable(client, tableName);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: failed to load the 'Movies' table; &quot; +
ex.Message);
return (null);
}
return (table);
}
public static void PauseForDebugWindow()
{
// Keep the console open if in Debug mode...
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}
}
}
Console.Write(&quot;\n\n ...Press any key to continue&quot;);
Console.ReadKey();
Console.WriteLine();
Note
• In the ﬁrst query, for all movies released in 1985, an empty expression indicates that
ﬁltering on the sort-key part of the primary key is not wanted.
• In the second query, which uses the AWS SDK for .NET document model to query for all
movies released in 1992 with titles starting with the letters A through L, you can query
only for top-level attributes. So you must retrieve the entire info attribute. The display
code then accesses the nested attributes you're interested in.
• In the third query, you use the low-level AWS SDK for .NET API, which gives more control
over what is returned. Here, you can retrieve only those nested attributes within the info
attribute that you're interested in, namely info.genres and info.actors[0].
2.
Compile and run the program.
Note
The preceding program shows how to query a table by its primary key attributes. In DynamoDB,
you can also optionally create one or more secondary indexes on a table, and query those
indexes in the same way that you query a table. Secondary indexes give your applications
additional ﬂexibility by allowing queries on non-key attributes. For more information, see
Improving Data Access with Secondary Indexes (p. 446).
Step 4.2: Scan
The Scan method reads every item in the table and returns all the data in the table. You can provide an
optional filter_expression so that only the items matching your criteria are returned. However, the
ﬁlter is applied only after the entire table has been scanned.
The following program scans the entire Movies table, which contains approximately 5,000 items. The
scan speciﬁes the optional ﬁlter to retrieve only the movies from the 1950s (approximately 100 items)
and discard all the others.
1.
Copy and paste the following program into the Program.cs ﬁle, replacing its current contents:
using
using
using
using
using
System;
System.Collections.Generic;
System.Linq;
System.Text;
System.Threading.Tasks;
using
using
using
using
Amazon;
Amazon.DynamoDBv2;
Amazon.DynamoDBv2.Model;
Amazon.DynamoDBv2.DocumentModel;
namespace DynamoDB_intro
{
class Program
{
static void Main(string[] args)
{
// Get an AmazonDynamoDBClient for the local DynamoDB database
AmazonDynamoDBClient client = GetLocalClient();
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// Get a Table object for the table that you created in Step 1
Table table = GetTableObject(client, &quot;Movies&quot;);
if (table == null)
{
PauseForDebugWindow();
return;
}
*/
/*----------------------------------------------------------------------* 4.2a: Call Table.Scan to return the movies released in the 1950's,
*
displaying title, year, lead actor and lead director.
*-----------------------------------------------------------------------
ScanFilter filter = new ScanFilter();
filter.AddCondition(&quot;year&quot;, ScanOperator.Between, new DynamoDBEntry[]
{ 1950, 1959 });
ScanOperationConfig config = new ScanOperationConfig
{
AttributesToGet = new List&lt;string&gt; { &quot;year, title, info&quot; },
Filter = filter
};
Search search = table.Scan(filter);
// Display the movie information returned by this query
Console.WriteLine(&quot;\n\n Movies released in the 1950's (Document Model):&quot; +
&quot;\n--------------------------------------------------&quot;);
List&lt;Document&gt; docList = new List&lt;Document&gt;();
Document infoDoc;
string movieFormatString = &quot;
\&quot;{0}\&quot; ({1})-- lead actor: {2}, lead
director: {3}&quot;;
do
{
try
{
docList = search.GetNextSet();
}
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: Search.GetNextStep failed because: &quot; +
ex.Message);
break;
}
foreach (var doc in docList)
{
infoDoc = doc[&quot;info&quot;].AsDocument();
Console.WriteLine(movieFormatString,
doc[&quot;title&quot;],
doc[&quot;year&quot;],
infoDoc[&quot;actors&quot;].AsArrayOfString()[0],
infoDoc[&quot;directors&quot;].AsArrayOfString()[0]);
}
} while (!search.IsDone);
*/
/*----------------------------------------------------------------------* 4.2b: Call AmazonDynamoDBClient.Scan to return all movies released
*
in the 1960's, only downloading the title, year, lead
*
actor and lead director attributes.
*----------------------------------------------------------------------ScanRequest sRequest = new ScanRequest
{
TableName = &quot;Movies&quot;,
ExpressionAttributeNames = new Dictionary&lt;string, string&gt;
{
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},
{
},
};
{ &quot;#yr&quot;, &quot;year&quot; }
ExpressionAttributeValues = new Dictionary&lt;string, AttributeValue&gt;
{ &quot;:y_a&quot;,
N =
} },
{ &quot;:y_z&quot;,
N =
} },
new AttributeValue {
&quot;1960&quot;
new AttributeValue {
&quot;1969&quot;
FilterExpression = &quot;#yr between :y_a and :y_z&quot;,
ProjectionExpression = &quot;#yr, title, info.actors[0], info.directors[0]&quot;
ScanResponse sResponse;
try
{
sResponse = client.Scan(sRequest);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: Low-level scan failed, because: &quot; +
ex.Message);
PauseForDebugWindow();
return;
}
}
// Display the movie information returned by this scan
Console.WriteLine(&quot;\n\n Movies released in the 1960's (low-level):&quot; +
&quot;\n-------------------------------------------&quot;);
foreach (Dictionary&lt;string, AttributeValue&gt; item in sResponse.Items)
{
Dictionary&lt;string, AttributeValue&gt; info = item[&quot;info&quot;].M;
Console.WriteLine(movieFormatString,
item[&quot;title&quot;].S,
item[&quot;year&quot;].N,
info[&quot;actors&quot;].L[0].S,
info[&quot;directors&quot;].L[0].S);
}
public static AmazonDynamoDBClient GetLocalClient()
{
// First, set up a DynamoDB client for DynamoDB Local
AmazonDynamoDBConfig ddbConfig = new AmazonDynamoDBConfig();
ddbConfig.ServiceURL = &quot;http://localhost:8000&quot;;
AmazonDynamoDBClient client;
try
{
client = new AmazonDynamoDBClient(ddbConfig);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: failed to create a DynamoDB client; &quot; +
ex.Message);
return (null);
}
return (client);
}
public static Table GetTableObject(AmazonDynamoDBClient client, string
tableName)
{
Table table = null;
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try
{
table = Table.LoadTable(client, tableName);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: failed to load the 'Movies' table; &quot; +
ex.Message);
return (null);
}
return (table);
}
}
}
public static void PauseForDebugWindow()
{
// Keep the console open if in Debug mode...
Console.Write(&quot;\n\n ...Press any key to continue&quot;);
Console.ReadKey();
Console.WriteLine();
}
In the code, note the following:
• The ﬁrst scan uses the AWS SDK for .NET document model to scan the Movies table and return
movies released in the 1950s. Because the document model doesn't support nested attributes in
the AttributesToGet ﬁeld, you must download the entire info attribute to have access to the lead
actor and director.
• The second scan uses the AWS SDK for .NET low-level API to scan the Movies table and return
movies released in the 1960s. In this case, you can download only those attribute values in info
that you're interested in, namely info.actors[0] and info.directors[0].
2.
Compile and run the program.
Note
You can also use the Scan operation with any secondary indexes that you have created on the
table. For more information, see Improving Data Access with Secondary Indexes (p. 446).
Step 5: (Optional) Delete the Table
To delete the Movies table:
1.
Copy and paste the following program into the Program.cs ﬁle, replacing its current contents:
using System;
using System.Text;
using Amazon.DynamoDBv2;
using Amazon.DynamoDBv2.Model;
namespace DynamoDB_intro
{
class Program
{
static void Main(string[] args)
{
// Get an AmazonDynamoDBClient for the local DynamoDB database
AmazonDynamoDBClient client = GetLocalClient();
try
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{
\n
client.DeleteTable(&quot;Movies&quot;);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: the \'Movies\&quot; table could not be deleted!
Reason: &quot; + ex.Message);
Console.Write(&quot;\n\n ...Press any key to continue&quot;);
Console.ReadKey();
Console.WriteLine();
return;
}
Console.WriteLine(&quot;\n Deleted the \'Movies\&quot; table successfully!&quot;);
}
public static AmazonDynamoDBClient GetLocalClient()
{
// First, set up a DynamoDB client for DynamoDB Local
AmazonDynamoDBConfig ddbConfig = new AmazonDynamoDBConfig();
ddbConfig.ServiceURL = &quot;http://localhost:8000&quot;;
AmazonDynamoDBClient client;
try
{
client = new AmazonDynamoDBClient(ddbConfig);
}
catch (Exception ex)
{
Console.WriteLine(&quot;\n Error: failed to create a DynamoDB client; &quot; +
ex.Message);
return (null);
}
return (client);
}
}
}
2.
Compile and run the program.
Summary
In this tutorial, you created the Movies table in DynamoDB on your computer and performed basic
operations. DynamoDB (Downloadable Version) is useful during application development and testing.
However, when you're ready to run your application in a production environment, you must modify your
code so that it uses the Amazon DynamoDB service.
Modifying the Code to Use the DynamoDB Service
To use the Amazon DynamoDB service, you must change the endpoint in your application.
1.
To do this, ﬁrst remove the following line:
ddbConfig.ServiceURL = &quot;http://localhost:8000&quot;;
2.
Add a new line that speciﬁes the AWS Region you want to access:
ddbConfig.RegionEndpoint = RegionEndpoint.REGION;
For example, if you want to access the us-west-2 region, you would do this:
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ddbConfig.RegionEndpoint = RegionEndpoint.USWest2;
Instead of using the downloadable version of DynamoDB, the program now uses the DynamoDB service
endpoint in US West (Oregon).
Amazon DynamoDB is available in several Regions worldwide. For the complete list, see Regions and
Endpoints in the AWS General Reference. For more information about setting Regions and endpoints in
your code, see AWS Region Selection in the AWS SDK for .NET Developer Guide.
PHP and DynamoDB
In this tutorial, you use the AWS SDK for PHP to write simple programs to perform the following Amazon
DynamoDB operations:
• Create a table called Movies and load sample data in JSON format.
• Perform create, read, update, and delete operations on the table.
• Run simple queries.
You use the downloadable version of DynamoDB in this tutorial. For information about how to run the
same code against the DynamoDB service, see the Summary (p. 149).
As you work through this tutorial, you can refer to the AWS SDK for PHP Developer Guide. The Amazon
DynamoDB section in the AWS SDK for PHP API Reference describes the parameters and results for
DynamoDB operations.
Prerequisites
• Download and run DynamoDB on your computer. For more information, see Setting Up DynamoDB
Local (Downloadable Version) (p. 41).
• Set up an AWS access key to use the AWS SDKs. For more information, see Setting Up DynamoDB (Web
Service) (p. 46).
• Set up the AWS SDK for PHP:
• Go to http://php.net and install PHP.
• Go to https://aws.amazon.com/sdk-for-php and install the SDK for PHP.
For more information, see Getting Started in the AWS SDK for PHP Getting Started Guide.
Step 1: Create a Table
In this step, you create a table named Movies. The primary key for the table is composed of the following
two attributes:
• year – The partition key. The AttributeType is N for number.
• title – The sort key. The AttributeType is S for string.
1.
Copy and paste the following program into a ﬁle named MoviesCreateTable.php:
&lt;?php
require 'vendor/autoload.php';
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date_default_timezone_set('UTC');
use Aws\DynamoDb\Exception\DynamoDbException;
$sdk = new Aws\Sdk([
'endpoint'
=&gt; 'http://localhost:8000',
'region'
=&gt; 'us-west-2',
'version' =&gt; 'latest'
]);
$dynamodb = $sdk-&gt;createDynamoDb();
$params = [
'TableName' =&gt; 'Movies',
'KeySchema' =&gt; [
[
'AttributeName' =&gt; 'year',
'KeyType' =&gt; 'HASH' //Partition key
],
[
'AttributeName' =&gt; 'title',
'KeyType' =&gt; 'RANGE' //Sort key
]
],
'AttributeDefinitions' =&gt; [
[
'AttributeName' =&gt; 'year',
'AttributeType' =&gt; 'N'
],
[
'AttributeName' =&gt; 'title',
'AttributeType' =&gt; 'S'
],
];
],
'ProvisionedThroughput' =&gt; [
'ReadCapacityUnits' =&gt; 10,
'WriteCapacityUnits' =&gt; 10
]
try {
$result = $dynamodb-&gt;createTable($params);
echo 'Created table. Status: ' .
$result['TableDescription']['TableStatus'] .&quot;\n&quot;;
} catch (DynamoDbException $e) {
echo &quot;Unable to create table:\n&quot;;
echo $e-&gt;getMessage() . &quot;\n&quot;;
}
?&gt;
Note
• You set the endpoint to indicate that you are creating the table in DynamoDB on your
computer.
• In the createTable call, you specify table name, primary key attributes, and its data
types.
• The ProvisionedThroughput parameter is required, but the downloadable version of
DynamoDB ignores it. (Provisioned throughput is beyond the scope of this exercise.)
2.
To run the program, type the following command:
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php MoviesCreateTable.php
To learn more about managing tables, see Working with Tables in DynamoDB (p. 290).
Step 2: Load Sample Data
In this step, you populate the Movies table with sample data.
Topics
• Step 2.1: Download the Sample Data File (p. 135)
• Step 2.2: Load the Sample Data into the Movies Table (p. 135)
This scenario uses a sample data ﬁle that contains information about a few thousand movies from the
Internet Movie Database (IMDb). The movie data is in JSON format, as shown in the following example.
For each movie, there is a year, a title, and a JSON map named info.
[
{
},
{
},
&quot;year&quot; : ... ,
&quot;title&quot; : ... ,
&quot;info&quot; : { ... }
&quot;year&quot; : ...,
&quot;title&quot; : ...,
&quot;info&quot; : { ... }
...
]
In the JSON data, note the following:
• The year and title are used as the primary key attribute values for the Movies table.
• The rest of the info values are stored in a single attribute called info. This program illustrates how
you can store JSON in a DynamoDB attribute.
The following is an example of movie data:
{
&quot;year&quot; : 2013,
&quot;title&quot; : &quot;Turn It Down, Or Else!&quot;,
&quot;info&quot; : {
&quot;directors&quot; : [
&quot;Alice Smith&quot;,
&quot;Bob Jones&quot;
],
&quot;release_date&quot; : &quot;2013-01-18T00:00:00Z&quot;,
&quot;rating&quot; : 6.2,
&quot;genres&quot; : [
&quot;Comedy&quot;,
&quot;Drama&quot;
],
&quot;image_url&quot; : &quot;http://ia.media-imdb.com/images/N/
O9ERWAU7FS797AJ7LU8HN09AMUP908RLlo5JF90EWR7LJKQ7@@._V1_SX400_.jpg&quot;,
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&quot;plot&quot; : &quot;A rock band plays their music at high volumes, annoying the neighbors.&quot;,
&quot;rank&quot; : 11,
&quot;running_time_secs&quot; : 5215,
&quot;actors&quot; : [
&quot;David Matthewman&quot;,
&quot;Ann Thomas&quot;,
&quot;Jonathan G. Neff&quot;
}
}
]
Step 2.1: Download the Sample Data File
1.
Download the sample data archive: moviedata.zip
2.
Extract the data ﬁle (moviedata.json) from the archive.
3.
Copy and paste the moviedata.json ﬁle into your current directory.
Step 2.2: Load the Sample Data into the Movies Table
After you download the sample data, you can run the following program to populate the Movies table.
1.
Copy and paste the following program into a ﬁle named MoviesLoadData.php:
&lt;?php
require 'vendor/autoload.php';
date_default_timezone_set('UTC');
use Aws\DynamoDb\Exception\DynamoDbException;
use Aws\DynamoDb\Marshaler;
$sdk = new Aws\Sdk([
'endpoint'
=&gt; 'http://localhost:8000',
'region'
=&gt; 'us-west-2',
'version' =&gt; 'latest'
]);
$dynamodb = $sdk-&gt;createDynamoDb();
$marshaler = new Marshaler();
$tableName = 'Movies';
$movies = json_decode(file_get_contents('moviedata.json'), true);
foreach ($movies as $movie) {
$year = $movie['year'];
$title = $movie['title'];
$info = $movie['info'];
$json = json_encode([
'year' =&gt; $year,
'title' =&gt; $title,
'info' =&gt; $info
]);
$params = [
'TableName' =&gt; $tableName,
'Item' =&gt; $marshaler-&gt;marshalJson($json)
];
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try {
$result = $dynamodb-&gt;putItem($params);
echo &quot;Added movie: &quot; . $movie['year'] . &quot; &quot; . $movie['title'] . &quot;\n&quot;;
} catch (DynamoDbException $e) {
echo &quot;Unable to add movie:\n&quot;;
echo $e-&gt;getMessage() . &quot;\n&quot;;
break;
}
}
?&gt;
Note
The DynamoDB Marshaler class has methods for converting JSON documents and PHP
arrays to the DynamoDB format. In this program, $marshaler-&gt;marshalJson($json) takes a
JSON document and converts it into a DynamoDB item.
2.
To run the program, type the following command:
php MoviesLoadData.php
Step 3: Create, Read, Update, and Delete an Item
In this step, you perform read and write operations on an item in the Movies table.
To learn more about reading and writing data, see Working with Items in DynamoDB (p. 327).
Topics
• Step 3.1: Create a New Item (p. 136)
• Step 3.2: Read an Item (p. 137)
• Step 3.3: Update an Item (p. 138)
• Step 3.4: Increment an Atomic Counter (p. 140)
• Step 3.5: Update an Item (Conditionally) (p. 141)
• Step 3.6: Delete an Item (p. 142)
Step 3.1: Create a New Item
In this step, you add a new item to the Movies table.
1.
Copy and paste the following program into a ﬁle named MoviesItemOps01.php:
&lt;?php
require 'vendor/autoload.php';
date_default_timezone_set('UTC');
use Aws\DynamoDb\Exception\DynamoDbException;
use Aws\DynamoDb\Marshaler;
$sdk = new Aws\Sdk([
'endpoint'
=&gt; 'http://localhost:8000',
'region'
=&gt; 'us-west-2',
'version' =&gt; 'latest'
]);
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$dynamodb = $sdk-&gt;createDynamoDb();
$marshaler = new Marshaler();
$tableName = 'Movies';
$year = 2015;
$title = 'The Big New Movie';
$item = $marshaler-&gt;marshalJson('
{
&quot;year&quot;: ' . $year . ',
&quot;title&quot;: &quot;' . $title . '&quot;,
&quot;info&quot;: {
&quot;plot&quot;: &quot;Nothing happens at all.&quot;,
&quot;rating&quot;: 0
}
}
');
$params = [
'TableName' =&gt; 'Movies',
'Item' =&gt; $item
];
try {
$result = $dynamodb-&gt;putItem($params);
echo &quot;Added item: $year - $title\n&quot;;
} catch (DynamoDbException $e) {
echo &quot;Unable to add item:\n&quot;;
echo $e-&gt;getMessage() . &quot;\n&quot;;
}
?&gt;
Note
The primary key is required. This code adds an item that has primary key (year, title) and
info attributes. The info attribute stores a map that provides more information about the
movie.
2.
To run the program, type the following command:
php MoviesItemOps01.php
Step 3.2: Read an Item
In the previous program, you added the following item to the table:
{
}
year: 2015,
title: &quot;The Big New Movie&quot;,
info: {
plot: &quot;Nothing happens at all.&quot;,
rating: 0
}
You can use the getItem method to read the item from the Movies table. You must specify the primary
key values, so you can read any item from Movies if you know its year and title.
1.
Copy and paste the following program into a ﬁle named MoviesItemOps02.php:
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&lt;?php
require 'vendor/autoload.php';
date_default_timezone_set('UTC');
use Aws\DynamoDb\Exception\DynamoDbException;
use Aws\DynamoDb\Marshaler;
$sdk = new Aws\Sdk([
'endpoint'
=&gt; 'http://localhost:8000',
'region'
=&gt; 'us-west-2',
'version' =&gt; 'latest'
]);
$dynamodb = $sdk-&gt;createDynamoDb();
$marshaler = new Marshaler();
$tableName = 'Movies';
$year = 2015;
$title = 'The Big New Movie';
$key = $marshaler-&gt;marshalJson('
{
&quot;year&quot;: ' . $year . ',
&quot;title&quot;: &quot;' . $title . '&quot;
}
');
$params = [
'TableName' =&gt; $tableName,
'Key' =&gt; $key
];
try {
$result = $dynamodb-&gt;getItem($params);
print_r($result[&quot;Item&quot;]);
} catch (DynamoDbException $e) {
echo &quot;Unable to get item:\n&quot;;
echo $e-&gt;getMessage() . &quot;\n&quot;;
}
?&gt;
2.
To run the program, type the following command:
php MoviesItemOps02.php
Step 3.3: Update an Item
You can use the updateItem method to modify an existing item. You can update values of existing
attributes, add new attributes, or remove attributes.
In this example, you perform the following updates:
• Change the value of the existing attributes (rating, plot).
• Add a new list attribute (actors) to the existing info map.
The item changes from this:
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{
}
year: 2015,
title: &quot;The Big New Movie&quot;,
info: {
plot: &quot;Nothing happens at all.&quot;,
rating: 0
}
To the following:
{
}
1.
year: 2015,
title: &quot;The Big New Movie&quot;,
info: {
plot: &quot;Everything happens all at once.&quot;,
rating: 5.5,
actors: [&quot;Larry&quot;, &quot;Moe&quot;, &quot;Curly&quot;]
}
Copy and paste the following program into a ﬁle named MoviesItemOps03.php:
&lt;?php
require 'vendor/autoload.php';
date_default_timezone_set('UTC');
use Aws\DynamoDb\Exception\DynamoDbException;
use Aws\DynamoDb\Marshaler;
$sdk = new Aws\Sdk([
'endpoint'
=&gt; 'http://localhost:8000',
'region'
=&gt; 'us-west-2',
'version' =&gt; 'latest'
]);
$dynamodb = $sdk-&gt;createDynamoDb();
$marshaler = new Marshaler();
$tableName = 'Movies';
$year = 2015;
$title = 'The Big New Movie';
$key = $marshaler-&gt;marshalJson('
{
&quot;year&quot;: ' . $year . ',
&quot;title&quot;: &quot;' . $title . '&quot;
}
');
$eav = $marshaler-&gt;marshalJson('
{
&quot;:r&quot;: 5.5 ,
&quot;:p&quot;: &quot;Everything happens all at once.&quot;,
&quot;:a&quot;: [ &quot;Larry&quot;, &quot;Moe&quot;, &quot;Curly&quot; ]
}
');
$params = [
'TableName' =&gt; $tableName,
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];
'Key' =&gt; $key,
'UpdateExpression' =&gt;
'set info.rating = :r, info.plot=:p, info.actors=:a',
'ExpressionAttributeValues'=&gt; $eav,
'ReturnValues' =&gt; 'UPDATED_NEW'
try {
$result = $dynamodb-&gt;updateItem($params);
echo &quot;Updated item.\n&quot;;
print_r($result['Attributes']);
} catch (DynamoDbException $e) {
echo &quot;Unable to update item:\n&quot;;
echo $e-&gt;getMessage() . &quot;\n&quot;;
}
?&gt;
Note
This program uses UpdateExpression to describe all updates you want to perform on the
speciﬁed item.
The ReturnValues parameter instructs DynamoDB to return only the updated attributes
(UPDATED_NEW).
2.
To run the program, type the following command:
php MoviesItemOps03.php
Step 3.4: Increment an Atomic Counter
DynamoDB supports atomic counters, where you use the updateItem method to increment or decrement
the value of an existing attribute without interfering with other write requests. (All write requests are
applied in the order in which they are received.)
The following program shows how to increment the rating for a movie. Each time you run it, the
program increments this attribute by one.
1.
Copy and paste the following program into a ﬁle named MoviesItemOps04.php:
&lt;?php
require 'vendor/autoload.php';
date_default_timezone_set('UTC');
use Aws\DynamoDb\Exception\DynamoDbException;
use Aws\DynamoDb\Marshaler;
$sdk = new Aws\Sdk([
'endpoint'
=&gt; 'http://localhost:8000',
'region'
=&gt; 'us-west-2',
'version' =&gt; 'latest'
]);
$dynamodb = $sdk-&gt;createDynamoDb();
$marshaler = new Marshaler();
$tableName = 'Movies';
$year = 2015;
$title = 'The Big New Movie';
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$key = $marshaler-&gt;marshalJson('
{
&quot;year&quot;: ' . $year . ',
&quot;title&quot;: &quot;' . $title . '&quot;
}
');
$eav = $marshaler-&gt;marshalJson('
{
&quot;:val&quot;: 1
}
');
$params = [
'TableName' =&gt; $tableName,
'Key' =&gt; $key,
'UpdateExpression' =&gt; 'set info.rating = info.rating + :val',
'ExpressionAttributeValues'=&gt; $eav,
'ReturnValues' =&gt; 'UPDATED_NEW'
];
try {
$result = $dynamodb-&gt;updateItem($params);
echo &quot;Updated item. ReturnValues are:\n&quot;;
print_r($result['Attributes']);
} catch (DynamoDbException $e) {
echo &quot;Unable to update item:\n&quot;;
echo $e-&gt;getMessage() . &quot;\n&quot;;
}
?&gt;
2.
To run the program, type the following command:
php MoviesItemOps04.php
Step 3.5: Update an Item (Conditionally)
The following program shows how to use UpdateItem with a condition. If the condition evaluates to true,
the update succeeds; otherwise, the update is not performed.
In this case, the item is updated only if there are more than three actors in the movie.
1.
Copy and paste the following program into a ﬁle named MoviesItemOps05.php.
&lt;?php
require 'vendor/autoload.php';
date_default_timezone_set('UTC');
use Aws\DynamoDb\Exception\DynamoDbException;
use Aws\DynamoDb\Marshaler;
$sdk = new Aws\Sdk([
'endpoint'
=&gt; 'http://localhost:8000',
'region'
=&gt; 'us-west-2',
'version' =&gt; 'latest'
]);
$dynamodb = $sdk-&gt;createDynamoDb();
$marshaler = new Marshaler();
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$tableName = 'Movies';
$year = 2015;
$title = 'The Big New Movie';
$key = $marshaler-&gt;marshalJson('
{
&quot;year&quot;: ' . $year . ',
&quot;title&quot;: &quot;' . $title . '&quot;
}
');
$eav = $marshaler-&gt;marshalJson('
{
&quot;:num&quot;: 3
}
');
$params = [
'TableName' =&gt; $tableName,
'Key' =&gt; $key,
'UpdateExpression' =&gt; 'remove info.actors[0]',
'ConditionExpression' =&gt; 'size(info.actors) &gt; :num',
'ExpressionAttributeValues'=&gt; $eav,
'ReturnValues' =&gt; 'UPDATED_NEW'
];
try {
$result = $dynamodb-&gt;updateItem($params);
echo &quot;Updated item. ReturnValues are:\n&quot;;
print_r($result['Attributes']);
} catch (DynamoDbException $e) {
echo &quot;Unable to update item:\n&quot;;
echo $e-&gt;getMessage() . &quot;\n&quot;;
}
?&gt;
2.
To run the program, type the following command:
php MoviesItemOps05.php
The program should fail with the following message:
The conditional request failed
This is because the movie has three actors in it, but the condition is checking for greater than three
actors.
3.
Modify the program so that the ConditionExpression looks like this:
ConditionExpression=&quot;size(info.actors) &gt;= :num&quot;,
The condition is now greater than or equal to 3 instead of greater than 3.
4.
Run the program again. The UpdateItem operation should now succeed.
Step 3.6: Delete an Item
You can use the deleteItem method to delete one item by specifying its primary key. You can optionally
provide a ConditionExpression to prevent the item from being deleted if the condition is not met.
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In the following example, you try to delete a speciﬁc movie item if its rating is 5 or less.
1.
Copy and paste the following program into a ﬁle named MoviesItemOps06.php:
&lt;?php
require 'vendor/autoload.php';
date_default_timezone_set('UTC');
use Aws\DynamoDb\Exception\DynamoDbException;
use Aws\DynamoDb\Marshaler;
$sdk = new Aws\Sdk([
'endpoint'
=&gt; 'http://localhost:8000',
'region'
=&gt; 'us-west-2',
'version' =&gt; 'latest'
]);
$dynamodb = $sdk-&gt;createDynamoDb();
$marshaler = new Marshaler();
$tableName = 'Movies';
$year = 2015;
$title = 'The Big New Movie';
$key = $marshaler-&gt;marshalJson('
{
&quot;year&quot;: ' . $year . ',
&quot;title&quot;: &quot;' . $title . '&quot;
}
');
$eav = $marshaler-&gt;marshalJson('
{
&quot;:val&quot;: 5
}
');
$params = [
'TableName' =&gt; $tableName,
'Key' =&gt; $key,
'ConditionExpression' =&gt; 'info.rating &lt;= :val',
'ExpressionAttributeValues'=&gt; $eav
];
try {
$result = $dynamodb-&gt;deleteItem($params);
echo &quot;Deleted item.\n&quot;;
} catch (DynamoDbException $e) {
echo &quot;Unable to delete item:\n&quot;;
echo $e-&gt;getMessage() . &quot;\n&quot;;
}
?&gt;
2.
To run the program, type the following command:
php MoviesItemOps06.php
The program should fail with the following message:
The conditional request failed
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3.
This is because the rating for this particular move is greater than 5.
Modify the program to remove the condition:
$params = [
'TableName' =&gt; $tableName,
'Key' =&gt; $key
];
4.
Run the program. Now, the delete succeeds because you removed the condition.
Step 4: Query and Scan the Data
You can use the query method to retrieve data from a table. You must specify a partition key value. The
sort key is optional.
The primary key for the Movies table is composed of the following:
• year – The partition key. The attribute type is number. • title – The sort key. The attribute type is string.
To ﬁnd all movies released during a year, you need to specify only the year. You can also provide the
title to retrieve a subset of movies based on some condition (on the sort key). For example, to ﬁnd
movies released in 2014 that have a title starting with the letter &quot;A&quot;.
In addition to query, there is also a scan method that can retrieve all of the table data.
To learn more about querying and scanning data, see Working with Queries (p. 410) and Working with
Scans (p. 427), respectively.
Topics
• Step 4.1: Query - All Movies Released in a Year (p. 144)
• Step 4.2: Query - All Movies Released in a Year with Certain Titles (p. 145)
• Step 4.3: Scan (p. 147)
Step 4.1: Query - All Movies Released in a Year
The program included in this step retrieves all movies released in the year 1985.
1.
Copy and paste the following program into a ﬁle named MoviesQuery01.php:
&lt;?php
require 'vendor/autoload.php';
date_default_timezone_set('UTC');
use Aws\DynamoDb\Exception\DynamoDbException;
use Aws\DynamoDb\Marshaler;
$sdk = new Aws\Sdk([
'endpoint'
=&gt; 'http://localhost:8000',
'region'
=&gt; 'us-west-2',
'version' =&gt; 'latest'
]);
$dynamodb = $sdk-&gt;createDynamoDb();
$marshaler = new Marshaler();
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$tableName = 'Movies';
$eav = $marshaler-&gt;marshalJson('
{
&quot;:yyyy&quot;: 1985
}
');
$params = [
'TableName' =&gt; $tableName,
'KeyConditionExpression' =&gt; '#yr = :yyyy',
'ExpressionAttributeNames'=&gt; [ '#yr' =&gt; 'year' ],
'ExpressionAttributeValues'=&gt; $eav
];
echo &quot;Querying for movies from 1985.\n&quot;;
try {
$result = $dynamodb-&gt;query($params);
echo &quot;Query succeeded.\n&quot;;
foreach ($result['Items'] as $movie) {
echo $marshaler-&gt;unmarshalValue($movie['year']) . ': ' .
$marshaler-&gt;unmarshalValue($movie['title']) . &quot;\n&quot;;
}
} catch (DynamoDbException $e) {
echo &quot;Unable to query:\n&quot;;
echo $e-&gt;getMessage() . &quot;\n&quot;;
}
?&gt;
Note
• ExpressionAttributeNames provides name substitution. We use this because year is
a reserved word in DynamoDB—you can't use it directly in any expression, including
KeyConditionExpression. You can use the expression attribute name #yr to address this.
• ExpressionAttributeValues provides value substitution. You use this because you
can't use literals in any expression, including KeyConditionExpression. You can use the
expression attribute value :yyyy to address this.
2.
To run the program, type the following command:
php MoviesItemQuery01.php
Note
The preceding program shows how to query a table by its primary key attributes. In DynamoDB,
you can optionally create one or more secondary indexes on a table, and query those indexes
in the same way that you query a table. Secondary indexes give your applications additional
ﬂexibility by allowing queries on non-key attributes. For more information, see Improving Data
Access with Secondary Indexes (p. 446).
Step 4.2: Query - All Movies Released in a Year with Certain
Titles
The program included in this step retrieves all movies released in year 1992, with title beginning with
the letter &quot;A&quot; through the letter &quot;L&quot;.
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1.
Copy and paste the following program into a ﬁle named MoviesQuery02.php:
&lt;?php
require 'vendor/autoload.php';
date_default_timezone_set('UTC');
use Aws\DynamoDb\Exception\DynamoDbException;
use Aws\DynamoDb\Marshaler;
$sdk = new Aws\Sdk([
'endpoint'
=&gt; 'http://localhost:8000',
'region'
=&gt; 'us-west-2',
'version' =&gt; 'latest'
]);
$dynamodb = $sdk-&gt;createDynamoDb();
$marshaler = new Marshaler();
$tableName = 'Movies';
$eav = $marshaler-&gt;marshalJson('
{
&quot;:yyyy&quot;:1992,
&quot;:letter1&quot;: &quot;A&quot;,
&quot;:letter2&quot;: &quot;L&quot;
}
');
$params = [
'TableName' =&gt; $tableName,
'ProjectionExpression' =&gt; '#yr, title, info.genres, info.actors[0]',
'KeyConditionExpression' =&gt;
'#yr = :yyyy and title between :letter1 and :letter2',
'ExpressionAttributeNames'=&gt; [ '#yr' =&gt; 'year' ],
'ExpressionAttributeValues'=&gt; $eav
];
echo &quot;Querying for movies from 1992 - titles A-L, with genres and lead actor\n&quot;;
try {
$result = $dynamodb-&gt;query($params);
echo &quot;Query succeeded.\n&quot;;
foreach ($result['Items'] as $i) {
$movie = $marshaler-&gt;unmarshalItem($i);
print $movie['year'] . ': ' . $movie['title'] . ' ... ';
foreach ($movie['info']['genres'] as $gen) {
print $gen . ' ';
}
}
echo ' ... ' . $movie['info']['actors'][0] . &quot;\n&quot;;
} catch (DynamoDbException $e) {
echo &quot;Unable to query:\n&quot;;
echo $e-&gt;getMessage() . &quot;\n&quot;;
}
?&gt;
2.
To run the program, type the following command:
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php MoviesQuery02.php
Step 4.3: Scan
The scan method reads every item in the entire table, and returns all of the data in the table. You can
provide an optional filter_expression, so that only the items matching your criteria are returned.
However, the ﬁlter is applied only after the entire table has been scanned.
The following program scans the entire Movies table, which contains approximately 5,000 items. The
scan speciﬁes the optional ﬁlter to retrieve only the movies from the 1950s (approximately 100 items),
and discard all of the others.
1.
Copy and paste the following program into a ﬁle named MoviesScan.php:
&lt;?php
require 'vendor/autoload.php';
date_default_timezone_set('UTC');
use Aws\DynamoDb\Exception\DynamoDbException;
use Aws\DynamoDb\Marshaler;
$sdk = new Aws\Sdk([
'endpoint'
=&gt; 'http://localhost:8000',
'region'
=&gt; 'us-west-2',
'version' =&gt; 'latest'
]);
$dynamodb = $sdk-&gt;createDynamoDb();
$marshaler = new Marshaler();
//Expression attribute values
$eav = $marshaler-&gt;marshalJson('
{
&quot;:start_yr&quot;: 1950,
&quot;:end_yr&quot;: 1959
}
');
$params = [
'TableName' =&gt; 'Movies',
'ProjectionExpression' =&gt; '#yr, title, info.rating',
'FilterExpression' =&gt; '#yr between :start_yr and :end_yr',
'ExpressionAttributeNames'=&gt; [ '#yr' =&gt; 'year' ],
'ExpressionAttributeValues'=&gt; $eav
];
echo &quot;Scanning Movies table.\n&quot;;
try {
while (true) {
$result = $dynamodb-&gt;scan($params);
foreach ($result['Items'] as $i) {
$movie = $marshaler-&gt;unmarshalItem($i);
echo $movie['year'] . ': ' . $movie['title'];
echo ' ... ' . $movie['info']['rating']
. &quot;\n&quot;;
}
if (isset($result['LastEvaluatedKey'])) {
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}
$params['ExclusiveStartKey'] = $result['LastEvaluatedKey'];
} else {
break;
}
} catch (DynamoDbException $e) {
echo &quot;Unable to scan:\n&quot;;
echo $e-&gt;getMessage() . &quot;\n&quot;;
}
?&gt;
In the code, note the following:
• ProjectionExpression speciﬁes the attributes you want in the scan result.
• FilterExpression speciﬁes a condition that returns only items that satisfy the condition. All other
items are discarded.
2.
To run the program, type the following command:
php MoviesScan.php
Note
You can also use the Scan operation with any secondary indexes that you have created on the
table. For more information, see Improving Data Access with Secondary Indexes (p. 446).
Step 5: (Optional) Delete the Table
To delete the Movies table:
1.
Copy and paste the following program into a ﬁle named MoviesDeleteTable.php:
&lt;?php
require 'vendor/autoload.php';
date_default_timezone_set('UTC');
use Aws\DynamoDb\Exception\DynamoDbException;
$sdk = new Aws\Sdk([
'endpoint'
=&gt; 'http://localhost:8000',
'region'
=&gt; 'us-west-2',
'version' =&gt; 'latest'
]);
$dynamodb = $sdk-&gt;createDynamoDb();
$params = [
'TableName' =&gt; 'Movies'
];
try {
$result = $dynamodb-&gt;deleteTable($params);
echo &quot;Deleted table.\n&quot;;
} catch (DynamoDbException $e) {
echo &quot;Unable to delete table:\n&quot;;
echo $e-&gt;getMessage() . &quot;\n&quot;;
}
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?&gt;
2.
To run the program, type the following command:
php MoviesDeleteTable.php
Summary
In this tutorial, you created the Movies table in DynamoDB on your computer and performed basic
operations. The downloadable version of DynamoDB is useful during application development and
testing. However, when you're ready to run your application in a production environment, you need to
modify your code so that it uses the Amazon DynamoDB web service.
Modifying the Code to Use the DynamoDB Service
To use the DynamoDB service, you must change the endpoint in your application. To do this, ﬁnd the
following lines in the code:
$sdk = new Aws\Sdk([
'endpoint'
=&gt; 'http://localhost:8000',
'region'
=&gt; 'us-west-2',
'version' =&gt; 'latest'
]);
Remove the endpoint parameter so that the code looks like this:
$sdk = new Aws\Sdk([
'region'
=&gt; 'us-west-2',
'version' =&gt; 'latest'
]);
After you remove this line, the code can access the DynamoDB service in the Region speciﬁed by the
region conﬁg value. For example, the following line speciﬁes that you want to use the US West (Oregon)
Region:
'region'
=&gt; 'us-west-2',
Instead of using the downloadable version of DynamoDB on your computer, the program now uses the
DynamoDB service endpoint in US West (Oregon).
DynamoDB is available in several Regions worldwide. For the complete list, see Regions and Endpoints in
the AWS General Reference. For more information about setting Regions and endpoints in your code, see
the boto: A Python interface to Amazon Web Services.
Python and DynamoDB
In this tutorial, you use the AWS SDK for Python (Boto 3) to write simple programs to perform the
following Amazon DynamoDB operations:
• Create a table called Movies and load sample data in JSON format.
• Perform create, read, update, and delete operations on the table.
• Run simple queries.
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Prerequisites
You use the downloadable version of DynamoDB in this tutorial. In the Summary (p. 164), we explain
how to run the same code against the DynamoDB web service.
As you work through this tutorial, you can refer to the AWS SDK for Python (Boto) documentation at
http://boto.readthedocs.org/en/latest/. The following sections are speciﬁc to DynamoDB:
• DynamoDB tutorial
• DynamoDB low-level client
Prerequisites
• Download and run DynamoDB on your computer. For more information, see Setting Up DynamoDB
Local (Downloadable Version) (p. 41).
• Set up an AWS access key to use the AWS SDKs. For more information, see Setting Up DynamoDB (Web
Service) (p. 46).
• Install Python 2.6 or later. For more information, see https://www.python.org/downloads. For
instructions, see Quickstart in the Boto 3 documentation.
Step 1: Create a Table
In this step, you create a table named Movies. The primary key for the table is composed of the following
attributes:
• year – The partition key. The AttributeType is N for number.
• title – The sort key. The AttributeType is S for string.
1.
Copy and paste the following program into a ﬁle named MoviesCreateTable.py.
from __future__ import print_function # Python 2/3 compatibility
import boto3
dynamodb = boto3.resource('dynamodb', region_name='us-west-2', endpoint_url=&quot;http://
localhost:8000&quot;)
table = dynamodb.create_table(
TableName='Movies',
KeySchema=[
{
'AttributeName': 'year',
'KeyType': 'HASH' #Partition key
},
{
'AttributeName': 'title',
'KeyType': 'RANGE' #Sort key
}
],
AttributeDefinitions=[
{
'AttributeName': 'year',
'AttributeType': 'N'
},
{
'AttributeName': 'title',
'AttributeType': 'S'
},
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],
ProvisionedThroughput={
'ReadCapacityUnits': 10,
'WriteCapacityUnits': 10
}
)
print(&quot;Table status:&quot;, table.table_status)
Note
• You set the endpoint to indicate that you are creating the table in the downloadable
version of DynamoDB on your computer.
• In the create_table call, you specify table name, primary key attributes, and its data
types.
• The ProvisionedThroughput parameter is required. However, the downloadable version
of DynamoDB ignores it. (Provisioned throughput is beyond the scope of this exercise.)
• These examples use the Python 3 style print function. The line from __future__ import
print_function enables Python 3 printing in Python 2.6 and later.
2.
To run the program, type the following command:
python MoviesCreateTable.py
To learn more about managing tables, see Working with Tables in DynamoDB (p. 290).
Step 2: Load Sample Data
In this step, you populate the Movies table with sample data.
Topics
• Step 2.1: Download the Sample Data File (p. 152)
• Step 2.2: Load the Sample Data into the Movies Table (p. 152)
This scenario uses a sample data ﬁle that contains information about a few thousand movies from the
Internet Movie Database (IMDb). The movie data is in JSON format, as shown in the following example.
For each movie, there is a year, a title, and a JSON map named info.
[
{
},
{
},
&quot;year&quot; : ... ,
&quot;title&quot; : ... ,
&quot;info&quot; : { ... }
&quot;year&quot; : ...,
&quot;title&quot; : ...,
&quot;info&quot; : { ... }
...
]
In the JSON data, note the following:
• The year and title are used as the primary key attribute values for the Movies table.
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• The rest of the info values are stored in a single attribute called info. This program illustrates how
you can store JSON in a DynamoDB attribute.
The following is an example of movie data:
{
&quot;year&quot; : 2013,
&quot;title&quot; : &quot;Turn It Down, Or Else!&quot;,
&quot;info&quot; : {
&quot;directors&quot; : [
&quot;Alice Smith&quot;,
&quot;Bob Jones&quot;
],
&quot;release_date&quot; : &quot;2013-01-18T00:00:00Z&quot;,
&quot;rating&quot; : 6.2,
&quot;genres&quot; : [
&quot;Comedy&quot;,
&quot;Drama&quot;
],
&quot;image_url&quot; : &quot;http://ia.media-imdb.com/images/N/
O9ERWAU7FS797AJ7LU8HN09AMUP908RLlo5JF90EWR7LJKQ7@@._V1_SX400_.jpg&quot;,
&quot;plot&quot; : &quot;A rock band plays their music at high volumes, annoying the neighbors.&quot;,
&quot;rank&quot; : 11,
&quot;running_time_secs&quot; : 5215,
&quot;actors&quot; : [
&quot;David Matthewman&quot;,
&quot;Ann Thomas&quot;,
&quot;Jonathan G. Neff&quot;
]
}
}
Step 2.1: Download the Sample Data File
1.
Download the sample data archive: moviedata.zip
2.
Extract the data ﬁle (moviedata.json) from the archive.
3.
Copy and paste the moviedata.json ﬁle into your current directory.
Step 2.2: Load the Sample Data into the Movies Table
After you download the sample data, you can run the following program to populate the Movies table.
1.
Copy and paste the following program into a ﬁle named MoviesLoadData.py:
from __future__ import print_function # Python 2/3 compatibility
import boto3
import json
import decimal
dynamodb = boto3.resource('dynamodb', region_name='us-west-2', endpoint_url=&quot;http://
localhost:8000&quot;)
table = dynamodb.Table('Movies')
with open(&quot;moviedata.json&quot;) as json_file:
movies = json.load(json_file, parse_float = decimal.Decimal)
for movie in movies:
year = int(movie['year'])
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title = movie['title']
info = movie['info']
print(&quot;Adding movie:&quot;, year, title)
table.put_item(
Item={
'year': year,
'title': title,
'info': info,
}
)
2.
To run the program, type the following command:
python MoviesLoadData.py
Step 3: Create, Read, Update, and Delete an Item
In this step, you perform read and write operations on an item in the Movies table.
To learn more about reading and writing data, see Working with Items in DynamoDB (p. 327).
Topics
• Step 3.1: Create a New Item (p. 153)
• Step 3.2: Read an Item (p. 154)
• Step 3.3: Update an Item (p. 155)
• Step 3.4: Increment an Atomic Counter (p. 156)
• Step 3.5: Update an Item (Conditionally) (p. 157)
• Step 3.6: Delete an Item (p. 158)
Step 3.1: Create a New Item
In this step, you add a new item to the Movies table.
1.
Copy and paste the following program into a ﬁle named MoviesItemOps01.py:
from __future__ import print_function # Python 2/3 compatibility
import boto3
import json
import decimal
# Helper class to convert a DynamoDB item to JSON.
class DecimalEncoder(json.JSONEncoder):
def default(self, o):
if isinstance(o, decimal.Decimal):
if o % 1 &gt; 0:
return float(o)
else:
return int(o)
return super(DecimalEncoder, self).default(o)
dynamodb = boto3.resource('dynamodb', region_name='us-west-2', endpoint_url=&quot;http://
localhost:8000&quot;)
table = dynamodb.Table('Movies')
title = &quot;The Big New Movie&quot;
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year = 2015
response = table.put_item(
Item={
'year': year,
'title': title,
'info': {
'plot':&quot;Nothing happens at all.&quot;,
'rating': decimal.Decimal(0)
}
}
)
print(&quot;PutItem succeeded:&quot;)
print(json.dumps(response, indent=4, cls=DecimalEncoder))
Note
• The primary key is required. This code adds an item that has primary key (year, title)
and info attributes. The info attribute stores sample JSON that provides more
information about the movie.
• The DecimalEncoder class is used to print out numbers stored using the Decimal class.
The Boto SDK uses the Decimal class to hold DynamoDB number values.
2.
To run the program, type the following command:
python MoviesItemOps01.py
Step 3.2: Read an Item
In the previous program, you added the following item to the table:
{
}
year: 2015,
title: &quot;The Big New Movie&quot;,
info: {
plot: &quot;Nothing happens at all.&quot;,
rating: 0
}
You can use the get_item method to read the item from the Movies table. You must specify the primary
key values, so you can read any item from Movies if you know its year and title.
1.
Copy and paste the following program into a ﬁle named MoviesItemOps02.py.
from __future__ import print_function # Python 2/3 compatibility
import boto3
import json
import decimal
from boto3.dynamodb.conditions import Key, Attr
from botocore.exceptions import ClientError
# Helper class to convert a DynamoDB item to JSON.
class DecimalEncoder(json.JSONEncoder):
def default(self, o):
if isinstance(o, decimal.Decimal):
if o % 1 &gt; 0:
return float(o)
else:
return int(o)
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return super(DecimalEncoder, self).default(o)
dynamodb = boto3.resource(&quot;dynamodb&quot;, region_name='us-west-2', endpoint_url=&quot;http://
localhost:8000&quot;)
table = dynamodb.Table('Movies')
title = &quot;The Big New Movie&quot;
year = 2015
try:
response = table.get_item(
Key={
'year': year,
'title': title
}
)
except ClientError as e:
print(e.response['Error']['Message'])
else:
item = response['Item']
print(&quot;GetItem succeeded:&quot;)
print(json.dumps(item, indent=4, cls=DecimalEncoder))
2.
To run the program, type the following command:
python MoviesItemOps02.py
Step 3.3: Update an Item
You can use the update_item method to modify an existing item. You can update values of existing
attributes, add new attributes, or remove attributes.
In this example, you perform the following updates:
• Change the value of the existing attributes (rating, plot).
• Add a new list attribute (actors) to the existing info map.
The item changes from this:
{
}
year: 2015,
title: &quot;The Big New Movie&quot;,
info: {
plot: &quot;Nothing happens at all.&quot;,
rating: 0
}
To the following:
{
}
year: 2015,
title: &quot;The Big New Movie&quot;,
info: {
plot: &quot;Everything happens all at once.&quot;,
rating: 5.5,
actors: [&quot;Larry&quot;, &quot;Moe&quot;, &quot;Curly&quot;]
}
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1.
Copy and paste the following program into a ﬁle named MoviesItemOps03.py:
from __future__ import print_function # Python 2/3 compatibility
import boto3
import json
import decimal
# Helper class to convert a DynamoDB item to JSON.
class DecimalEncoder(json.JSONEncoder):
def default(self, o):
if isinstance(o, decimal.Decimal):
if o % 1 &gt; 0:
return float(o)
else:
return int(o)
return super(DecimalEncoder, self).default(o)
dynamodb = boto3.resource('dynamodb', region_name='us-west-2', endpoint_url=&quot;http://
localhost:8000&quot;)
table = dynamodb.Table('Movies')
title = &quot;The Big New Movie&quot;
year = 2015
response = table.update_item(
Key={
'year': year,
'title': title
},
UpdateExpression=&quot;set info.rating = :r, info.plot=:p, info.actors=:a&quot;,
ExpressionAttributeValues={
':r': decimal.Decimal(5.5),
':p': &quot;Everything happens all at once.&quot;,
':a': [&quot;Larry&quot;, &quot;Moe&quot;, &quot;Curly&quot;]
},
ReturnValues=&quot;UPDATED_NEW&quot;
)
print(&quot;UpdateItem succeeded:&quot;)
print(json.dumps(response, indent=4, cls=DecimalEncoder))
Note
2.
This program uses UpdateExpression to describe all updates you want to perform on the
speciﬁed item.
The ReturnValues parameter instructs DynamoDB to return only the updated attributes
(UPDATED_NEW).
To run the program, type the following command:
python MoviesItemOps03.py
Step 3.4: Increment an Atomic Counter
DynamoDB supports atomic counters, where you use the update_item method to increment or
decrement the value of an existing attribute without interfering with other write requests. (All write
requests are applied in the order in which they are received.)
The following program shows how to increment the rating for a movie. Each time you run it, the
program increments this attribute by one.
1.
Copy and paste the following program into a ﬁle named MoviesItemOps04.py:
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from __future__ import print_function # Python 2/3 compatibility
import boto3
import json
import decimal
# Helper class to convert a DynamoDB item to JSON.
class DecimalEncoder(json.JSONEncoder):
def default(self, o):
if isinstance(o, decimal.Decimal):
if o % 1 &gt; 0:
return float(o)
else:
return int(o)
return super(DecimalEncoder, self).default(o)
dynamodb = boto3.resource('dynamodb', region_name='us-west-2', endpoint_url=&quot;http://
localhost:8000&quot;)
table = dynamodb.Table('Movies')
title = &quot;The Big New Movie&quot;
year = 2015
response = table.update_item(
Key={
'year': year,
'title': title
},
UpdateExpression=&quot;set info.rating = info.rating + :val&quot;,
ExpressionAttributeValues={
':val': decimal.Decimal(1)
},
ReturnValues=&quot;UPDATED_NEW&quot;
)
print(&quot;UpdateItem succeeded:&quot;)
print(json.dumps(response, indent=4, cls=DecimalEncoder))
2.
To run the program, type the following command:
python MoviesItemOps04.py
Step 3.5: Update an Item (Conditionally)
The following program shows how to use UpdateItem with a condition. If the condition evaluates to true,
the update succeeds; otherwise, the update is not performed.
In this case, the item is updated only if there are more than three actors.
1.
Copy and paste the following program into a ﬁle named MoviesItemOps05.py:
from __future__ import print_function # Python 2/3 compatibility
import boto3
from botocore.exceptions import ClientError
import json
import decimal
# Helper class to convert a DynamoDB item to JSON.
class DecimalEncoder(json.JSONEncoder):
def default(self, o):
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if isinstance(o, decimal.Decimal):
if o % 1 &gt; 0:
return float(o)
else:
return int(o)
return super(DecimalEncoder, self).default(o)
dynamodb = boto3.resource('dynamodb', region_name='us-west-2', endpoint_url=&quot;http://
localhost:8000&quot;)
table = dynamodb.Table('Movies')
title = &quot;The Big New Movie&quot;
year = 2015
# Conditional update (will fail)
print(&quot;Attempting conditional update...&quot;)
try:
response = table.update_item(
Key={
'year': year,
'title': title
},
UpdateExpression=&quot;remove info.actors[0]&quot;,
ConditionExpression=&quot;size(info.actors) &gt; :num&quot;,
ExpressionAttributeValues={
':num': 3
},
ReturnValues=&quot;UPDATED_NEW&quot;
)
except ClientError as e:
if e.response['Error']['Code'] == &quot;ConditionalCheckFailedException&quot;:
print(e.response['Error']['Message'])
else:
raise
else:
print(&quot;UpdateItem succeeded:&quot;)
print(json.dumps(response, indent=4, cls=DecimalEncoder))
2.
To run the program, type the following command:
python MoviesItemOps05.py
The program should fail with the following message:
The conditional request failed
This is because the movie has three actors in it, but the condition is checking for greater than three
actors.
3.
Modify the program so that the ConditionExpression looks like this:
ConditionExpression=&quot;size(info.actors) &gt;= :num&quot;,
The condition is now greater than or equal to 3 instead of greater than 3.
4.
Run the program again. The UpdateItem operation should now succeed.
Step 3.6: Delete an Item
You can use the delete_item method to delete one item by specifying its primary key. You can optionally
provide a ConditionExpression to prevent the item from being deleted if the condition is not met.
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In the following example, you try to delete a speciﬁc movie item if its rating is 5 or less.
1.
Copy and paste the following program into a ﬁle named MoviesItemOps06.py:
from __future__ import print_function # Python 2/3 compatibility
import boto3
from botocore.exceptions import ClientError
import json
import decimal
# Helper class to convert a DynamoDB item to JSON.
class DecimalEncoder(json.JSONEncoder):
def default(self, o):
if isinstance(o, decimal.Decimal):
if o % 1 &gt; 0:
return float(o)
else:
return int(o)
return super(DecimalEncoder, self).default(o)
dynamodb = boto3.resource('dynamodb', region_name='us-west-2', endpoint_url=&quot;http://
localhost:8000&quot;)
table = dynamodb.Table('Movies')
title = &quot;The Big New Movie&quot;
year = 2015
print(&quot;Attempting a conditional delete...&quot;)
try:
response = table.delete_item(
Key={
'year': year,
'title': title
},
ConditionExpression=&quot;info.rating &lt;= :val&quot;,
ExpressionAttributeValues= {
&quot;:val&quot;: decimal.Decimal(5)
}
)
except ClientError as e:
if e.response['Error']['Code'] == &quot;ConditionalCheckFailedException&quot;:
print(e.response['Error']['Message'])
else:
raise
else:
print(&quot;DeleteItem succeeded:&quot;)
print(json.dumps(response, indent=4, cls=DecimalEncoder))
2.
To run the program, type the following command:
python MoviesItemOps06.py
The program should fail with the following message:
The conditional request failed
This is because the rating for this particular move is greater than 5.
3.
Modify the program to remove the condition in table.delete_item:
response = table.delete_item(
Key={
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)
4.
}
'year': year,
'title': title
Run the program. Now, the delete succeeds because you removed the condition.
Step 4: Query and Scan the Data
You can use the query method to retrieve data from a table. You must specify a partition key value. The
sort key is optional.
The primary key for the Movies table is composed of the following:
• year – The partition key. The attribute type is number. • title – The sort key. The attribute type is string.
To ﬁnd all movies released during a year, you need to specify only the year. You can also provide the
title to retrieve a subset of movies based on some condition (on the sort key); for example, to ﬁnd
movies released in 2014 that have a title starting with the letter &quot;A&quot;.
In addition to query, there is also a scan method that can retrieve all the table data.
To learn more about querying and scanning data, see Working with Queries (p. 410) and Working with
Scans (p. 427), respectively.
Topics
• Step 4.1: Query - All Movies Released in a Year (p. 160)
• Step 4.2: Query - All Movies Released in a Year with Certain Titles (p. 161)
• Step 4.3: Scan (p. 162)
Step 4.1: Query - All Movies Released in a Year
The program included in this step retrieves all movies released in the year 1985.
1.
Copy and paste the following program into a ﬁle named MoviesQuery01.py.
from __future__ import print_function # Python 2/3 compatibility
import boto3
import json
import decimal
from boto3.dynamodb.conditions import Key, Attr
# Helper class to convert a DynamoDB item to JSON.
class DecimalEncoder(json.JSONEncoder):
def default(self, o):
if isinstance(o, decimal.Decimal):
if o % 1 &gt; 0:
return float(o)
else:
return int(o)
return super(DecimalEncoder, self).default(o)
dynamodb = boto3.resource('dynamodb', region_name='us-west-2', endpoint_url=&quot;http://
localhost:8000&quot;)
table = dynamodb.Table('Movies')
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print(&quot;Movies from 1985&quot;)
response = table.query(
KeyConditionExpression=Key('year').eq(1985)
)
for i in response['Items']:
print(i['year'], &quot;:&quot;, i['title'])
Note
The Boto 3 SDK constructs a ConditionExpression for you when you use the Key and
Attr functions imported from boto3.dynamodb.conditions. You can also specify a
ConditionExpression as a string.
For a list of available conditions for DynamoDB, see the DynamoDB Conditions in AWS SDK
for Python (Boto 3) Getting Started.
For more information, see Condition Expressions (p. 346).
2.
To run the program, type the following command:
python MoviesQuery01.py
Note
The preceding program shows how to query a table by its primary key attributes. In DynamoDB,
you can optionally create one or more secondary indexes on a table, and query those indexes
in the same way that you query a table. Secondary indexes give your applications additional
ﬂexibility by allowing queries on non-key attributes. For more information, see Improving Data
Access with Secondary Indexes (p. 446).
Step 4.2: Query - All Movies Released in a Year with Certain
Titles
The program included in this step retrieves all movies released in year 1992, with title beginning with
the letter &quot;A&quot; through the letter &quot;L&quot;.
1.
Copy and paste the following program into a ﬁle named MoviesQuery02.py:
from __future__ import print_function # Python 2/3 compatibility
import boto3
import json
import decimal
from boto3.dynamodb.conditions import Key, Attr
# Helper class to convert a DynamoDB item to JSON.
class DecimalEncoder(json.JSONEncoder):
def default(self, o):
if isinstance(o, decimal.Decimal):
return str(o)
return super(DecimalEncoder, self).default(o)
dynamodb = boto3.resource('dynamodb', region_name='us-west-2', endpoint_url=&quot;http://
localhost:8000&quot;)
table = dynamodb.Table('Movies')
print(&quot;Movies from 1992 - titles A-L, with genres and lead actor&quot;)
response = table.query(
ProjectionExpression=&quot;#yr, title, info.genres, info.actors[0]&quot;,
ExpressionAttributeNames={ &quot;#yr&quot;: &quot;year&quot; }, # Expression Attribute Names for
Projection Expression only.
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)
KeyConditionExpression=Key('year').eq(1992) &amp; Key('title').between('A', 'L')
for i in response[u'Items']:
print(json.dumps(i, cls=DecimalEncoder))
2.
To run the program, type the following command:
python MoviesQuery02.py
Step 4.3: Scan
The scan method reads every item in the entire table, and returns all the data in the table. You can
provide an optional filter_expression, so that only the items matching your criteria are returned.
However, the ﬁlter is applied only after the entire table has been scanned.
The following program scans the entire Movies table, which contains approximately 5,000 items. The
scan speciﬁes the optional ﬁlter to retrieve only the movies from the 1950s (approximately 100 items),
and discard all the others.
1.
Copy and paste the following program into a ﬁle named MoviesScan.py:
from __future__ import print_function # Python 2/3 compatibility
import boto3
import json
import decimal
from boto3.dynamodb.conditions import Key, Attr
# Helper class to convert a DynamoDB item to JSON.
class DecimalEncoder(json.JSONEncoder):
def default(self, o):
if isinstance(o, decimal.Decimal):
if o % 1 &gt; 0:
return float(o)
else:
return int(o)
return super(DecimalEncoder, self).default(o)
dynamodb = boto3.resource('dynamodb', region_name='us-west-2', endpoint_url=&quot;http://
localhost:8000&quot;)
table = dynamodb.Table('Movies')
fe = Key('year').between(1950, 1959);
pe = &quot;#yr, title, info.rating&quot;
# Expression Attribute Names for Projection Expression only.
ean = { &quot;#yr&quot;: &quot;year&quot;, }
esk = None
response = table.scan(
FilterExpression=fe,
ProjectionExpression=pe,
ExpressionAttributeNames=ean
)
for i in response['Items']:
print(json.dumps(i, cls=DecimalEncoder))
while 'LastEvaluatedKey' in response:
response = table.scan(
ProjectionExpression=pe,
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FilterExpression=fe,
ExpressionAttributeNames= ean,
ExclusiveStartKey=response['LastEvaluatedKey']
)
for i in response['Items']:
print(json.dumps(i, cls=DecimalEncoder))
In the code, note the following:
• ProjectionExpression speciﬁes the attributes you want in the scan result.
• FilterExpression speciﬁes a condition that returns only items that satisfy the condition. All other
items are discarded.
• The scan method returns a subset of the items each time, called a page. The LastEvaluatedKey
value in the response is then passed to the scan method via the ExclusiveStartKey parameter.
When the last page is returned, LastEvaluatedKey is not part of the response.
Note
• ExpressionAttributeNames provides name substitution. We use this because year is
a reserved word in DynamoDB—you can't use it directly in any expression, including
KeyConditionExpression. You can use the expression attribute name #yr to address this.
• ExpressionAttributeValues provides value substitution. You use this because you
can't use literals in any expression, including KeyConditionExpression. You can use the
expression attribute value :yyyy to address this.
2.
To run the program, type the following command:
python MoviesScan.py
Note
You can also use the Scan operation with any secondary indexes that you create on the table.
For more information, see Improving Data Access with Secondary Indexes (p. 446).
Step 5: (Optional) Delete the Table
To delete the Movies table:
1.
Copy and paste the following program into a ﬁle named MoviesDeleteTable.py:
from __future__ import print_function # Python 2/3 compatibility
import boto3
dynamodb = boto3.resource('dynamodb', region_name='us-west-2', endpoint_url=&quot;http://
localhost:8000&quot;)
table = dynamodb.Table('Movies')
table.delete()
2.
To run the program, type the following command:
python MoviesDeleteTable.py
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Summary
Summary
In this tutorial, you created the Movies table in the downloadable version of DynamoDB on your
computer and performed basic operations. The downloadable version of DynamoDB is useful during
application development and testing. However, when you're ready to run your application in a
production environment, you must modify your code so that it uses the Amazon DynamoDB web service.
Modifying the Code to Use the DynamoDB Service
To use the Amazon DynamoDB service, you must change the endpoint in your application. To do this,
modify the following line:
dynamodb = boto3.resource('dynamodb',endpoint_url=&quot;http://localhost:8000&quot;)
For example, if you want to use the us-west-2 Region:
dynamodb = boto3.resource('dynamodb',region_name='us-west-2')
Instead of using the downloadable version of DynamoDB on your computer, the program now uses the
DynamoDB service in US West (Oregon).
DynamoDB is available in several Regions worldwide. For the complete list, see Regions and Endpoints in
the AWS General Reference. For more information about setting Regions and endpoints in your code, see
AWS Region Selection in the AWS SDK for Java Developer Guide.
Ruby and DynamoDB
In this tutorial, you use the AWS SDK for Ruby to write simple programs to perform the following
Amazon DynamoDB operations:
• Create a table called Movies and load sample data in JSON format.
• Perform create, read, update, and delete operations on the table.
• Run simple queries.
You use the downloadable version of DynamoDB in this tutorial. For information about how to run the
same code against the DynamoDB service, see the Summary (p. 179).
As you work through this tutorial, you can refer to the AWS SDK for Ruby API Reference. The DynamoDB
section describes the parameters and results for DynamoDB operations.
Prerequisites
• Download and run DynamoDB on your computer. For more information, see Setting Up DynamoDB
Local (Downloadable Version) (p. 41).
• Set up an AWS access key to use the AWS SDKs. For more information, see Setting Up DynamoDB (Web
Service) (p. 46).
• Set up the AWS SDK for Ruby:
• Go to https://www.ruby-lang.org/en/documentation/installation/ and install Ruby.
• Go to https://aws.amazon.com/sdk-for-ruby and install the AWS SDK for Ruby.
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Step 1: Create a Table
For more information, see Installation in the AWS SDK for Ruby API Reference.
Step 1: Create a Table
In this step, you create a table named Movies. The primary key for the table is composed of the following
two attributes:
• year – The partition key. The attribute_type is N for number. • title – The sort key. The attribute_type is S for string.
1.
Copy and paste the following program into a ﬁle named MoviesCreateTable.rb:
require &quot;aws-sdk&quot;
Aws.config.update({
region: &quot;us-west-2&quot;,
endpoint: &quot;http://localhost:8000&quot;
})
dynamodb = Aws::DynamoDB::Client.new
params = {
table_name: &quot;Movies&quot;,
key_schema: [
{
attribute_name: &quot;year&quot;,
key_type: &quot;HASH&quot; #Partition key
},
{
attribute_name: &quot;title&quot;,
key_type: &quot;RANGE&quot; #Sort key
}
],
attribute_definitions: [
{
attribute_name: &quot;year&quot;,
attribute_type: &quot;N&quot;
},
{
attribute_name: &quot;title&quot;,
attribute_type: &quot;S&quot;
},
}
}
],
provisioned_throughput: {
read_capacity_units: 10,
write_capacity_units: 10
begin
result = dynamodb.create_table(params)
puts &quot;Created table. Status: &quot; +
result.table_description.table_status;
rescue Aws::DynamoDB::Errors::ServiceError =&gt; error
puts &quot;Unable to create table:&quot;
puts &quot;#{error.message}&quot;
end
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Step 2: Load Sample Data
Note
• You set the endpoint to indicate that you are creating the table in the downloadable
version of DynamoDB on your computer.
• In the create_table call, you specify table name, primary key attributes, and its data
types.
• The provisioned_throughput parameter is required. However, the downloadable version
of DynamoDB ignores it. (Provisioned throughput is beyond the scope of this exercise.)
2.
To run the program, type the following command:
ruby MoviesCreateTable.rb
To learn more about managing tables, see Working with Tables in DynamoDB (p. 290).
Step 2: Load Sample Data
In this step, you populate the Movies table with sample data.
Topics
• Step 2.1: Download the Sample Data File (p. 167)
• Step 2.2: Load the Sample Data into the Movies Table (p. 167)
You use a sample data ﬁle that contains information about a few thousand movies from the Internet
Movie Database (IMDb). The movie data is in JSON format, as shown in the following example. For each
movie, there is a year, a title, and a JSON map named info.
[
{
},
{
},
&quot;year&quot; : ... ,
&quot;title&quot; : ... ,
&quot;info&quot; : { ... }
&quot;year&quot; : ...,
&quot;title&quot; : ...,
&quot;info&quot; : { ... }
...
]
In the JSON data, note the following:
• The year and title are used as the primary key attribute values for the Movies table.
• You store the rest of the info values in a single attribute called info. This program illustrates how you
can store JSON in a DynamoDB attribute.
The following is an example of movie data:
{
&quot;year&quot; : 2013,
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&quot;title&quot; : &quot;Turn It Down, Or Else!&quot;,
&quot;info&quot; : {
&quot;directors&quot; : [
&quot;Alice Smith&quot;,
&quot;Bob Jones&quot;
],
&quot;release_date&quot; : &quot;2013-01-18T00:00:00Z&quot;,
&quot;rating&quot; : 6.2,
&quot;genres&quot; : [
&quot;Comedy&quot;,
&quot;Drama&quot;
],
&quot;image_url&quot; : &quot;http://ia.media-imdb.com/images/N/
O9ERWAU7FS797AJ7LU8HN09AMUP908RLlo5JF90EWR7LJKQ7@@._V1_SX400_.jpg&quot;,
&quot;plot&quot; : &quot;A rock band plays their music at high volumes, annoying the neighbors.&quot;,
&quot;rank&quot; : 11,
&quot;running_time_secs&quot; : 5215,
&quot;actors&quot; : [
&quot;David Matthewman&quot;,
&quot;Ann Thomas&quot;,
&quot;Jonathan G. Neff&quot;
]
}
}
Step 2.1: Download the Sample Data File
1.
Download the sample data archive: moviedata.zip
2.
3.
Extract the data ﬁle (moviedata.json) from the archive.
Copy and paste the moviedata.json ﬁle into your current directory.
Step 2.2: Load the Sample Data into the Movies Table
After you download the sample data, you can run the following program to populate the Movies table.
1.
Copy and paste the following program into a ﬁle named MoviesLoadData.rb:
require &quot;aws-sdk&quot;
require &quot;json&quot;
Aws.config.update({
region: &quot;us-west-2&quot;,
endpoint: &quot;http://localhost:8000&quot;
})
dynamodb = Aws::DynamoDB::Client.new
tableName = 'Movies'
file = File.read('moviedata.json')
movies = JSON.parse(file)
movies.each{|movie|
params = {
table_name: tableName,
item: movie
}
begin
result = dynamodb.put_item(params)
puts &quot;Added movie: #{movie[&quot;year&quot;]} #{movie[&quot;title&quot;]}&quot;
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}
2.
rescue Aws::DynamoDB::Errors::ServiceError =&gt; error
puts &quot;Unable to add movie:&quot;
puts &quot;#{error.message}&quot;
end
To run the program, type the following command:
ruby MoviesLoadData.rb
Step 3: Create, Read, Update, and Delete an Item
In this step, you perform read and write operations on an item in the Movies table.
To learn more about reading and writing data, see Working with Items in DynamoDB (p. 327).
Topics
• Step 3.1: Create a New Item (p. 168)
• Step 3.2: Read an Item (p. 169)
• Step 3.3: Update an Item (p. 170)
• Step 3.4: Increment an Atomic Counter (p. 171)
• Step 3.5: Update an Item (Conditionally) (p. 172)
• Step 3.6: Delete an Item (p. 173)
Step 3.1: Create a New Item
In this step, you add a new item to the table.
1.
Copy and paste the following program into a ﬁle named MoviesItemOps01.rb:
require &quot;aws-sdk&quot;
Aws.config.update({
region: &quot;us-west-2&quot;,
endpoint: &quot;http://localhost:8000&quot;
})
dynamodb = Aws::DynamoDB::Client.new
tableName = 'Movies'
year = 2015
title = &quot;The Big New Movie&quot;
item = {
year: year,
title: title,
info: {
plot: &quot;Nothing happens at all.&quot;,
rating: 0
}
}
params = {
table_name: &quot;Movies&quot;,
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}
item: item
begin
result = dynamodb.put_item(params)
puts &quot;Added item: #{year} - #{title}&quot;
rescue Aws::DynamoDB::Errors::ServiceError =&gt; error
puts &quot;Unable to add item:&quot;
puts &quot;#{error.message}&quot;
end
Note
The primary key is required. This code adds an item that has primary key (year, title) and
info attributes. The info attribute stores a map that provides more information about the
movie.
2.
To run the program, type the following command:
ruby MoviesItemOps01.rb
Step 3.2: Read an Item
In the previous program, you added the following item to the table:
{
}
year: 2015,
title: &quot;The Big New Movie&quot;,
info: {
plot: &quot;Nothing happens at all.&quot;,
rating: 0
}
You can use the get_item method to read the item from the Movies table. You must specify the primary
key values, so you can read any item from Movies if you know its year and title.
1.
Copy and paste the following program into a ﬁle named MoviesItemOps02.rb:
require &quot;aws-sdk&quot;
Aws.config.update({
region: &quot;us-west-2&quot;,
endpoint: &quot;http://localhost:8000&quot;
})
dynamodb = Aws::DynamoDB::Client.new
tableName = 'Movies'
year = 2015
title = &quot;The Big New Movie&quot;
key = {
year: year,
title: title
}
params = {
table_name: &quot;Movies&quot;,
key: {
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}
}
year: year,
title: title
begin
result = dynamodb.get_item(params)
printf &quot;%i - %s\n%s\n%d\n&quot;,
result.item[&quot;year&quot;],
result.item[&quot;title&quot;],
result.item[&quot;info&quot;][&quot;plot&quot;],
result.item[&quot;info&quot;][&quot;rating&quot;]
rescue Aws::DynamoDB::Errors::ServiceError =&gt; error
puts &quot;Unable to read item:&quot;
puts &quot;#{error.message}&quot;
end
2.
To run the program, type the following command:
ruby MoviesItemOps02.rb
Step 3.3: Update an Item
You can use the update_item method to modify an existing item. You can update values of existing
attributes, add new attributes, or remove attributes.
In this example, you perform the following updates:
• Change the value of the existing attributes (rating, plot).
• Add a new list attribute (actors) to the existing info map.
The item changes from this:
{
}
year: 2015,
title: &quot;The Big New Movie&quot;,
info: {
plot: &quot;Nothing happens at all.&quot;,
rating: 0
}
To the following:
{
}
1.
year: 2015,
title: &quot;The Big New Movie&quot;,
info: {
plot: &quot;Everything happens all at once.&quot;,
rating: 5.5,
actors: [&quot;Larry&quot;, &quot;Moe&quot;, &quot;Curly&quot;]
}
Copy and paste the following program into a ﬁle named MoviesItemOps03.rb:
require &quot;aws-sdk&quot;
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Aws.config.update({
region: &quot;us-west-2&quot;,
endpoint: &quot;http://localhost:8000&quot;
})
dynamodb = Aws::DynamoDB::Client.new
tableName = 'Movies'
year = 2015
title = &quot;The Big New Movie&quot;
params = {
table_name: &quot;Movies&quot;,
key: {
year: year,
title: title
},
update_expression: &quot;set info.rating = :r, info.plot=:p, info.actors=:a&quot;,
expression_attribute_values: {
&quot;:r&quot; =&gt; 5.5,
&quot;:p&quot; =&gt; &quot;Everything happens all at once.&quot;, # value
&lt;Hash,Array,String,Numeric,Boolean,IO,Set,nil&gt;
&quot;:a&quot; =&gt; [&quot;Larry&quot;, &quot;Moe&quot;, &quot;Curly&quot;]
},
return_values: &quot;UPDATED_NEW&quot;
}
begin
result = dynamodb.update_item(params)
puts &quot;Added item: #{year} - #{title}&quot;
rescue Aws::DynamoDB::Errors::ServiceError =&gt; error
puts &quot;Unable to add item:&quot;
puts &quot;#{error.message}&quot;
end
Note
This program uses update_expression to describe all updates you want to perform on the
speciﬁed item.
The return_values parameter instructs DynamoDB to return only the updated attributes
(UPDATED_NEW).
2.
To run the program, type the following command:
ruby MoviesItemOps03.rb
Step 3.4: Increment an Atomic Counter
DynamoDB supports atomic counters, where you use the update_item method to increment or
decrement the value of an existing attribute without interfering with other write requests. (All write
requests are applied in the order in which they are received.)
The following program shows how to increment the rating for a movie. Each time you run it, the
program increments this attribute by one.
1.
Copy and paste the following program into a ﬁle named MoviesItemOps04.rb:
require &quot;aws-sdk&quot;
Aws.config.update({
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region: &quot;us-west-2&quot;,
endpoint: &quot;http://localhost:8000&quot;
})
dynamodb = Aws::DynamoDB::Client.new
tableName = 'Movies'
year = 2015
title = &quot;The Big New Movie&quot;
params = {
table_name: &quot;Movies&quot;,
key: {
year: year,
title: title
},
update_expression: &quot;set info.rating = info.rating + :val&quot;,
expression_attribute_values: {
&quot;:val&quot; =&gt; 1
},
return_values: &quot;UPDATED_NEW&quot;
}
begin
result = dynamodb.update_item(params)
puts &quot;Updated item. ReturnValues are:&quot;
result.attributes[&quot;info&quot;].each do |key, value|
if key == &quot;rating&quot;
puts &quot;#{key}: #{value.to_f}&quot;
else
puts &quot;#{key}: #{value}&quot;
end
end
rescue Aws::DynamoDB::Errors::ServiceError =&gt; error
puts &quot;Unable to update item:&quot;
puts &quot;#{error.message}&quot;
end
2.
To run the program, type the following command:
ruby MoviesItemOps04.rb
Step 3.5: Update an Item (Conditionally)
The following program shows how to use update_item with a condition. If the condition evaluates to
true, the update succeeds; otherwise, the update is not performed.
In this case, the item is updated only if there are more than three actors.
1.
Copy and paste the following program into a ﬁle named MoviesItemOps05.rb:
require &quot;aws-sdk&quot;
Aws.config.update({
region: &quot;us-west-2&quot;,
endpoint: &quot;http://localhost:8000&quot;
})
dynamodb = Aws::DynamoDB::Client.new
tableName = 'Movies'
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year = 2015
title = &quot;The Big New Movie&quot;
params = {
table_name: &quot;Movies&quot;,
key: {
year: year,
title: title
},
update_expression: &quot;remove info.actors[0]&quot;,
condition_expression: &quot;size(info.actors) &gt; :num&quot;,
expression_attribute_values: {
&quot;:num&quot; =&gt; 3
},
return_values: &quot;UPDATED_NEW&quot;
}
begin
result = dynamodb.update_item(params)
puts &quot;Updated item. ReturnValues are:&quot;
result.attributes[&quot;info&quot;].each do |key, value|
if key == &quot;rating&quot;
puts &quot;#{key}: #{value.to_f}&quot;
else
puts &quot;#{key}: #{value}&quot;
end
end
rescue Aws::DynamoDB::Errors::ServiceError =&gt; error
puts &quot;Unable to update item:&quot;
puts &quot;#{error.message}&quot;
end
2.
To run the program, type the following command:
ruby MoviesItemOps05.rb
The program should fail with the following message:
The conditional request failed
This is because the movie has three actors in it, but the condition is checking for greater than three
actors.
3.
Modify the program so that the ConditionExpression looks like this:
condition_expression: &quot;size(info.actors) &gt;= :num&quot;,
The condition is now greater than or equal to 3 instead of greater than 3.
4.
Run the program again. The update_item method should now succeed.
Step 3.6: Delete an Item
You can use the delete_item method to delete one item by specifying its primary key. You can optionally
provide a condition_expression to prevent the item from being deleted if the condition is not met.
In the following example, you try to delete a speciﬁc movie item if its rating is 5 or less.
1.
Copy and paste the following program into a ﬁle named MoviesItemOps06.rb:
require &quot;aws-sdk&quot;
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Aws.config.update({
region: &quot;us-west-2&quot;,
endpoint: &quot;http://localhost:8000&quot;
})
dynamodb = Aws::DynamoDB::Client.new
tableName = 'Movies'
year = 2015
title = &quot;The Big New Movie&quot;
params = {
table_name: &quot;Movies&quot;,
key: {
year: year,
title: title
},
condition_expression: &quot;info.rating &lt;= :val&quot;,
expression_attribute_values: {
&quot;:val&quot; =&gt; 5
}
}
begin
result = dynamodb.delete_item(params)
puts &quot;Deleted item.&quot;
rescue Aws::DynamoDB::Errors::ServiceError =&gt; error
puts &quot;Unable to update item:&quot;
puts &quot;#{error.message}&quot;
end
2.
To run the program, type the following command:
ruby MoviesItemOps06.rb
The program should fail with the following message:
The conditional request failed
This is because the rating for this particular move is greater than 5.
3.
Modify the program to remove the condition:
params = {
table_name: &quot;Movies&quot;,
key: {
year: year,
title: title
}
}
4.
Run the program. Now, the delete succeeds because you removed the condition.
Step 4: Query and Scan the Data
You can use the query method to retrieve data from a table. You must specify a partition key value. The
sort key is optional.
The primary key for the Movies table is composed of the following:
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• year – The partition key. The attribute type is number. • title – The sort key. The attribute type is string.
To ﬁnd all movies released during a year, you need to specify only the year. You can also provide the
title to retrieve a subset of movies based on some condition (on the sort key); for example, to ﬁnd
movies released in 2014 that have a title starting with the letter &quot;A&quot;.
In addition to query, there is also a scan method that can retrieve all of the table data.
To learn more about querying and scanning data, see Working with Queries (p. 410) and Working with
Scans (p. 427), respectively.
Topics
• Step 4.1: Query - All Movies Released in a Year (p. 175)
• Step 4.2: Query - All Movies Released in a Year with Certain Titles (p. 176)
• Step 4.3: Scan (p. 177)
Step 4.1: Query - All Movies Released in a Year
The following program retrieves all movies released in the year 1985.
1.
Copy and paste the following program into a ﬁle named MoviesQuery01.rb:
require &quot;aws-sdk&quot;
Aws.config.update({
region: &quot;us-west-2&quot;,
endpoint: &quot;http://localhost:8000&quot;
})
dynamodb = Aws::DynamoDB::Client.new
tableName = &quot;Movies&quot;
params = {
table_name: tableName,
key_condition_expression: &quot;#yr = :yyyy&quot;,
expression_attribute_names: {
&quot;#yr&quot; =&gt; &quot;year&quot;
},
expression_attribute_values: {
&quot;:yyyy&quot; =&gt; 1985
}
}
puts &quot;Querying for movies from 1985.&quot;;
begin
result = dynamodb.query(params)
puts &quot;Query succeeded.&quot;
result.items.each{|movie|
puts &quot;#{movie[&quot;year&quot;].to_i} #{movie[&quot;title&quot;]}&quot;
}
rescue Aws::DynamoDB::Errors::ServiceError =&gt; error
puts &quot;Unable to query table:&quot;
puts &quot;#{error.message}&quot;
end
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Note
• expression_attribute_names provides name substitution. We use this because year
is a reserved word in DynamoDB—you can't use it directly in any expression, including
KeyConditionExpression. You can use the expression attribute name #yr to address this.
2.
• expression_attribute_values provides value substitution. You use this because you
can't use literals in any expression, including key_condition_expression. You can use the
expression attribute value :yyyy to address this.
To run the program, type the following command:
ruby MoviesItemQuery01.rb
Note
The preceding program shows how to query a table by its primary key attributes. In DynamoDB,
you can optionally create one or more secondary indexes on a table, and query those indexes
in the same way that you query a table. Secondary indexes give your applications additional
ﬂexibility by allowing queries on non-key attributes. For more information, see Improving Data
Access with Secondary Indexes (p. 446).
Step 4.2: Query - All Movies Released in a Year with Certain
Titles
The following program retrieves all movies released in year 1992, with a title beginning with the letter
&quot;A&quot; through the letter &quot;L&quot;.
1.
Copy and paste the following program into a ﬁle named MoviesQuery02.rb:
require &quot;aws-sdk&quot;
Aws.config.update({
region: &quot;us-west-2&quot;,
endpoint: &quot;http://localhost:8000&quot;
})
dynamodb = Aws::DynamoDB::Client.new
tableName = &quot;Movies&quot;
params = {
table_name: tableName,
projection_expression: &quot;#yr, title, info.genres, info.actors[0]&quot;,
key_condition_expression:
&quot;#yr = :yyyy and title between :letter1 and :letter2&quot;,
expression_attribute_names: {
&quot;#yr&quot; =&gt; &quot;year&quot;
},
expression_attribute_values: {
&quot;:yyyy&quot; =&gt; 1992,
&quot;:letter1&quot; =&gt; &quot;A&quot;,
&quot;:letter2&quot; =&gt; &quot;L&quot;
}
}
puts &quot;Querying for movies from 1992 - titles A-L, with genres and lead actor&quot;;
begin
result = dynamodb.query(params)
puts &quot;Query succeeded.&quot;
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Step 4: Query and Scan the Data
result.items.each{|movie|
print &quot;#{movie[&quot;year&quot;].to_i}: #{movie[&quot;title&quot;]} ... &quot;
movie['info']['genres'].each{|gen|
print gen + &quot; &quot;
}
}
print &quot; ... #{movie[&quot;info&quot;][&quot;actors&quot;][0]}\n&quot;
rescue Aws::DynamoDB::Errors::ServiceError =&gt; error
puts &quot;Unable to query table:&quot;
puts &quot;#{error.message}&quot;
end
2.
To run the program, type the following command:
ruby MoviesQuery02.rb
Step 4.3: Scan
The scan method reads every item in the entire table, and returns all the data in the table. You can
provide an optional filter_expression, so that only the items matching your criteria are returned.
However, note that the ﬁlter is only applied after the entire table has been scanned.
The following program scans the Movies table, which contains approximately 5,000 items. The scan
speciﬁes the optional ﬁlter to retrieve only the movies from the 1950s (approximately 100 items), and
discard all the others.
1.
Copy and paste the following program into a ﬁle named MoviesScan.rb:
require &quot;aws-sdk&quot;
Aws.config.update({
region: &quot;us-west-2&quot;,
endpoint: &quot;http://localhost:8000&quot;
})
dynamodb = Aws::DynamoDB::Client.new
tableName = &quot;Movies&quot;
params = {
table_name: tableName,
projection_expression: &quot;#yr, title, info.rating&quot;,
filter_expression: &quot;#yr between :start_yr and :end_yr&quot;,
expression_attribute_names: {&quot;#yr&quot;=&gt; &quot;year&quot;},
expression_attribute_values: {
&quot;:start_yr&quot; =&gt; 1950,
&quot;:end_yr&quot; =&gt; 1959
}
}
puts &quot;Scanning Movies table.&quot;
begin
loop do
result = dynamodb.scan(params)
result.items.each{|movie|
puts &quot;#{movie[&quot;year&quot;].to_i}: &quot; +
&quot;#{movie[&quot;title&quot;]} ... &quot; +
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}
&quot;#{movie[&quot;info&quot;][&quot;rating&quot;].to_f}&quot;
break if result.last_evaluated_key.nil?
end
puts &quot;Scanning for more...&quot;
params[:exclusive_start_key] = result.last_evaluated_key
rescue Aws::DynamoDB::Errors::ServiceError =&gt; error
puts &quot;Unable to scan:&quot;
puts &quot;#{error.message}&quot;
end
In the code, note the following:
• projection_expression speciﬁes the attributes you want in the scan result.
• filter_expression speciﬁes a condition that returns only items that satisfy the condition. All
other items are discarded.
2.
To run the program, type the following command:
ruby MoviesScan.rb
Note
You can also use the scan method with any secondary indexes that you create on the table. For
more information, see Improving Data Access with Secondary Indexes (p. 446).
Step 5: (Optional) Delete the Table
To delete the Movies table:
1.
Copy and paste the following program into a ﬁle named MoviesDeleteTable.rb:
require &quot;aws-sdk&quot;
Aws.config.update({
region: &quot;us-west-2&quot;,
endpoint: &quot;http://localhost:8000&quot;
})
dynamodb = Aws::DynamoDB::Client.new
params = {
table_name: &quot;Movies&quot;
}
begin
result = dynamodb.delete_table(params)
puts &quot;Deleted table.&quot;
rescue Aws::DynamoDB::Errors::ServiceError =&gt; error
puts &quot;Unable to delete table:&quot;
puts &quot;#{error.message}&quot;
end
2.
To run the program, type the following command:
ruby MoviesDeleteTable.rb
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Summary
Summary
In this tutorial, you created the Movies table in the downloadable version of DynamoDB on your
computer and performed basic operations. The downloadable version of DynamoDB is useful during
application development and testing. However, when you're ready to run your application in a
production environment, you must modify your code so that it uses the Amazon DynamoDB web service.
Modifying the Code to Use the DynamoDB Service
To use the Amazon DynamoDB service, you must change the endpoint in your application in order. To do
this, ﬁnd the following lines in the code:
Aws.config.update({
region: &quot;us-west-2&quot;,
endpoint: &quot;http://localhost:8000&quot;
})
Remove the endpoint parameter so that the code looks like this:
Aws.config.update({
region: &quot;us-west-2&quot;
]);
After you remove this line, the code can access the DynamoDB service in the Region speciﬁed by the
region conﬁg value.
Instead of using the version of DynamoDB on your computer, the program uses the DynamoDB service
endpoint in US West (Oregon).
DynamoDB is available in several Regions worldwide. For the complete list, see Regions and Endpoints in
the AWS General Reference. For more information, see the AWS SDK for Ruby Getting Started Guide.
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Overview of AWS SDK Support for DynamoDB
Programming with DynamoDB and
the AWS SDKs
This chapter covers developer-related topics. If you want to run code samples instead, see Running the
Code Samples In This Developer Guide (p. 280).
Topics
• Overview of AWS SDK Support for DynamoDB (p. 180)
• Programmatic Interfaces (p. 182)
• DynamoDB Low-Level API (p. 185)
• Error Handling (p. 189)
• Higher-Level Programming Interfaces for DynamoDB (p. 194)
• Running the Code Samples In This Developer Guide (p. 280)
Overview of AWS SDK Support for DynamoDB
The following diagram provides a high-level overview of DynamoDB application programming with the
AWS SDKs.
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1. You write an application using an AWS SDK for your programming language.
2. Each AWS SDK provides one or more programmatic interfaces for working with DynamoDB. The
speciﬁc interfaces available depend on which programming language and AWS SDK you use.
3. The AWS SDK constructs HTTP(S) requests for use with the low-level DynamoDB API.
4. The AWS SDK sends the request to the DynamoDB endpoint.
5. DynamoDB executes the request. If the request is successful, DynamoDB returns an HTTP 200
response code (OK). If the request is unsuccessful, DynamoDB returns an HTTP error code and an error
message.
6. The AWS SDK processes the response and propagates it back to your application.
Each of the AWS SDKs provides important services to your application, including the following:
• Formatting HTTP(S) requests and serializing request parameters.
• Generating a cryptographic signature for each request.
• Forwarding request to a DynamoDB endpoint and receiving responses from DynamoDB.
• Extracting the results from those responses.
• Implementing basic retry logic in case of errors.
You do not need to write code for any of these tasks.
Note
For more information about AWS SDKs, including installation instructions and documentation,
see Tools for Amazon Web Services.
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Programmatic Interfaces
Programmatic Interfaces
Every AWS SDK provides one or more programmatic interfaces for working with DynamoDB. These
interfaces range from simple low-level DynamoDB wrappers to object-oriented persistence layers. The
available interfaces vary depending on the AWS SDK and programming language that you use.
The following section highlights some of the interfaces available, using the AWS SDK for Java as an
example. (Not all interfaces are available in all AWS SDKs.)
Topics
• Low-Level Interfaces (p. 182)
• Document Interfaces (p. 183)
• Object Persistence Interface (p. 184)
Low-Level Interfaces
Every language-speciﬁc AWS SDK provides a low-level interface for DynamoDB, with methods that
closely resemble low-level DynamoDB API requests.
In some cases, you will need to identify the data types of the attributes using Data Type
Descriptors (p. 188), such as S for string or N for number.
Note
A low-level interface is available in every language-speciﬁc AWS SDK.
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Document Interfaces
The following Java program uses the low-level interface of the AWS SDK for Java. The program issues a
GetItem request for a song in the Music table, and prints the year that the song was released.
The com.amazonaws.services.dynamodbv2.AmazonDynamoDB class implements the DynamoDB low-level
interface.
package com.amazonaws.codesamples;
import java.util.HashMap;
import
import
import
import
import
com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
com.amazonaws.services.dynamodbv2.model.AttributeValue;
com.amazonaws.services.dynamodbv2.model.GetItemRequest;
com.amazonaws.services.dynamodbv2.model.GetItemResult;
public class MusicLowLevelDemo {
public static void main(String[] args) {
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
HashMap&lt;String, AttributeValue&gt; key = new HashMap&lt;String, AttributeValue&gt;();
key.put(&quot;Artist&quot;, new AttributeValue().withS(&quot;No One You Know&quot;));
key.put(&quot;SongTitle&quot;, new AttributeValue().withS(&quot;Call Me Today&quot;));
GetItemRequest request = new GetItemRequest()
.withTableName(&quot;Music&quot;)
.withKey(key);
}
}
try {
GetItemResult result = client.getItem(request);
if (result &amp;&amp; result.getItem() != null) {
AttributeValue year = result.getItem().get(&quot;Year&quot;);
System.out.println(&quot;The song was released in &quot; + year.getN());
} else {
System.out.println(&quot;No matching song was found&quot;);
}
} catch (Exception e) {
System.err.println(&quot;Unable to retrieve data: &quot;);
System.err.println(e.getMessage());
}
Document Interfaces
Many AWS SDKs provide a document interface, allowing you to perform data plane operations (create,
read, update, delete) on tables and indexes. With a document interface, you do not need to specify Data
Type Descriptors (p. 188); the data types are implied by the semantics of the data itself. These AWS
SDKs also provide methods to easily convert JSON documents to and from native DynamoDB data types.
Note
Document interfaces are available in the AWS SDKs for Java, .NET, Node.js, and JavaScript in the
Browser.
The following Java program uses the document interface of the AWS SDK for Java. The program creates
a Table object that represents the Music table, and then asks that object to use GetItem to retrieve a
song. The program then prints the year that the song was released.
The com.amazonaws.services.dynamodbv2.document.DynamoDB class implements the DynamoDB
document interface. Note how DynamoDB acts as a wrapper around the low-level client (AmazonDynamoDB).
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Object Persistence Interface
package com.amazonaws.codesamples.gsg;
import
import
import
import
import
com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
com.amazonaws.services.dynamodbv2.document.DynamoDB;
com.amazonaws.services.dynamodbv2.document.GetItemOutcome;
com.amazonaws.services.dynamodbv2.document.Table;
public class MusicDocumentDemo {
public static void main(String[] args) {
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
DynamoDB docClient = new DynamoDB(client);
Table table = docClient.getTable(&quot;Music&quot;);
GetItemOutcome outcome = table.getItemOutcome(
&quot;Artist&quot;, &quot;No One You Know&quot;,
&quot;SongTitle&quot;, &quot;Call Me Today&quot;);
int year = outcome.getItem().getInt(&quot;Year&quot;);
System.out.println(&quot;The song was released in &quot; + year);
}
}
Object Persistence Interface
Some AWS SDKs provide an object persistence interface where you do not directly perform data plane
operations. Instead, you create objects that represent items in DynamoDB tables and indexes, and
interact only with those objects. This allows you to write object-centric code, rather than databasecentric code.
Note
Object persistence interfaces are available in the AWS SDKs for Java and .NET. For more
information, see Higher-Level Programming Interfaces for DynamoDB (p. 194).
The following Java program uses DynamoDBMapper, the object persistence interface of the AWS SDK for
Java. The MusicItem class represents an item the Music table.
package com.amazonaws.codesamples;
import
import
import
import
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBAttribute;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBHashKey;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBRangeKey;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBTable;
@DynamoDBTable(tableName=&quot;Music&quot;)
public class MusicItem {
private String artist;
private String songTitle;
private String albumTitle;
private int year;
@DynamoDBHashKey(attributeName=&quot;Artist&quot;)
public String getArtist() { return artist;}
public void setArtist(String artist) {this.artist = artist;}
@DynamoDBRangeKey(attributeName=&quot;SongTitle&quot;)
public String getSongTitle() { return songTitle;}
public void setSongTitle(String songTitle) {this.songTitle = songTitle;}
@DynamoDBAttribute(attributeName = &quot;AlbumTitle&quot;)
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public String getAlbumTitle() { return albumTitle;}
public void setAlbumTitle(String albumTitle) {this.albumTitle = albumTitle;}
}
@DynamoDBAttribute(attributeName = &quot;Year&quot;)
public int getYear() { return year; }
public void setYear(int year) { this.year = year; }
You can then instantiate a MusicItem object, and retrieve a song using the load() method of
DynamoDBMapper. The program then prints the year that the song was released.
The com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBMapper class implements the
DynamoDB object persistence interface. Note how DynamoDBMapper acts as a wrapper around the lowlevel client (AmazonDynamoDB).
package com.amazonaws.codesamples;
import com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
import com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
import com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBMapper;
public class MusicMapperDemo {
public static void main(String[] args) {
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
DynamoDBMapper mapper = new DynamoDBMapper(client);
MusicItem keySchema = new MusicItem();
keySchema.setArtist(&quot;No One You Know&quot;);
keySchema.setSongTitle(&quot;Call Me Today&quot;);
try {
MusicItem result = mapper.load(keySchema);
if (result != null) {
System.out.println(
&quot;The song was released in &quot;+ result.getYear());
} else {
System.out.println(&quot;No matching song was found&quot;);
}
} catch (Exception e) {
System.err.println(&quot;Unable to retrieve data: &quot;);
System.err.println(e.getMessage());
}
}
}
DynamoDB Low-Level API
Topics
• Request Format (p. 187)
• Response Format (p. 187)
• Data Type Descriptors (p. 188)
• Numeric Data (p. 188)
• Binary Data (p. 189)
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DynamoDB Low-Level API
The DynamoDB low-level API is the protocol-level interface for Amazon DynamoDB. At this level, every
HTTP(S) request must be correctly formatted and carry a valid digital signature.
The AWS SDKs construct low-level DynamoDB API requests on your behalf and process the responses
from DynamoDB. This lets you focus on your application logic, instead of low-level details. However, you
can still beneﬁt from a basic knowledge of how the low-level DynamoDB API works.
For more information about the low-level DynamoDB API, see Amazon DynamoDB API Reference.
Note
DynamoDB Streams has its own low-level API, which is separate from that of DynamoDB and is
fully supported by the AWS SDKs.
For more information, see Capturing Table Activity with DynamoDB Streams (p. 518). For the
low-level DynamoDB Streams API, see the Amazon DynamoDB Streams API Reference
The low-level DynamoDB API uses JavaScript Object Notation (JSON) as a wire protocol format. JSON
presents data in a hierarchy, so that both data values and data structure are conveyed simultaneously.
Name-value pairs are deﬁned in the format name:value. The data hierarchy is deﬁned by nested brackets
of name-value pairs.
DynamoDB uses JSON only as a transport protocol, not as a storage format. The AWS SDKs use JSON
to send data to DynamoDB, and DynamoDB responds with JSON, but DynamoDB does not store data
persistently in JSON format.
Note
For more information about JSON, see the Introducing JSON at the JSON.org website.
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Request Format
Request Format
The DynamoDB low-level API accepts HTTP(S) POST requests as input. The AWS SDKs construct these
requests for you.
Suppose that you have a table named Pets, with a key schema consisting of AnimalType (partition key)
and Name (sort key). Both of these attributes are of type string. To retrieve an item from Pets, the AWS
SDK constructs a request as shown following:
POST / HTTP/1.1
Host: dynamodb.&lt;region&gt;.&lt;domain&gt;;
Accept-Encoding: identity
Content-Length: &lt;PayloadSizeBytes&gt;
User-Agent: &lt;UserAgentString&gt;
Content-Type: application/x-amz-json-1.0
Authorization: AWS4-HMAC-SHA256 Credential=&lt;Credential&gt;, SignedHeaders=&lt;Headers&gt;,
Signature=&lt;Signature&gt;
X-Amz-Date: &lt;Date&gt;
X-Amz-Target: DynamoDB_20120810.GetItem
{
}
&quot;TableName&quot;: &quot;Pets&quot;,
&quot;Key&quot;: {
&quot;AnimalType&quot;: {&quot;S&quot;: &quot;Dog&quot;},
&quot;Name&quot;: {&quot;S&quot;: &quot;Fido&quot;}
}
Note the following about this request:
• The Authorization header contains information required for DynamoDB to authenticate the request.
For more information, see Signing AWS API Requests and Signature Version 4 Signing Process in the
Amazon Web Services General Reference.
• The X-Amz-Target header contains the name of a DynamoDB operation: GetItem. (This is also
accompanied by the low-level API version, in this case 20120810.)
• The payload (body) of the request contains the parameters for the operation, in JSON format. For the
GetItem operation, the parameters are TableName and Key.
Response Format
Upon receipt of the request, DynamoDB processes it and returns a response. For the request shown
above, the HTTP(S) response payload contains the results from the operation, as in this example:
HTTP/1.1 200 OK
x-amzn-RequestId: &lt;RequestId&gt;
x-amz-crc32: &lt;Checksum&gt;
Content-Type: application/x-amz-json-1.0
Content-Length: &lt;PayloadSizeBytes&gt;
Date: &lt;Date&gt;
{
&quot;Item&quot;: {
&quot;Age&quot;: {&quot;N&quot;: &quot;8&quot;},
&quot;Colors&quot;: {
&quot;L&quot;: [
{&quot;S&quot;: &quot;White&quot;},
{&quot;S&quot;: &quot;Brown&quot;},
{&quot;S&quot;: &quot;Black&quot;}
]
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Data Type Descriptors
}
}
},
&quot;Name&quot;: {&quot;S&quot;: &quot;Fido&quot;},
&quot;Vaccinations&quot;: {
&quot;M&quot;: {
&quot;Rabies&quot;: {
&quot;L&quot;: [
{&quot;S&quot;: &quot;2009-03-17&quot;},
{&quot;S&quot;: &quot;2011-09-21&quot;},
{&quot;S&quot;: &quot;2014-07-08&quot;}
]
},
&quot;Distemper&quot;: {&quot;S&quot;: &quot;2015-10-13&quot;}
}
},
&quot;Breed&quot;: {&quot;S&quot;: &quot;Beagle&quot;},
&quot;AnimalType&quot;: {&quot;S&quot;: &quot;Dog&quot;}
At this point, the AWS SDK returns the response data to your application for further processing.
Note
If DynamoDB cannot process a request, it returns an HTTP error code and message. The AWS
SDK propagates these to your application, in the form of exceptions. For more information, see
Error Handling (p. 189).
Data Type Descriptors
The low-level DynamoDB API protocol requires each attribute to be accompanied by a data type
descriptor. Data type descriptors are tokens that tell DynamoDB how to interpret each attribute.
The examples in Request Format (p. 187) and Response Format (p. 187) show examples of how data
type descriptors are used. The GetItem request speciﬁes S for the Pets key schema attributes (AnimalType
and Name), which are of type string. The GetItem response contains a Pets item with attributes of type
string (S), number (N), map (M), and list (L).
The following is a complete list of DynamoDB data type descriptors:
• S – String
• N – Number
• B – Binary
• BOOL – Boolean
• NULL – Null
• M – Map
• L – List
• SS – String Set
• NS – Number Set
• BS – Binary Set
Note
For detailed descriptions of DynamoDB data types, see Data Types (p. 12).
Numeric Data
Diﬀerent programming languages oﬀer diﬀerent levels of support for JSON. In some cases, you might
decide to use a third party library for validating and parsing JSON documents.
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Binary Data
Some third party libraries build upon the JSON number type, providing their own types such as int, long
or double. However, the native number data type in DynamoDB does not map exactly to these other
data types, so these type distinctions can cause conﬂicts. In addition, many JSON libraries do not handle
ﬁxed-precision numeric values, and they automatically infer a double data type for digit sequences that
contain a decimal point.
To solve these problems, DynamoDB provides a single numeric type with no data loss. To avoid
unwanted implicit conversions to a double value, DynamoDB uses strings for the data transfer of numeric
values. This approach provides ﬂexibility for updating attribute values while maintaining proper sorting
semantics, such as putting the values &quot;01&quot;, &quot;2&quot;, and &quot;03&quot; in the proper sequence.
If number precision is important to your application, you should convert numeric values to strings before
you pass them to DynamoDB.
Binary Data
DynamoDB supports binary attributes. However, JSON does not natively support encoding binary
data. To send binary data in a request, you will need to encode it in Base64 format. Upon receiving the
request, DynamoDB decodes the Base64 data back to binary.
The Base64 encoding scheme used by DynamoDB is described at RFC 4648 at the Internet Engineering
Task Force (IETF) website.
Error Handling
This section describes runtime errors and how to handle them. It also describes error messages and codes
that are speciﬁc to DynamoDB.
Topics
• Error Components (p. 189)
• Error Messages and Codes (p. 190)
• Error Handling in Your Application (p. 192)
• Error Retries and Exponential Backoﬀ (p. 193)
• Batch Operations and Error Handling (p. 194)
Error Components
When your program sends a request, DynamoDB attempts to process it. If the request is successful,
DynamoDB returns an HTTP success status code (200 OK), along with the results from the requested
operation.
If the request is unsuccessful, DynamoDB returns an error. Each error has three components:
• An HTTP status code (such as 400).
• An exception name (such as ResourceNotFoundException).
• An error message (such as Requested resource not found: Table: tablename not found).
The AWS SDKs take care of propagating errors to your application, so that you can take
appropriate action. For example, in a Java program, you can write try-catch logic to handle a
ResourceNotFoundException.
If you are not using an AWS SDK, you will need to parse the content of the low-level response from
DynamoDB. The following is an example of such a response:
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Error Messages and Codes
HTTP/1.1 400 Bad Request
x-amzn-RequestId: LDM6CJP8RMQ1FHKSC1RBVJFPNVV4KQNSO5AEMF66Q9ASUAAJG
Content-Type: application/x-amz-json-1.0
Content-Length: 240
Date: Thu, 15 Mar 2012 23:56:23 GMT
{&quot;__type&quot;:&quot;com.amazonaws.dynamodb.v20120810#ResourceNotFoundException&quot;,
&quot;message&quot;:&quot;Requested resource not found: Table: tablename not found&quot;}
Error Messages and Codes
The following is a list of exceptions returned by DynamoDB, grouped by HTTP status code. If OK to retry?
is Yes, you can submit the same request again. If OK to retry? is No, you will need to ﬁx the problem on
the client side before you submit a new request.
HTTP Status Code 400
An HTTP 400 status code indicates a problem with your request, such as authentication failure, missing
required parameters, or exceeding a table's provisioned throughput. You will have to ﬁx the issue in your
application before submitting the request again.
AccessDeniedException
Message: Access denied.
The client did not correctly sign the request. If you are using an AWS SDK, requests are signed for
you automatically; otherwise, go to the Signature Version 4 Signing Process in the AWS General
Reference.
OK to retry? No
ConditionalCheckFailedException
Message: The conditional request failed.
You speciﬁed a condition that evaluated to false. For example, you might have tried to perform a
conditional update on an item, but the actual value of the attribute did not match the expected
value in the condition.
OK to retry? No
IncompleteSignatureException
Message: The request signature does not conform to AWS standards.
The request signature did not include all of the required components. If you are using an AWS SDK,
requests are signed for you automatically; otherwise, go to the Signature Version 4 Signing Process
in the AWS General Reference.
OK to retry? No
ItemCollectionSizeLimitExceededException
Message: Collection size exceeded.
For a table with a local secondary index, a group of items with the same partition key value has
exceeded the maximum size limit of 10 GB. For more information on item collections, see Item
Collections (p. 492).
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OK to retry? Yes
LimitExceededException
Message: Too many operations for a given subscriber.
There are too many concurrent control plane operations. The cumulative number of tables and
indexes in the CREATING, DELETING or UPDATING state cannot exceed 10.
OK to retry? Yes
MissingAuthenticationTokenException
Message: Request must contain a valid (registered) AWS Access Key ID.
The request did not include the required authorization header, or it was malformed. See DynamoDB
Low-Level API (p. 185).
OK to retry? No
ProvisionedThroughputExceededException
Message: You exceeded your maximum allowed provisioned throughput for a table or for one or more
global secondary indexes. To view performance metrics for provisioned throughput vs. consumed
throughput, open the Amazon CloudWatch console.
Example: Your request rate is too high. The AWS SDKs for DynamoDB automatically retry requests
that receive this exception. Your request is eventually successful, unless your retry queue is too large
to ﬁnish. Reduce the frequency of requests, using Error Retries and Exponential Backoﬀ (p. 193).
OK to retry? Yes
ResourceInUseException
Message: The resource which you are attempting to change is in use.
Example: You tried to recreate an existing table, or delete a table currently in the CREATING state.
OK to retry? No
ResourceNotFoundException
Message: Requested resource not found.
Example: Table which is being requested does not exist, or is too early in the CREATING state.
OK to retry? No
ThrottlingException
Message: Rate of requests exceeds the allowed throughput.
This exception might be returned if you perform any of the following operations too rapidly:
CreateTable; UpdateTable; DeleteTable.
OK to retry? Yes
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UnrecognizedClientException
Message: The Access Key ID or security token is invalid.
The request signature is incorrect. The most likely cause is an invalid AWS access key ID or secret key.
OK to retry? Yes
ValidationException
Message: Varies, depending upon the speciﬁc error(s) encountered
This error can occur for several reasons, such as a required parameter that is missing, a value that is
out range, or mismatched data types. The error message contains details about the speciﬁc part of
the request that caused the error.
OK to retry? No
HTTP Status Code 5xx
An HTTP 5xx status code indicates a problem that must be resolved by Amazon Web Services. This might
be a transient error in which case you can retry your request until it succeeds. Otherwise, go to the AWS
Service Health Dashboard to see if there are any operational issues with the service.
Internal Server Error (HTTP 500)
DynamoDB could not process your request.
OK to retry? Yes
Note
You may encounter Internal Server Errors while working with items. These are expected
during the lifetime of a table. Any failed requests can be retried immediately.
Service Unavailable (HTTP 503)
DynamoDB is currently unavailable. (This should be a temporary state.)
OK to retry? Yes
Error Handling in Your Application
For your application to run smoothly, you will need to add logic to catch and respond to errors. Typical
approaches include using try-catch blocks or an if-then statements.
The AWS SDKs perform their own retries and error checking. If you encounter an error while using one of
the AWS SDKs, the error code and description can help you troubleshoot it.
You should also see a Request ID in the response. The Request ID can be helpful if you need to work
with AWS Support to diagnose an issue.
The following Java code snippet attempts to delete an item from a DynamoDB table, and performs
rudimentary error handling. (In this case, it simply informs the user that the request failed).
Table table = dynamoDB.getTable(&quot;Movies&quot;);
try {
Item item = table.getItem(&quot;year&quot;, 1978, &quot;title&quot;, &quot;Superman&quot;);
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if (item != null) {
System.out.println(&quot;Result: &quot; + item);
} else {
//No such item exists in the table
System.out.println(&quot;Item not found&quot;);
}
} catch (AmazonServiceException ase) {
System.err.println(&quot;Could not complete operation&quot;);
System.err.println(&quot;Error Message: &quot; + ase.getMessage());
System.err.println(&quot;HTTP Status:
&quot; + ase.getStatusCode());
System.err.println(&quot;AWS Error Code: &quot; + ase.getErrorCode());
System.err.println(&quot;Error Type:
&quot; + ase.getErrorType());
System.err.println(&quot;Request ID:
&quot; + ase.getRequestId());
} catch (AmazonClientException ace) {
System.err.println(&quot;Internal error occured communicating with DynamoDB&quot;);
System.out.println(&quot;Error Message: &quot; + ace.getMessage());
}
In this code snippet, the try-catch construct handles two diﬀerent kinds of exceptions:
• AmazonServiceException—thrown if the client request was correctly transmitted to DynamoDB, but
DynamoDB was unable to process the request and returned an error response instead.
• AmazonClientException—thrown if the client was unable to get a response from a service, or if the
client was unable to parse the response from a service.
Error Retries and Exponential Backoﬀ
Numerous components on a network, such as DNS servers, switches, load balancers, and others can
generate errors anywhere in the life of a given request. The usual technique for dealing with these error
responses in a networked environment is to implement retries in the client application. This technique
increases the reliability of the application and reduces operational costs for the developer.
Each AWS SDK implements retry logic, automatically. You can modify the retry parameters to your
needs. For example, consider a Java application that requires a fail-fast strategy, with no retries allowed
in case of an error. With the AWS SDK for Java, you could use the ClientConfiguration class and
provide a maxErrorRetry value of 0 to turn oﬀ the retries. For more information, see the AWS SDK
documentation for your programming language
If you're not using an AWS SDK, you should retry original requests that receive server
errors (5xx). However, client errors (4xx, other than a ThrottlingException or a
ProvisionedThroughputExceededException) indicate you need to revise the request itself to correct the
problem before trying again.
In addition to simple retries, each AWS SDK implements exponential backoﬀ algorithm for better ﬂow
control. The concept behind exponential backoﬀ is to use progressively longer waits between retries
for consecutive error responses. For example, up to 50 milliseconds before the ﬁrst retry, up to 100
milliseconds before the second, up to 200 milliseconds before third, and so on. However, after a minute,
if the request has not succeeded, the problem might be the request size exceeding your provisioned
throughput, and not the request rate. Set the maximum number of retries to stop around one minute. If
the request is not successful, investigate your provisioned throughput options. For more information, see
Best Practices for Tables (p. 659).
Note
The AWS SDKs implement automatic retry logic and exponential backoﬀ.
Most exponential backoﬀ algorithms use jitter (randomized delay) to prevent successive collisions.
Because you aren't trying to avoid such collisions in these cases, you do not need to use this random
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number. However, if you use concurrent clients, jitter can help your requests succeed faster. For more
information, see the blog post for Exponential Backoﬀ and Jitter.
Batch Operations and Error Handling
The DynamoDB low-level API supports batch operations for reads and writes. BatchGetItem reads items
from one or more tables, and BatchWriteItem puts or deletes items in one or more tables. These batch
operations are implemented as wrappers around other non-batch DynamoDB operations. In other
words, BatchGetItem invokes GetItem once for each item in the batch. Similarly,BatchWriteItem invokes
DeleteItem or PutItem, as appropriate, for each item in the batch.
A batch operation can tolerate the failure of individual requests in the batch. For example, consider a
BatchGetItem request to read ﬁve items. Even if some of the underlying GetItem requests fail, this will
not cause the entire BatchGetItem operation to fail. On the other hand, if all of the ﬁve reads operations
fail, then the entire BatchGetItem will fail.
The batch operations return information about individual requests that fail, so that you can diagnose the
problem and retry the operation. For BatchGetItem, the tables and primary keys in question are returned
in the UnprocessedKeys parameter of the request. For BatchWriteItem, similar information is returned in
UnprocessedItems.
The most likely cause of a failed read or a failed write is throttling. For BatchGetItem, one or more of the
tables in the batch request does not have enough provisioned read capacity to support the operation.
For BatchWriteItem, one or more of the tables does not have enough provisioned write capacity.
If DynamoDB returns any unprocessed items, you should retry the batch operation on those items.
However, we strongly recommend that you use an exponential backoﬀ algorithm. If you retry the batch
operation immediately, the underlying read or write requests can still fail due to throttling on the
individual tables. If you delay the batch operation using exponential backoﬀ, the individual requests in
the batch are much more likely to succeed.
Higher-Level Programming Interfaces for
DynamoDB
The AWS SDKs provide applications with low-level interfaces for working with Amazon DynamoDB.
These client-side classes and methods correspond directly to the low-level DynamoDB API. However,
many developers experience a sense of disconnect, or &quot;impedance mismatch&quot;, when they need to map
complex data types to items in a database table. With a low-level database interface, developers must
write methods for reading or writing object data to database tables, and vice-versa. The amount of extra
code required for each combination of object type and database table can seem overwhelming.
To simplify development, the AWS SDKs for Java and .NET provide additional interfaces with higher
levels of abstraction. The higher-level interfaces for DynamoDB let you deﬁne the relationships between
objects in your program and the database tables that store those objects' data. After you deﬁne this
mapping, you call simple object methods such as save, load, or delete, and the underlying low-level
DynamoDB operations are automatically invoked on your behalf. This allows you to write object-centric
code, rather than database-centric code.
The higher-level programming interfaces for DynamoDB are available in the AWS SDKs for Java
and .NET.
Java
• Java: DynamoDBMapper (p. 195)
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.NET
• .NET: Document Model (p. 232)
• .NET: Object Persistence Model (p. 253)
Java: DynamoDBMapper
Topics
• Supported Data Types (p. 197)
• Java Annotations for DynamoDB (p. 198)
• The DynamoDBMapper Class (p. 202)
• Optional Conﬁguration Settings for DynamoDBMapper (p. 209)
• Example: CRUD Operations (p. 210)
• Example: Batch Write Operations (p. 212)
• Example: Query and Scan (p. 218)
• Optimistic Locking With Version Number (p. 227)
• Mapping Arbitrary Data (p. 229)
The AWS SDK for Java provides a DynamoDBMapper class, allowing you to map your client-side classes to
DynamoDB tables. To use DynamoDBMapper, you deﬁne the relationship between items in a DynamoDB
table and their corresponding object instances in your code. The DynamoDBMapper class enables you to
access your tables, perform various create, read, update and delete (CRUD) operations, and execute
queries.
Note
The DynamoDBMapper class does not allow you to create, update, or delete tables. To perform
those tasks, use the low-level SDK for Java interface instead. For more information, see Working
with Tables: Java (p. 316).
The SDK for Java provides a set of annotation types, so that you can map your classes to tables. For
example, consider a ProductCatalog table that has Id as the partition key.
ProductCatalog(Id, ...)
You can map a class in your client application to the ProductCatalog table as shown in the following
Java code. This code snippet deﬁnes a plain old Java object (POJO) named CatalogItem, which uses
annotations to map object ﬁelds to DynamoDB attribute names:
Example
package com.amazonaws.codesamples;
import java.util.Set;
import
import
import
import
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBAttribute;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBHashKey;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBIgnore;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBTable;
@DynamoDBTable(tableName=&quot;ProductCatalog&quot;)
public class CatalogItem {
private Integer id;
private String title;
private String ISBN;
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private Set&lt;String&gt; bookAuthors;
private String someProp;
@DynamoDBHashKey(attributeName=&quot;Id&quot;)
public Integer getId() { return id;}
public void setId(Integer id) {this.id = id;}
@DynamoDBAttribute(attributeName=&quot;Title&quot;)
public String getTitle() {return title; }
public void setTitle(String title) { this.title = title; }
@DynamoDBAttribute(attributeName=&quot;ISBN&quot;)
public String getISBN() { return ISBN; }
public void setISBN(String ISBN) { this.ISBN = ISBN; }
@DynamoDBAttribute(attributeName = &quot;Authors&quot;)
public Set&lt;String&gt; getBookAuthors() { return bookAuthors; }
public void setBookAuthors(Set&lt;String&gt; bookAuthors) { this.bookAuthors = bookAuthors; }
}
@DynamoDBIgnore
public String getSomeProp() { return someProp;}
public void setSomeProp(String someProp) {this.someProp = someProp;}
In the preceding code, the @DynamoDBTable annotation maps the CatalogItem class to the
ProductCatalog table. You can store individual class instances as items in the table. In the class
deﬁnition, the @DynamoDBHashKey annotation maps the Id property to the primary key.
By default, the class properties map to the same name attributes in the table. The properties Title and
ISBN map to the same name attributes in the table.
The @DynamoDBAttribute annotation is optional when the name of the DynamoDB attribute matches
the name of the property declared in the class. When they diﬀer, use this annotation with the
attributeName() parameter to specify which DynamoDB attribute this property corresponds to. In
the preceding example, the @DynamoDBAttribute annotation is added to each property to ensure that
the property names match exactly with the tables created in Creating Tables and Loading Sample
Data (p. 280), and to be consistent with the attribute names used in other code examples in this guide.
Your class deﬁnition can have properties that don't map to any attributes in the table. You identify these
properties by adding the @DynamoDBIgnore annotation. In the preceding example, the SomeProp property
is marked with the @DynamoDBIgnore annotation. When you upload a CatalogItem instance to the table,
your DynamoDBMapper instance does not include SomeProp property. In addition, the mapper does not
return this attribute when you retrieve an item from the table.
After you have deﬁned your mapping class, you can use DynamoDBMapper methods to write an instance
of that class to a corresponding item in the Catalog table. The following code snippet demonstrates this
technique:
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
DynamoDBMapper mapper = new DynamoDBMapper(client);
CatalogItem item = new CatalogItem();
item.setId(102);
item.setTitle(&quot;Book 102 Title&quot;);
item.setISBN(&quot;222-2222222222&quot;);
item.setBookAuthors(new HashSet&lt;String&gt;(Arrays.asList(&quot;Author 1&quot;, &quot;Author 2&quot;)));
item.setSomeProp(&quot;Test&quot;);
mapper.save(item);
The following code snippet shows how to retrieve the item and access some of its attributes:
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CatalogItem partitionKey = new CatalogItem();
partitionKey.setId(102);
DynamoDBQueryExpression&lt;CatalogItem&gt; queryExpression = new
DynamoDBQueryExpression&lt;CatalogItem&gt;()
.withHashKeyValues(partitionKey);
List&lt;CatalogItem&gt; itemList = mapper.query(CatalogItem.class, queryExpression);
for (int i = 0; i &lt; itemList.size(); i++) {
System.out.println(itemList.get(i).getTitle());
System.out.println(itemList.get(i).getBookAuthors());
}
DynamoDBMapper oﬀers an intuitive, natural way of working with DynamoDB data within Java. It also
provides a number of built-in features such as optimistic locking, auto-generated partition key and sort
key values, and object versioning.
Supported Data Types
This section describes the supported primitive Java data types, collections, and arbitrary data types.
DynamoDB supports the following primitive data types and primitive wrapper classes.
• String
• Boolean, boolean
• Byte, byte
• Date (as ISO8601 millisecond-precision string, shifted to UTC)
• Calendar (as ISO8601 millisecond-precision string, shifted to UTC)
• Long, long
• Integer, int
• Double, double
• Float, float
• BigDecimal
• BigInteger
DynamoDB supports the Java Set collection types. If your mapped collection property is not a Set, then
an exception is thrown.
The following table summarizes how the preceding Java types map to the DynamoDB types.
Java type
DynamoDB type
All number types
N (number type)
Strings
S (string type)
Boolean
N (number type), 0 or 1.
Alternatively, you can use
@DynamoDBNativeBooleanType to map a Java
Boolean to the DynamoDB BOOL data type. For
more information, see Java Annotations for
DynamoDB (p. 198).)
ByteBuﬀer
B (binary type)
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Java type
DynamoDB type
Date
S (string type). The Date values are stored as
Set collection types
SS (string set) type, NS (number set) type, or BS
ISO-8601 formatted strings.
(binary set) type.
The DynamoDBTypeConverter interface lets you map your own arbitrary data types to a data type that is
natively supported by DynamoDB. For more information, see Mapping Arbitrary Data (p. 229).
Java Annotations for DynamoDB
This section describes the annotations that are available for mapping your classes and properties to
tables and attributes.
For the corresponding Javadoc documentation, see Annotation Types Summary in the AWS SDK for Java
API Reference.
Note
In the following annotations, only DynamoDBTable and the DynamoDBHashKey are required.
Topics
• DynamoDBAttribute (p. 198)
• DynamoDBAutoGeneratedKey (p. 198)
• DynamoDBDocument (p. 199)
• DynamoDBHashKey (p. 200)
• DynamoDBIgnore (p. 200)
• DynamoDBIndexHashKey (p. 201)
• DynamoDBIndexRangeKey (p. 201)
• DynamoDBRangeKey (p. 201)
• DynamoDBTable (p. 201)
• DynamoDBTypeConverted (p. 202)
• DynamoDBTyped (p. 202)
• DynamoDBVersionAttribute (p. 202)
DynamoDBAttribute
Maps a property to a table attribute. By default, each class property maps to an item attribute with the
same name. However, if the names are not the same, you can use this annotation to map a property to
the attribute. In the following Java snippet, the DynamoDBAttribute maps the BookAuthors property to
the Authors attribute name in the table.
@DynamoDBAttribute(attributeName = &quot;Authors&quot;)
public List&lt;String&gt; getBookAuthors() { return BookAuthors; }
public void setBookAuthors(List&lt;String&gt; BookAuthors) { this.BookAuthors = BookAuthors; }
The DynamoDBMapper uses Authors as the attribute name when saving the object to the table.
DynamoDBAutoGeneratedKey
Marks a partition key or sort key property as being auto-generated. DynamoDBMapper will generate a
random UUID when saving these attributes. Only String properties can be marked as auto-generated
keys.
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The following snippet demonstrates using auto-generated keys.
@DynamoDBTable(tableName=&quot;AutoGeneratedKeysExample&quot;)
public class AutoGeneratedKeys {
private String id;
private String payload;
@DynamoDBHashKey(attributeName = &quot;Id&quot;)
@DynamoDBAutoGeneratedKey
public String getId() { return id; }
public void setId(String id) { this.id = id; }
@DynamoDBAttribute(attributeName=&quot;payload&quot;)
public String getPayload() { return this.payload; }
public void setPayload(String payload) { this.payload = payload; }
public static void saveItem() {
AutoGeneratedKeys obj = new AutoGeneratedKeys();
obj.setPayload(&quot;abc123&quot;);
// id field is null at this point
DynamoDBMapper mapper = new DynamoDBMapper(dynamoDBClient);
mapper.save(obj);
}
}
System.out.println(&quot;Object was saved with id &quot; + obj.getId());
DynamoDBDocument
Indicates that a class can be serialized as a DynamoDB document.
For example, suppose you wanted to map a JSON document to a DynamoDB attribute of type Map (M).
The following code snippet deﬁnes an item containing a nested attribute (Pictures) of type Map.
public class ProductCatalogItem {
private Integer id; //partition key
private Pictures pictures;
/* ...other attributes omitted... */
@DynamoDBHashKey(attributeName=&quot;Id&quot;)
public Integer getId() { return id;}
public void setId(Integer id) {this.id = id;}
@DynamoDBAttribute(attributeName=&quot;Pictures&quot;)
public Pictures getPictures() { return pictures;}
public void setPictures(Pictures pictures) {this.pictures = pictures;}
// Additional properties go here.
@DynamoDBDocument
public static class Pictures {
private String frontView;
private String rearView;
private String sideView;
@DynamoDBAttribute(attributeName = &quot;FrontView&quot;)
public String getFrontView() { return frontView; }
public void setFrontView(String frontView) { this.frontView = frontView; }
@DynamoDBAttribute(attributeName = &quot;RearView&quot;)
public String getRearView() { return rearView; }
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public void setRearView(String rearView) { this.rearView = rearView; }
@DynamoDBAttribute(attributeName = &quot;SideView&quot;)
public String getSideView() { return sideView; }
public void setSideView(String sideView) { this.sideView = sideView; }
}
}
You could then save a new ProductCatalog item, with Pictures, as shown in the following snippet:
ProductCatalogItem item = new ProductCatalogItem();
Pictures pix = new Pictures();
pix.setFrontView(&quot;http://example.com/products/123_front.jpg&quot;);
pix.setRearView(&quot;http://example.com/products/123_rear.jpg&quot;);
pix.setSideView(&quot;http://example.com/products/123_left_side.jpg&quot;);
item.setPictures(pix);
item.setId(123);
mapper.save(item);
The resulting ProductCatalog item would look like this (in JSON format):
{
}
&quot;Id&quot; : 123
&quot;Pictures&quot; : {
&quot;SideView&quot; : &quot;http://example.com/products/123_left_side.jpg&quot;,
&quot;RearView&quot; : &quot;http://example.com/products/123_rear.jpg&quot;,
&quot;FrontView&quot; : &quot;http://example.com/products/123_front.jpg&quot;
}
DynamoDBHashKey
Maps a class property to the partition key of the table. The property must be one of the scalar string,
number or binary types; it cannot be a collection type.
Assume that you have a table, ProductCatalog, that has Id as the primary key. The following Java code
snippet deﬁnes a CatalogItem class and maps its Id property to the primary key of the ProductCatalog
table using the @DynamoDBHashKey tag.
@DynamoDBTable(tableName=&quot;ProductCatalog&quot;)
public class CatalogItem {
private Integer Id;
@DynamoDBHashKey(attributeName=&quot;Id&quot;)
public Integer getId() {
return Id;
}
public void setId(Integer Id) {
this.Id = Id;
}
// Additional properties go here.
}
DynamoDBIgnore
Indicates to the DynamoDBMapper instance that the associated property should be ignored. When saving
data to the table, the DynamoDBMapper does not save this property to the table.
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DynamoDBIndexHashKey
Maps a class property to the partition key of a global secondary index. The property must be one of the
scalar string, number or binary types; it cannot be a collection type.
Use this annotation if you need to Query a global secondary index. You must specify the index name
(globalSecondaryIndexName). If the name of the class property is diﬀerent from the index partition key,
you must also specify the name of that index attribute (attributeName).
DynamoDBIndexRangeKey
Maps a class property to the sort key of a global secondary index or a local secondary index. The
property must be one of the scalar string, number or binary types; it cannot be a collection type.
Use this annotation if you need to Query a local secondary index or a global secondary index
and want to reﬁne your results using the index sort key. You must specify the index name (either
globalSecondaryIndexName or localSecondaryIndexName). If the name of the class property is diﬀerent
from the index sort key, you must also specify the name of that index attribute (attributeName).
DynamoDBRangeKey
Maps a class property to the sort key of the table. The property must be one of the scalar string, number
or binary types; it cannot be a collection type.
If the primary key is composite (partition key and sort key), you can use this tag to map your class
ﬁeld to the sort key. For example, assume that you have a Reply table that stores replies for forum
threads. Each thread can have many replies. So the primary key of this table is both the ThreadId and
ReplyDateTime. The ThreadId is the partition key and ReplyDateTime is the sort key. The following Java
code snippet deﬁnes a Reply class and maps it to the Reply table. It uses both the @DynamoDBHashKey and
@DynamoDBRangeKey tags to identify class properties that map to the primary key.
@DynamoDBTable(tableName=&quot;Reply&quot;)
public class Reply {
private Integer id;
private String replyDateTime;
@DynamoDBHashKey(attributeName=&quot;Id&quot;)
public Integer getId() { return id; }
public void setId(Integer id) { this.id = id; }
@DynamoDBRangeKey(attributeName=&quot;ReplyDateTime&quot;)
public String getReplyDateTime() { return replyDateTime; }
public void setReplyDateTime(String replyDateTime) { this.replyDateTime =
replyDateTime; }
}
// Additional properties go here.
DynamoDBTable
Identiﬁes the target table in DynamoDB. For example, the following Java code snippet deﬁnes a class
Developer and maps it to the People table in DynamoDB.
@DynamoDBTable(tableName=&quot;People&quot;)
public class Developer { ...}
The @DynamoDBTable annotation can be inherited. Any new class that inherits from the Developer class
also maps to the People table. For example, assume that you create a Lead class that inherits from the
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Developer class. Because you mapped the Developer class to the People table, the Lead class objects are
also stored in the same table.
The @DynamoDBTable can also be overridden. Any new class that inherits from the Developer class by
default maps to the same People table. However, you can override this default mapping. For example,
if you create a class that inherits from the Developer class, you can explicitly map it to another table by
adding the @DynamoDBTable annotation as shown in the following Java code snippet.
@DynamoDBTable(tableName=&quot;Managers&quot;)
public class Manager extends Developer { ...}
DynamoDBTypeConverted
Annotation to mark a property as using a custom type-converter. May be annotated on a user-deﬁned
annotation to pass additional properties to the DynamoDBTypeConverter.
The DynamoDBTypeConverter interface lets you map your own arbitrary data types to a data type that is
natively supported by DynamoDB. For more information, see Mapping Arbitrary Data (p. 229).
DynamoDBTyped
Annotation to override the standard attribute type binding. Standard types do not require the
annotation if applying the default attribute binding for that type.
DynamoDBVersionAttribute
Identiﬁes a class property for storing an optimistic locking version number. DynamoDBMapper assigns
a version number to this property when it saves a new item, and increments it each time you update
the item. Only number scalar types are supported. For more information about data type, see
Data Types (p. 12). For more information about versioning, see Optimistic Locking With Version
Number (p. 227).
The DynamoDBMapper Class
The DynamoDBMapper class is the entry point to DynamoDB. It provides access to a DynamoDB endpoint
and enables you to access your data in various tables, perform various CRUD operations on items, and
execute queries and scans against tables. This class provides the following methods for working with
DynamoDB.
For the corresponding Javadoc documentation, see DynamoDBMapper in the AWS SDK for Java API
Reference.
Topics
• save (p. 203)
• load (p. 203)
• delete (p. 203)
• query (p. 203)
• queryPage (p. 205)
• scan (p. 205)
• scanPage (p. 206)
• parallelScan (p. 206)
• batchSave (p. 206)
• batchLoad (p. 207)
• batchDelete (p. 207)
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• batchWrite (p. 207)
• count (p. 208)
• generateCreateTableRequest (p. 208)
• createS3Link (p. 208)
• getS3ClientCache (p. 209)
save
Saves the speciﬁed object to the table. The object that you wish to save is the only required parameter
for this method. You can provide optional conﬁguration parameters using the DynamoDBMapperConfig
object.
If an item that has the same primary key does not exist, this method creates a new item in the table.
If an item that has the same primary key exists, it updates the existing item. If the partition key and
sort key are of type String, and annotated with @DynamoDBAutoGeneratedKey, then they are given
a random universally unique identiﬁer (UUID) if left uninitialized. Version ﬁelds annotated with
@DynamoDBVersionAttribute will be incremented by one. Additionally, if a version ﬁeld is updated or a
key generated, the object passed in is updated as a result of the operation.
By default, only attributes corresponding to mapped class properties are updated; any additional existing
attributes on an item are unaﬀected. However, if you specify SaveBehavior.CLOBBER, you can force the
item to be completely overwritten.
mapper.save(obj, new DynamoDBMapperConfig(DynamoDBMapperConfig.SaveBehavior.CLOBBER));
If you have versioning enabled, then the client-side and server-side item versions must match. However,
the version does not need to match if the SaveBehavior.CLOBBER option is used. For more information
about versioning, see Optimistic Locking With Version Number (p. 227).
load
Retrieves an item from a table. You must provide the primary key of the item that you wish to retrieve.
You can provide optional conﬁguration parameters using the DynamoDBMapperConfig object. For example,
you can optionally request strongly consistent reads to ensure that this method retrieves only the latest
item values as shown in the following Java statement.
CatalogItem item = mapper.load(CatalogItem.class, item.getId(),
new
DynamoDBMapperConfig(DynamoDBMapperConfig.ConsistentReads.CONSISTENT));
By default, DynamoDB returns the item that has values that are eventually consistent. For information
about the eventual consistency model of DynamoDB, see Read Consistency (p. 15).
delete
Deletes an item from the table. You must pass in an object instance of the mapped class.
If you have versioning enabled, then the client-side and server-side item versions must match. However,
the version does not need to match if the SaveBehavior.CLOBBER option is used. For more information
about versioning, see Optimistic Locking With Version Number (p. 227).
query
Queries a table or a secondary index. You can query a table or an index only if it has a composite primary
key (partition key and sort key). This method requires you to provide a partition key value and a query
ﬁlter that is applied on the sort key. A ﬁlter expression includes a condition and a value.
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Assume that you have a table, Reply, that stores forum thread replies. Each thread subject can have 0 or
more replies. The primary key of the Reply table consists of the Id and ReplyDateTime ﬁelds, where Id is
the partition key and ReplyDateTime is the sort key of the primary key.
Reply ( Id, ReplyDateTime, ... )
Now, assume that you have created a mapping between a Reply class and the corresponding Reply table
in DynamoDB. The following Java code snippet uses DynamoDBMapper to ﬁnd all replies in the past two
weeks for a speciﬁc thread subject.
Example
String forumName = &quot;DynamoDB&quot;;
String forumSubject = &quot;DynamoDB Thread 1&quot;;
String partitionKey = forumName + &quot;#&quot; + forumSubject;
long twoWeeksAgoMilli = (new Date()).getTime() - (14L*24L*60L*60L*1000L);
Date twoWeeksAgo = new Date();
twoWeeksAgo.setTime(twoWeeksAgoMilli);
SimpleDateFormat df = new SimpleDateFormat(&quot;yyyy-MM-dd'T'HH:mm:ss.SSS'Z'&quot;);
String twoWeeksAgoStr = df.format(twoWeeksAgo);
Map&lt;String, AttributeValue&gt; eav = new HashMap&lt;String, AttributeValue&gt;();
eav.put(&quot;:v1&quot;, new AttributeValue().withS(partitionKey));
eav.put(&quot;:v2&quot;,new AttributeValue().withS(twoWeeksAgoStr.toString()));
DynamoDBQueryExpression&lt;Reply&gt; queryExpression = new DynamoDBQueryExpression&lt;Reply&gt;()
.withKeyConditionExpression(&quot;Id = :v1 and ReplyDateTime &gt; :v2&quot;)
.withExpressionAttributeValues(eav);
List&lt;Reply&gt; latestReplies = mapper.query(Reply.class, queryExpression);
The query returns a collection of Reply objects.
By default, the query method returns a &quot;lazy-loaded&quot; collection. It initially returns only one page of
results, and then makes a service call for the next page if needed. To obtain all the matching items, you
only need to iterate over the latestReplies collection.
To query an index, you must ﬁrst model the index as a mapper class. Suppose that the Reply table has a
global secondary index named PostedBy-Message-Index. The partition key for this index is PostedBy, and
the sort key is Message. The class deﬁnition for an item in the index would look like this:
@DynamoDBTable(tableName=&quot;Reply&quot;)
public class PostedByMessage {
private String postedBy;
private String message;
@DynamoDBIndexHashKey(globalSecondaryIndexName = &quot;PostedBy-Message-Index&quot;,
attributeName = &quot;PostedBy&quot;)
public String getPostedBy() { return postedBy; }
public void setPostedBy(String postedBy) { this.postedBy = postedBy; }
@DynamoDBIndexRangeKey(globalSecondaryIndexName = &quot;PostedBy-Message-Index&quot;,
attributeName = &quot;Message&quot;)
public String getMessage() { return message; }
public void setMessage(String message) { this.message = message; }
}
// Additional properties go here.
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The @DynamoDBTable annotation indicates that this index is associated with the Reply table.
The @DynamoDBIndexHashKey annotation denotes the partition key (PostedBy) of the index, and
@DynamoDBIndexRangeKey denotes the sort key (Message) of the index.
Now you can use DynamoDBMapper to query the index, retrieving a subset of messages that were posted
by a particular user. You must specify withIndexName so that DynamoDB knows which index to query.
In the following code snippet, we are querying a global secondary index. Because global secondary
indexes support eventually consistent reads, but not strongly consistent reads, we must specify
withConsistentRead(false).
HashMap&lt;String, AttributeValue&gt; eav = new HashMap&lt;String, AttributeValue&gt;();
eav.put(&quot;:v1&quot;, new AttributeValue().withS(&quot;User A&quot;));
eav.put(&quot;:v2&quot;, new AttributeValue().withS(&quot;DynamoDB&quot;));
DynamoDBQueryExpression&lt;PostedByMessage&gt; queryExpression = new
DynamoDBQueryExpression&lt;PostedByMessage&gt;()
.withIndexName(&quot;PostedBy-Message-Index&quot;)
.withConsistentRead(false)
.withKeyConditionExpression(&quot;PostedBy = :v1 and begins_with(Message, :v2)&quot;)
.withExpressionAttributeValues(eav);
List&lt;PostedByMessage&gt; iList =
mapper.query(PostedByMessage.class, queryExpression);
The query returns a collection of PostedByMessage objects.
queryPage
Queries a table or secondary index and returns a single page of matching results. As with the query
method, you must specify a partition key value and a query ﬁlter that is applied on the sort key attribute.
However, queryPage will only return the ﬁrst &quot;page&quot; of data - that is, the amount of data that will ﬁt
within 1 MB
scan
Scans an entire table or a secondary index. You can optionally specify a FilterExpression to ﬁlter the
result set.
Assume that you have a table, Reply, that stores forum thread replies. Each thread subject can have 0 or
more replies. The primary key of the Reply table consists of the Id and ReplyDateTime ﬁelds, where Id is
the partition key and ReplyDateTime is the sort key of the primary key.
Reply ( Id, ReplyDateTime, ... )
If you have mapped a Java class to the Reply table, you can use the DynamoDBMapper to scan the table.
For example, the following Java code snippet scans the entire Reply table, returning only the replies for a
particular year.
Example
HashMap&lt;String, AttributeValue&gt; eav = new HashMap&lt;String, AttributeValue&gt;();
eav.put(&quot;:v1&quot;, new AttributeValue().withS(&quot;2015&quot;));
DynamoDBScanExpression scanExpression = new DynamoDBScanExpression()
.withFilterExpression(&quot;begins_with(ReplyDateTime,:v1)&quot;)
.withExpressionAttributeValues(eav);
List&lt;Reply&gt; replies =
mapper.scan(Reply.class, scanExpression);
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By default, the scan method returns a &quot;lazy-loaded&quot; collection. It initially returns only one page of
results, and then makes a service call for the next page if needed. To obtain all the matching items, you
only need to iterate over the replies collection.
To scan an index, you must ﬁrst model the index as a mapper class. Suppose that the Reply table has a
global secondary index named PostedBy-Message-Index. The partition key for this index is PostedBy, and
the sort key is Message. A mapper class for this index is shown in the query (p. 203) section, where we
use the @DynamoDBIndexHashKey and @DynamoDBIndexRangeKey annotations to specify the index partition
key and sort key.
The following code snippet scans PostedBy-Message-Index. It does not use a scan ﬁlter, so all of the items
in the index are returned to you.
DynamoDBScanExpression scanExpression = new DynamoDBScanExpression()
.withIndexName(&quot;PostedBy-Message-Index&quot;)
.withConsistentRead(false);
List&lt;PostedByMessage&gt; indexItems = mapper.scan(PostedByMessage.class, scanExpression);
Iterator&lt;PostedByMessage&gt; indexItems = iList.iterator();
scanPage
Scans a table or secondary index and returns a single page of matching results. As with the scan method,
you can optionally specify a FilterExpression to ﬁlter the result set. However, scanPage will only return
the ﬁrst &quot;page&quot; of data - that is, the amount of data that will ﬁt within 1 MB
parallelScan
Performs a parallel scan of an entire table or secondary index. You specify a number of logical segments
for the table, along with a scan expression to ﬁlter the results. The parallelScan divides the scan task
among multiple workers, one for each logical segment; the workers process the data in parallel and
return the results.
The following Java code snippet performs a parallel scan on the Product table.
int numberOfThreads = 4;
Map&lt;String, AttributeValue&gt; eav = new HashMap&lt;String, AttributeValue&gt; ();
eav.put(&quot;:n&quot;, new AttributeValue().withN(&quot;100&quot;));
DynamoDBScanExpression scanExpression = new DynamoDBScanExpression()
.withFilterExpression(&quot;Price &gt;= :n&quot;)
.withExpressionAttributeValues(eav);
List&lt;Product&gt; scanResult = mapper.parallelScan(Product.class, scanExpression,
numberOfThreads);
For a Java code sample illustrating usage of parallelScan, see Example: Query and Scan (p. 218).
batchSave
Saves objects to one or more tables using one or more calls to the AmazonDynamoDB.batchWriteItem
method. This method does not provide transaction guarantees.
The following Java code snippet saves two items (books) to the ProductCatalog table.
Book book1 = new Book();
book1.id = 901;
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book1.productCategory = &quot;Book&quot;;
book1.title = &quot;Book 901 Title&quot;;
Book book2 = new Book();
book2.id = 902;
book2.productCategory = &quot;Book&quot;;
book2.title = &quot;Book 902 Title&quot;;
mapper.batchSave(Arrays.asList(book1, book2));
batchLoad
Retrieves multiple items from one or more tables using their primary keys.
The following Java code snippet retrieves two items from two diﬀerent tables.
ArrayList&lt;Object&gt; itemsToGet = new ArrayList&lt;Object&gt;();
ForumItem forumItem = new ForumItem();
forumItem.setForumName(&quot;Amazon DynamoDB&quot;);
itemsToGet.add(forumItem);
ThreadItem threadItem = new ThreadItem();
threadItem.setForumName(&quot;Amazon DynamoDB&quot;);
threadItem.setSubject(&quot;Amazon DynamoDB thread 1 message text&quot;);
itemsToGet.add(threadItem);
Map&lt;String, List&lt;Object&gt;&gt; items = mapper.batchLoad(itemsToGet);
batchDelete
Deletes objects from one or more tables using one or more calls to the AmazonDynamoDB.batchWriteItem
method. This method does not provide transaction guarantees.
The following Java code snippet deletes two items (books) from the ProductCatalog table.
Book book1 = mapper.load(Book.class, 901);
Book book2 = mapper.load(Book.class, 902);
mapper.batchDelete(Arrays.asList(book1, book2));
batchWrite
Saves objects to and deletes objects from one or more tables using one or more calls to the
AmazonDynamoDB.batchWriteItem method. This method does not provide transaction guarantees or
support versioning (conditional puts or deletes).
The following Java code snippet writes a new item to the Forum table, writes a new item to the Thread
table, and deletes an item from the ProductCatalog table.
// Create a Forum item to save
Forum forumItem = new Forum();
forumItem.name = &quot;Test BatchWrite Forum&quot;;
// Create a Thread item to save
Thread threadItem = new Thread();
threadItem.forumName = &quot;AmazonDynamoDB&quot;;
threadItem.subject = &quot;My sample question&quot;;
// Load a ProductCatalog item to delete
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Book book3 = mapper.load(Book.class, 903);
List&lt;Object&gt; objectsToWrite = Arrays.asList(forumItem, threadItem);
List&lt;Book&gt; objectsToDelete = Arrays.asList(book3);
mapper.batchWrite(objectsToWrite, objectsToDelete);
count
Evaluates the speciﬁed scan expression and returns the count of matching items. No item data is
returned.
generateCreateTableRequest
Parses a POJO class that represents a DynamoDB table, and returns a CreateTableRequest for that table.
createS3Link
Creates a link to an object in Amazon S3. You must specify a bucket name and a key name, which
uniquely identiﬁes the object in the bucket.
To use createS3Link, your mapper class must deﬁne getter and setter methods. The following code
snippet illustrates this by adding a new attribute and getter/setter methods to the CatalogItem class:
@DynamoDBTable(tableName=&quot;ProductCatalog&quot;)
public class CatalogItem {
...
public S3Link productImage;
....
@DynamoDBAttribute(attributeName = &quot;ProductImage&quot;)
public S3Link getProductImage() {
return productImage;
}
public void setProductImage(S3Link productImage) {
this.productImage = productImage;
}
...
}
The following Java code deﬁnes a new item to be written to the Product table. The item includes a link
to a product image; the image data is uploaded to Amazon S3.
CatalogItem item = new CatalogItem();
item.id = 150;
item.title = &quot;Book 150 Title&quot;;
String myS3Bucket = &quot;myS3bucket&quot;;
String myS3Key = &quot;productImages/book_150_cover.jpg&quot;;
item.setProductImage(mapper.createS3Link(myS3Bucket, myS3Key));
item.getProductImage().uploadFrom(new File(&quot;/file/path/book_150_cover.jpg&quot;));
mapper.save(item);
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The S3Link class provides many other methods for manipulating objects in Amazon S3. For more
information, see the Javadocs for S3Link.
getS3ClientCache
Returns the underlying S3ClientCache for accessing Amazon S3. An S3ClientCache is a smart Map
for AmazonS3Client objects. If you have multiple clients, then an S3ClientCache can help you keep the
clients organized by region, and can create new Amazon S3 clients on demand.
Optional Conﬁguration Settings for DynamoDBMapper
When you create an instance of DynamoDBMapper, it has certain default behaviors; you can override these
defaults by using the DynamoDBMapperConfig class.
The following code snippet creates a DynamoDBMapper with custom settings:
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
DynamoDBMapperConfig mapperConfig = new DynamoDBMapperConfig(
DynamoDBMapperConfig.SaveBehavior.CLOBBER,
DynamoDBMapperConfig.ConsistentReads.CONSISTENT,
null, //TableNameOverride - leaving this at default setting
DynamoDBMapperConfig.PaginationLoadingStrategy.EAGER_LOADING
);
DynamoDBMapper mapper = new DynamoDBMapper(client, mapperConfig, cp);
For more information, see DynamoDBMapperConﬁg in the AWS SDK for Java API Reference.
You can use the following arguments for an instance of DynamoDBMapperConfig:
• A DynamoDBMapperConfig.ConsistentReads enumeration value:
• EVENTUAL—the mapper instance uses an eventually consistent read request.
• CONSISTENT—the mapper instance uses a strongly consistent read request. You can use this optional
setting with load, query, or scan operations. Strongly consistent reads have implications for
performance and billing; see the DynamoDB product detail page for more information.
If you do not specify a read consistency setting for your mapper instance, the default is EVENTUAL.
• A DynamoDBMapperConfig.PaginationLoadingStrategy enumeration value—Controls how the mapper
instance processes a paginated list of data, such as the results from a query or scan:
• LAZY_LOADING— the mapper instance loads data when possible, and keep all loaded results in
memory.
• EAGER_LOADING—the mapper instance loads the data as soon as the list is initialized.
• ITERATION_ONLY—you can only use an Iterator to read from the list. During the iteration, the list will
clear all the previous results before loading the next page, so that the list will keep at most one page
of the loaded results in memory. This also means the list can only be iterated once. This strategy is
recommended when handling large items, in order to reduce memory overhead.
If you do not specify a pagination loading strategy for your mapper instance, the default is
LAZY_LOADING.
• A DynamoDBMapperConfig.SaveBehavior enumeration value - Speciﬁes how the mapper instance
should deal with attributes during save operations:
• UPDATE—during a save operation, all modeled attributes are updated, and unmodeled attributes are
unaﬀected. Primitive number types (byte, int, long) are set to 0. Object types are set to null.
• CLOBBER—clears and replaces all attributes, included unmodeled ones, during a save operation. This
is done be deleting the item and re-creating it. Versioned ﬁeld constraints are also disregarded.
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If you do not specify the save behavior for your mapper instance, the default is UPDATE.
• A DynamoDBMapperConfig.TableNameOverride object—Instructs the mapper instance to ignore the
table name speciﬁed by a class's DynamoDBTable annotation, and instead use a diﬀerent table name
that you supply. This is useful when partitioning your data into multiple tables at run time.
You can override the default conﬁguration object for DynamoDBMapper per operation, as needed.
Example: CRUD Operations
The following Java code example declares a CatalogItem class that has Id, Title, ISBN and Authors
properties. It uses the annotations to map these properties to the ProductCatalog table in DynamoDB.
The code example then uses the DynamoDBMapper to save a book object, retrieve it, update it and delete
the book item.
Note
This code sample assumes that you have already loaded data into DynamoDB for your account
by following the instructions in the Creating Tables and Loading Sample Data (p. 280) section.
For step-by-step instructions to run the following example, see Java Code Samples (p. 285).
// Copyright 2012-2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
// Licensed under the Apache License, Version 2.0.
package com.amazonaws.codesamples.datamodeling;
import
import
import
import
java.io.IOException;
java.util.Arrays;
java.util.HashSet;
java.util.Set;
import
import
import
import
import
import
import
com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBAttribute;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBHashKey;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBMapper;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBMapperConfig;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBTable;
public class DynamoDBMapperCRUDExample {
static AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
public static void main(String[] args) throws IOException {
testCRUDOperations();
System.out.println(&quot;Example complete!&quot;);
}
@DynamoDBTable(tableName = &quot;ProductCatalog&quot;)
public static class CatalogItem {
private Integer id;
private String title;
private String ISBN;
private Set&lt;String&gt; bookAuthors;
// Partition key
@DynamoDBHashKey(attributeName = &quot;Id&quot;)
public Integer getId() {
return id;
}
public void setId(Integer id) {
this.id = id;
}
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@DynamoDBAttribute(attributeName = &quot;Title&quot;)
public String getTitle() {
return title;
}
public void setTitle(String title) {
this.title = title;
}
@DynamoDBAttribute(attributeName = &quot;ISBN&quot;)
public String getISBN() {
return ISBN;
}
public void setISBN(String ISBN) {
this.ISBN = ISBN;
}
@DynamoDBAttribute(attributeName = &quot;Authors&quot;)
public Set&lt;String&gt; getBookAuthors() {
return bookAuthors;
}
public void setBookAuthors(Set&lt;String&gt; bookAuthors) {
this.bookAuthors = bookAuthors;
}
@Override
public String toString() {
return &quot;Book [ISBN=&quot; + ISBN + &quot;, bookAuthors=&quot; + bookAuthors + &quot;, id=&quot; + id +
&quot;, title=&quot; + title + &quot;]&quot;;
}
}
private static void testCRUDOperations() {
CatalogItem item = new CatalogItem();
item.setId(601);
item.setTitle(&quot;Book 601&quot;);
item.setISBN(&quot;611-1111111111&quot;);
item.setBookAuthors(new HashSet&lt;String&gt;(Arrays.asList(&quot;Author1&quot;, &quot;Author2&quot;)));
// Save the item (book).
DynamoDBMapper mapper = new DynamoDBMapper(client);
mapper.save(item);
// Retrieve the item.
CatalogItem itemRetrieved = mapper.load(CatalogItem.class, 601);
System.out.println(&quot;Item retrieved:&quot;);
System.out.println(itemRetrieved);
// Update the item.
itemRetrieved.setISBN(&quot;622-2222222222&quot;);
itemRetrieved.setBookAuthors(new HashSet&lt;String&gt;(Arrays.asList(&quot;Author1&quot;,
&quot;Author3&quot;)));
mapper.save(itemRetrieved);
System.out.println(&quot;Item updated:&quot;);
System.out.println(itemRetrieved);
// Retrieve the updated item.
DynamoDBMapperConfig config = new
DynamoDBMapperConfig(DynamoDBMapperConfig.ConsistentReads.CONSISTENT);
CatalogItem updatedItem = mapper.load(CatalogItem.class, 601, config);
System.out.println(&quot;Retrieved the previously updated item:&quot;);
System.out.println(updatedItem);
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// Delete the item.
mapper.delete(updatedItem);
// Try to retrieve deleted item.
CatalogItem deletedItem = mapper.load(CatalogItem.class, updatedItem.getId(),
config);
if (deletedItem == null) {
System.out.println(&quot;Done - Sample item is deleted.&quot;);
}
}
}
Example: Batch Write Operations
The following Java code example declares Book, Forum, Thread, and Reply classes and maps them to the
DynamoDB tables using the DynamoDBMapper class.
The code illustrate the following batch write operations:
• batchSave to put book items in the ProductCatalog table.
• batchDelete to delete items from the ProductCatalog table.
• batchWrite to put and delete items from the Forum and the Thread tables.
For more information about the tables used in this example, see Creating Tables and Loading
Sample Data (p. 280). For step-by-step instructions to test the following sample, see Java Code
Samples (p. 285).
Example
// Copyright 2012-2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
// Licensed under the Apache License, Version 2.0.
package com.amazonaws.codesamples.datamodeling;
import
import
import
import
import
import
java.text.SimpleDateFormat;
java.util.ArrayList;
java.util.Arrays;
java.util.HashSet;
java.util.List;
java.util.Set;
import
import
import
import
import
import
import
import
com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBAttribute;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBHashKey;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBMapper;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBMapperConfig;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBRangeKey;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBTable;
public class DynamoDBMapperBatchWriteExample {
static AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
static SimpleDateFormat dateFormatter = new SimpleDateFormat(&quot;yyyy-MMdd'T'HH:mm:ss.SSS'Z'&quot;);
public static void main(String[] args) throws Exception {
try {
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DynamoDBMapper mapper = new DynamoDBMapper(client);
testBatchSave(mapper);
testBatchDelete(mapper);
testBatchWrite(mapper);
System.out.println(&quot;Example complete!&quot;);
}
}
catch (Throwable t) {
System.err.println(&quot;Error running the DynamoDBMapperBatchWriteExample: &quot; + t);
t.printStackTrace();
}
private static void testBatchSave(DynamoDBMapper mapper) {
Book book1 = new Book();
book1.id = 901;
book1.inPublication = true;
book1.ISBN = &quot;902-11-11-1111&quot;;
book1.pageCount = 100;
book1.price = 10;
book1.productCategory = &quot;Book&quot;;
book1.title = &quot;My book created in batch write&quot;;
Book book2 = new Book();
book2.id = 902;
book2.inPublication = true;
book2.ISBN = &quot;902-11-12-1111&quot;;
book2.pageCount = 200;
book2.price = 20;
book2.productCategory = &quot;Book&quot;;
book2.title = &quot;My second book created in batch write&quot;;
Book book3 = new Book();
book3.id = 903;
book3.inPublication = false;
book3.ISBN = &quot;902-11-13-1111&quot;;
book3.pageCount = 300;
book3.price = 25;
book3.productCategory = &quot;Book&quot;;
book3.title = &quot;My third book created in batch write&quot;;
}
System.out.println(&quot;Adding three books to ProductCatalog table.&quot;);
mapper.batchSave(Arrays.asList(book1, book2, book3));
private static void testBatchDelete(DynamoDBMapper mapper) {
}
Book book1 = mapper.load(Book.class, 901);
Book book2 = mapper.load(Book.class, 902);
System.out.println(&quot;Deleting two books from the ProductCatalog table.&quot;);
mapper.batchDelete(Arrays.asList(book1, book2));
private static void testBatchWrite(DynamoDBMapper mapper) {
// Create Forum item to save
Forum forumItem = new Forum();
forumItem.name = &quot;Test BatchWrite Forum&quot;;
forumItem.threads = 0;
forumItem.category = &quot;Amazon Web Services&quot;;
// Create Thread item to save
Thread threadItem = new Thread();
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threadItem.forumName = &quot;AmazonDynamoDB&quot;;
threadItem.subject = &quot;My sample question&quot;;
threadItem.message = &quot;BatchWrite message&quot;;
List&lt;String&gt; tags = new ArrayList&lt;String&gt;();
tags.add(&quot;batch operations&quot;);
tags.add(&quot;write&quot;);
threadItem.tags = new HashSet&lt;String&gt;(tags);
// Load ProductCatalog item to delete
Book book3 = mapper.load(Book.class, 903);
List&lt;Object&gt; objectsToWrite = Arrays.asList(forumItem, threadItem);
List&lt;Book&gt; objectsToDelete = Arrays.asList(book3);
DynamoDBMapperConfig config = new
DynamoDBMapperConfig(DynamoDBMapperConfig.SaveBehavior.CLOBBER);
mapper.batchWrite(objectsToWrite, objectsToDelete, config);
}
@DynamoDBTable(tableName = &quot;ProductCatalog&quot;)
public static class Book {
private int id;
private String title;
private String ISBN;
private int price;
private int pageCount;
private String productCategory;
private boolean inPublication;
// Partition key
@DynamoDBHashKey(attributeName = &quot;Id&quot;)
public int getId() {
return id;
}
public void setId(int id) {
this.id = id;
}
@DynamoDBAttribute(attributeName = &quot;Title&quot;)
public String getTitle() {
return title;
}
public void setTitle(String title) {
this.title = title;
}
@DynamoDBAttribute(attributeName = &quot;ISBN&quot;)
public String getISBN() {
return ISBN;
}
public void setISBN(String ISBN) {
this.ISBN = ISBN;
}
@DynamoDBAttribute(attributeName = &quot;Price&quot;)
public int getPrice() {
return price;
}
public void setPrice(int price) {
this.price = price;
}
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@DynamoDBAttribute(attributeName = &quot;PageCount&quot;)
public int getPageCount() {
return pageCount;
}
public void setPageCount(int pageCount) {
this.pageCount = pageCount;
}
@DynamoDBAttribute(attributeName = &quot;ProductCategory&quot;)
public String getProductCategory() {
return productCategory;
}
public void setProductCategory(String productCategory) {
this.productCategory = productCategory;
}
@DynamoDBAttribute(attributeName = &quot;InPublication&quot;)
public boolean getInPublication() {
return inPublication;
}
public void setInPublication(boolean inPublication) {
this.inPublication = inPublication;
}
@Override
public String toString() {
return &quot;Book [ISBN=&quot; + ISBN + &quot;, price=&quot; + price + &quot;, product category=&quot; +
productCategory + &quot;, id=&quot; + id
+ &quot;, title=&quot; + title + &quot;]&quot;;
}
}
@DynamoDBTable(tableName = &quot;Reply&quot;)
public static class Reply {
private String id;
private String replyDateTime;
private String message;
private String postedBy;
// Partition key
@DynamoDBHashKey(attributeName = &quot;Id&quot;)
public String getId() {
return id;
}
public void setId(String id) {
this.id = id;
}
// Sort key
@DynamoDBRangeKey(attributeName = &quot;ReplyDateTime&quot;)
public String getReplyDateTime() {
return replyDateTime;
}
public void setReplyDateTime(String replyDateTime) {
this.replyDateTime = replyDateTime;
}
@DynamoDBAttribute(attributeName = &quot;Message&quot;)
public String getMessage() {
return message;
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}
public void setMessage(String message) {
this.message = message;
}
@DynamoDBAttribute(attributeName = &quot;PostedBy&quot;)
public String getPostedBy() {
return postedBy;
}
}
public void setPostedBy(String postedBy) {
this.postedBy = postedBy;
}
@DynamoDBTable(tableName = &quot;Thread&quot;)
public static class Thread {
private String forumName;
private String subject;
private String message;
private String lastPostedDateTime;
private String lastPostedBy;
private Set&lt;String&gt; tags;
private int answered;
private int views;
private int replies;
// Partition key
@DynamoDBHashKey(attributeName = &quot;ForumName&quot;)
public String getForumName() {
return forumName;
}
public void setForumName(String forumName) {
this.forumName = forumName;
}
// Sort key
@DynamoDBRangeKey(attributeName = &quot;Subject&quot;)
public String getSubject() {
return subject;
}
public void setSubject(String subject) {
this.subject = subject;
}
@DynamoDBAttribute(attributeName = &quot;Message&quot;)
public String getMessage() {
return message;
}
public void setMessage(String message) {
this.message = message;
}
@DynamoDBAttribute(attributeName = &quot;LastPostedDateTime&quot;)
public String getLastPostedDateTime() {
return lastPostedDateTime;
}
public void setLastPostedDateTime(String lastPostedDateTime) {
this.lastPostedDateTime = lastPostedDateTime;
}
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@DynamoDBAttribute(attributeName = &quot;LastPostedBy&quot;)
public String getLastPostedBy() {
return lastPostedBy;
}
public void setLastPostedBy(String lastPostedBy) {
this.lastPostedBy = lastPostedBy;
}
@DynamoDBAttribute(attributeName = &quot;Tags&quot;)
public Set&lt;String&gt; getTags() {
return tags;
}
public void setTags(Set&lt;String&gt; tags) {
this.tags = tags;
}
@DynamoDBAttribute(attributeName = &quot;Answered&quot;)
public int getAnswered() {
return answered;
}
public void setAnswered(int answered) {
this.answered = answered;
}
@DynamoDBAttribute(attributeName = &quot;Views&quot;)
public int getViews() {
return views;
}
public void setViews(int views) {
this.views = views;
}
@DynamoDBAttribute(attributeName = &quot;Replies&quot;)
public int getReplies() {
return replies;
}
public void setReplies(int replies) {
this.replies = replies;
}
}
@DynamoDBTable(tableName = &quot;Forum&quot;)
public static class Forum {
private String name;
private String category;
private int threads;
// Partition key
@DynamoDBHashKey(attributeName = &quot;Name&quot;)
public String getName() {
return name;
}
public void setName(String name) {
this.name = name;
}
@DynamoDBAttribute(attributeName = &quot;Category&quot;)
public String getCategory() {
return category;
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}
public void setCategory(String category) {
this.category = category;
}
@DynamoDBAttribute(attributeName = &quot;Threads&quot;)
public int getThreads() {
return threads;
}
}
}
public void setThreads(int threads) {
this.threads = threads;
}
Example: Query and Scan
The Java example in this section deﬁnes the following classes and maps them to the tables in
DynamoDB. For more information about creating sample tables, see Creating Tables and Loading Sample
Data (p. 280).
• Book class maps to ProductCatalog table
• Forum, Thread and Reply classes maps to the same name tables.
The example then executes the follow query and scan operations using a DynamoDBMapper instance.
• Get a book by Id.
The ProductCatalog table has Id as its primary key. It does not have a sort key as part of its primary
key. Therefore, you cannot query the table. You can get an item using its id value.
• Execute the following queries against the Reply table.
The Reply table's primary key is composed of Id and ReplyDateTime attributes. The ReplyDateTime is a
sort key. Therefore, you can query this table.
• Find replies to a forum thread posted in the last 15 days
• Find replies to a forum thread posted in a speciﬁc date range
• Scan ProductCatalog table to ﬁnd books whose price is less than a speciﬁed value.
For performance reasons, you should use query instead of the scan operation. However, there are
times you might need to scan a table. Suppose there was a data entry error and one of the book
prices was set to less than 0. This example scans the ProductCategory table to ﬁnd book items
(ProductCategory is book) and price is less than 0.
• Perform a parallel scan of the ProductCatalog table to ﬁnd bicycles of a speciﬁc type.
Note
This code sample assumes that you have already loaded data into DynamoDB for your account
by following the instructions in the Creating Tables and Loading Sample Data (p. 280) section.
For step-by-step instructions to run the following example, see Java Code Samples (p. 285).
Example
// Copyright 2012-2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
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// Licensed under the Apache License, Version 2.0.
package com.amazonaws.codesamples.datamodeling;
import
import
import
import
import
import
import
java.text.SimpleDateFormat;
java.util.Date;
java.util.HashMap;
java.util.List;
java.util.Map;
java.util.Set;
java.util.TimeZone;
import
import
import
import
import
import
import
import
import
import
com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBAttribute;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBHashKey;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBMapper;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBQueryExpression;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBRangeKey;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBScanExpression;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBTable;
com.amazonaws.services.dynamodbv2.model.AttributeValue;
public class DynamoDBMapperQueryScanExample {
static AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
public static void main(String[] args) throws Exception {
try {
DynamoDBMapper mapper = new DynamoDBMapper(client);
// Get a book - Id=101
GetBook(mapper, 101);
// Sample forum and thread to test queries.
String forumName = &quot;Amazon DynamoDB&quot;;
String threadSubject = &quot;DynamoDB Thread 1&quot;;
// Sample queries.
FindRepliesInLast15Days(mapper, forumName, threadSubject);
FindRepliesPostedWithinTimePeriod(mapper, forumName, threadSubject);
// Scan a table and find book items priced less than specified
// value.
FindBooksPricedLessThanSpecifiedValue(mapper, &quot;20&quot;);
// Scan a table with multiple threads and find bicycle items with a
// specified bicycle type
int numberOfThreads = 16;
FindBicyclesOfSpecificTypeWithMultipleThreads(mapper, numberOfThreads, &quot;Road&quot;);
System.out.println(&quot;Example complete!&quot;);
}
}
catch (Throwable t) {
System.err.println(&quot;Error running the DynamoDBMapperQueryScanExample: &quot; + t);
t.printStackTrace();
}
private static void GetBook(DynamoDBMapper mapper, int id) throws Exception {
System.out.println(&quot;GetBook: Get book Id='101' &quot;);
System.out.println(&quot;Book table has no sort key. You can do GetItem, but not
Query.&quot;);
Book book = mapper.load(Book.class, 101);
System.out.format(&quot;Id = %s Title = %s, ISBN = %s %n&quot;, book.getId(),
book.getTitle(), book.getISBN());
}
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private static void FindRepliesInLast15Days(DynamoDBMapper mapper, String forumName,
String threadSubject)
throws Exception {
System.out.println(&quot;FindRepliesInLast15Days: Replies within last 15 days.&quot;);
String partitionKey = forumName + &quot;#&quot; + threadSubject;
long twoWeeksAgoMilli = (new Date()).getTime() - (15L * 24L * 60L * 60L * 1000L);
Date twoWeeksAgo = new Date();
twoWeeksAgo.setTime(twoWeeksAgoMilli);
SimpleDateFormat dateFormatter = new SimpleDateFormat(&quot;yyyy-MMdd'T'HH:mm:ss.SSS'Z'&quot;);
dateFormatter.setTimeZone(TimeZone.getTimeZone(&quot;UTC&quot;));
String twoWeeksAgoStr = dateFormatter.format(twoWeeksAgo);
Map&lt;String, AttributeValue&gt; eav = new HashMap&lt;String, AttributeValue&gt;();
eav.put(&quot;:val1&quot;, new AttributeValue().withS(partitionKey));
eav.put(&quot;:val2&quot;, new AttributeValue().withS(twoWeeksAgoStr.toString()));
DynamoDBQueryExpression&lt;Reply&gt; queryExpression = new
DynamoDBQueryExpression&lt;Reply&gt;()
.withKeyConditionExpression(&quot;Id = :val1 and ReplyDateTime
&gt; :val2&quot;).withExpressionAttributeValues(eav);
List&lt;Reply&gt; latestReplies = mapper.query(Reply.class, queryExpression);
for (Reply reply : latestReplies) {
System.out.format(&quot;Id=%s, Message=%s, PostedBy=%s %n, ReplyDateTime=%s %n&quot;,
reply.getId(),
reply.getMessage(), reply.getPostedBy(), reply.getReplyDateTime());
}
}
private static void FindRepliesPostedWithinTimePeriod(DynamoDBMapper mapper, String
forumName, String threadSubject)
throws Exception {
String partitionKey = forumName + &quot;#&quot; + threadSubject;
System.out.println(
&quot;FindRepliesPostedWithinTimePeriod: Find replies for thread Message = 'DynamoDB
Thread 2' posted within a period.&quot;);
long startDateMilli = (new Date()).getTime() - (14L * 24L * 60L * 60L * 1000L); //
Two
//
weeks
//
ago.
long endDateMilli = (new Date()).getTime() - (7L * 24L * 60L * 60L * 1000L); // One
//
week
//
ago.
SimpleDateFormat dateFormatter = new SimpleDateFormat(&quot;yyyy-MMdd'T'HH:mm:ss.SSS'Z'&quot;);
dateFormatter.setTimeZone(TimeZone.getTimeZone(&quot;UTC&quot;));
String startDate = dateFormatter.format(startDateMilli);
String endDate = dateFormatter.format(endDateMilli);
Map&lt;String, AttributeValue&gt; eav = new HashMap&lt;String, AttributeValue&gt;();
eav.put(&quot;:val1&quot;, new AttributeValue().withS(partitionKey));
eav.put(&quot;:val2&quot;, new AttributeValue().withS(startDate));
eav.put(&quot;:val3&quot;, new AttributeValue().withS(endDate));
DynamoDBQueryExpression&lt;Reply&gt; queryExpression = new
DynamoDBQueryExpression&lt;Reply&gt;()
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.withKeyConditionExpression(&quot;Id = :val1 and ReplyDateTime between :val2
and :val3&quot;)
.withExpressionAttributeValues(eav);
List&lt;Reply&gt; betweenReplies = mapper.query(Reply.class, queryExpression);
for (Reply reply : betweenReplies) {
System.out.format(&quot;Id=%s, Message=%s, PostedBy=%s %n, PostedDateTime=%s %n&quot;,
reply.getId(),
reply.getMessage(), reply.getPostedBy(), reply.getReplyDateTime());
}
}
private static void FindBooksPricedLessThanSpecifiedValue(DynamoDBMapper mapper, String
value) throws Exception {
System.out.println(&quot;FindBooksPricedLessThanSpecifiedValue: Scan ProductCatalog.&quot;);
Map&lt;String, AttributeValue&gt; eav = new HashMap&lt;String, AttributeValue&gt;();
eav.put(&quot;:val1&quot;, new AttributeValue().withN(value));
eav.put(&quot;:val2&quot;, new AttributeValue().withS(&quot;Book&quot;));
DynamoDBScanExpression scanExpression = new DynamoDBScanExpression()
.withFilterExpression(&quot;Price &lt; :val1 and ProductCategory
= :val2&quot;).withExpressionAttributeValues(eav);
List&lt;Book&gt; scanResult = mapper.scan(Book.class, scanExpression);
}
for (Book book : scanResult) {
System.out.println(book);
}
private static void FindBicyclesOfSpecificTypeWithMultipleThreads(DynamoDBMapper
mapper, int numberOfThreads,
String bicycleType) throws Exception {
System.out.println(&quot;FindBicyclesOfSpecificTypeWithMultipleThreads: Scan
ProductCatalog With Multiple Threads.&quot;);
Map&lt;String, AttributeValue&gt; eav = new HashMap&lt;String, AttributeValue&gt;();
eav.put(&quot;:val1&quot;, new AttributeValue().withS(&quot;Bicycle&quot;));
eav.put(&quot;:val2&quot;, new AttributeValue().withS(bicycleType));
DynamoDBScanExpression scanExpression = new DynamoDBScanExpression()
.withFilterExpression(&quot;ProductCategory = :val1 and BicycleType
= :val2&quot;).withExpressionAttributeValues(eav);
List&lt;Bicycle&gt; scanResult = mapper.parallelScan(Bicycle.class, scanExpression,
numberOfThreads);
for (Bicycle bicycle : scanResult) {
System.out.println(bicycle);
}
}
@DynamoDBTable(tableName = &quot;ProductCatalog&quot;)
public static class Book {
private int id;
private String title;
private String ISBN;
private int price;
private int pageCount;
private String productCategory;
private boolean inPublication;
@DynamoDBHashKey(attributeName = &quot;Id&quot;)
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public int getId() {
return id;
}
public void setId(int id) {
this.id = id;
}
@DynamoDBAttribute(attributeName = &quot;Title&quot;)
public String getTitle() {
return title;
}
public void setTitle(String title) {
this.title = title;
}
@DynamoDBAttribute(attributeName = &quot;ISBN&quot;)
public String getISBN() {
return ISBN;
}
public void setISBN(String ISBN) {
this.ISBN = ISBN;
}
@DynamoDBAttribute(attributeName = &quot;Price&quot;)
public int getPrice() {
return price;
}
public void setPrice(int price) {
this.price = price;
}
@DynamoDBAttribute(attributeName = &quot;PageCount&quot;)
public int getPageCount() {
return pageCount;
}
public void setPageCount(int pageCount) {
this.pageCount = pageCount;
}
@DynamoDBAttribute(attributeName = &quot;ProductCategory&quot;)
public String getProductCategory() {
return productCategory;
}
public void setProductCategory(String productCategory) {
this.productCategory = productCategory;
}
@DynamoDBAttribute(attributeName = &quot;InPublication&quot;)
public boolean getInPublication() {
return inPublication;
}
public void setInPublication(boolean inPublication) {
this.inPublication = inPublication;
}
@Override
public String toString() {
return &quot;Book [ISBN=&quot; + ISBN + &quot;, price=&quot; + price + &quot;, product category=&quot; +
productCategory + &quot;, id=&quot; + id
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}
+ &quot;, title=&quot; + title + &quot;]&quot;;
}
@DynamoDBTable(tableName = &quot;ProductCatalog&quot;)
public static class Bicycle {
private int id;
private String title;
private String description;
private String bicycleType;
private String brand;
private int price;
private List&lt;String&gt; color;
private String productCategory;
@DynamoDBHashKey(attributeName = &quot;Id&quot;)
public int getId() {
return id;
}
public void setId(int id) {
this.id = id;
}
@DynamoDBAttribute(attributeName = &quot;Title&quot;)
public String getTitle() {
return title;
}
public void setTitle(String title) {
this.title = title;
}
@DynamoDBAttribute(attributeName = &quot;Description&quot;)
public String getDescription() {
return description;
}
public void setDescription(String description) {
this.description = description;
}
@DynamoDBAttribute(attributeName = &quot;BicycleType&quot;)
public String getBicycleType() {
return bicycleType;
}
public void setBicycleType(String bicycleType) {
this.bicycleType = bicycleType;
}
@DynamoDBAttribute(attributeName = &quot;Brand&quot;)
public String getBrand() {
return brand;
}
public void setBrand(String brand) {
this.brand = brand;
}
@DynamoDBAttribute(attributeName = &quot;Price&quot;)
public int getPrice() {
return price;
}
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public void setPrice(int price) {
this.price = price;
}
@DynamoDBAttribute(attributeName = &quot;Color&quot;)
public List&lt;String&gt; getColor() {
return color;
}
public void setColor(List&lt;String&gt; color) {
this.color = color;
}
@DynamoDBAttribute(attributeName = &quot;ProductCategory&quot;)
public String getProductCategory() {
return productCategory;
}
public void setProductCategory(String productCategory) {
this.productCategory = productCategory;
}
@Override
public String toString() {
return &quot;Bicycle [Type=&quot; + bicycleType + &quot;, color=&quot; + color + &quot;, price=&quot; + price
+ &quot;, product category=&quot;
+ productCategory + &quot;, id=&quot; + id + &quot;, title=&quot; + title + &quot;]&quot;;
}
}
@DynamoDBTable(tableName = &quot;Reply&quot;)
public static class Reply {
private String id;
private String replyDateTime;
private String message;
private String postedBy;
// Partition key
@DynamoDBHashKey(attributeName = &quot;Id&quot;)
public String getId() {
return id;
}
public void setId(String id) {
this.id = id;
}
// Range key
@DynamoDBRangeKey(attributeName = &quot;ReplyDateTime&quot;)
public String getReplyDateTime() {
return replyDateTime;
}
public void setReplyDateTime(String replyDateTime) {
this.replyDateTime = replyDateTime;
}
@DynamoDBAttribute(attributeName = &quot;Message&quot;)
public String getMessage() {
return message;
}
public void setMessage(String message) {
this.message = message;
}
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@DynamoDBAttribute(attributeName = &quot;PostedBy&quot;)
public String getPostedBy() {
return postedBy;
}
}
public void setPostedBy(String postedBy) {
this.postedBy = postedBy;
}
@DynamoDBTable(tableName = &quot;Thread&quot;)
public static class Thread {
private String forumName;
private String subject;
private String message;
private String lastPostedDateTime;
private String lastPostedBy;
private Set&lt;String&gt; tags;
private int answered;
private int views;
private int replies;
// Partition key
@DynamoDBHashKey(attributeName = &quot;ForumName&quot;)
public String getForumName() {
return forumName;
}
public void setForumName(String forumName) {
this.forumName = forumName;
}
// Range key
@DynamoDBRangeKey(attributeName = &quot;Subject&quot;)
public String getSubject() {
return subject;
}
public void setSubject(String subject) {
this.subject = subject;
}
@DynamoDBAttribute(attributeName = &quot;Message&quot;)
public String getMessage() {
return message;
}
public void setMessage(String message) {
this.message = message;
}
@DynamoDBAttribute(attributeName = &quot;LastPostedDateTime&quot;)
public String getLastPostedDateTime() {
return lastPostedDateTime;
}
public void setLastPostedDateTime(String lastPostedDateTime) {
this.lastPostedDateTime = lastPostedDateTime;
}
@DynamoDBAttribute(attributeName = &quot;LastPostedBy&quot;)
public String getLastPostedBy() {
return lastPostedBy;
}
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public void setLastPostedBy(String lastPostedBy) {
this.lastPostedBy = lastPostedBy;
}
@DynamoDBAttribute(attributeName = &quot;Tags&quot;)
public Set&lt;String&gt; getTags() {
return tags;
}
public void setTags(Set&lt;String&gt; tags) {
this.tags = tags;
}
@DynamoDBAttribute(attributeName = &quot;Answered&quot;)
public int getAnswered() {
return answered;
}
public void setAnswered(int answered) {
this.answered = answered;
}
@DynamoDBAttribute(attributeName = &quot;Views&quot;)
public int getViews() {
return views;
}
public void setViews(int views) {
this.views = views;
}
@DynamoDBAttribute(attributeName = &quot;Replies&quot;)
public int getReplies() {
return replies;
}
public void setReplies(int replies) {
this.replies = replies;
}
}
@DynamoDBTable(tableName = &quot;Forum&quot;)
public static class Forum {
private String name;
private String category;
private int threads;
@DynamoDBHashKey(attributeName = &quot;Name&quot;)
public String getName() {
return name;
}
public void setName(String name) {
this.name = name;
}
@DynamoDBAttribute(attributeName = &quot;Category&quot;)
public String getCategory() {
return category;
}
public void setCategory(String category) {
this.category = category;
}
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@DynamoDBAttribute(attributeName = &quot;Threads&quot;)
public int getThreads() {
return threads;
}
}
}
public void setThreads(int threads) {
this.threads = threads;
}
Optimistic Locking With Version Number
Optimistic locking is a strategy to ensure that the client-side item that you are updating (or deleting)
is the same as the item in DynamoDB. If you use this strategy, then your database writes are protected
from being overwritten by the writes of others — and vice-versa.
With optimistic locking, each item has an attribute that acts as a version number. If you retrieve an item
from a table, the application records the version number of that item. You can update the item, but only
if the version number on the server side has not changed. If there is a version mismatch, it means that
someone else has modiﬁed the item before you did; the update attempt fails, because you have a stale
version of the item. If this happens, you simply try again by retrieving the item and then attempting to
update it. Optimistic locking prevents you from accidentally overwriting changes that were made by
others; it also prevents others from accidentally overwriting your changes.
To support optimistic locking, the AWS SDK for Java provides the @DynamoDBVersionAttribute
annotation. In the mapping class for your table, you designate one property to store the version number,
and mark it using this annotation. When you save an object, the corresponding item in the DynamoDB
table will have an attribute that stores the version number. The DynamoDBMapper assigns a version
number when you ﬁrst save the object, and it automatically increments the version number each time
you update the item. Your update or delete requests will succeed only if the client-side object version
matches the corresponding version number of the item in the DynamoDB table.
ConditionalCheckFailedException is thrown if:
• You use optimistic locking with @DynamoDBVersionAttribute and the version value on the server is
diﬀerent from the value on the client side.
• You specify your own conditional constraints while saving data by using DynamoDBMapper with
DynamoDBSaveExpression and these constraints failed.
For example, the following Java code snippet deﬁnes a CatalogItem class that has several properties.
The Version property is tagged with the @DynamoDBVersionAttribute annotation.
Example
@DynamoDBTable(tableName=&quot;ProductCatalog&quot;)
public class CatalogItem {
private
private
private
private
private
private
Integer id;
String title;
String ISBN;
Set&lt;String&gt; bookAuthors;
String someProp;
Long version;
@DynamoDBHashKey(attributeName=&quot;Id&quot;)
public Integer getId() { return id; }
public void setId(Integer Id) { this.id = Id; }
@DynamoDBAttribute(attributeName=&quot;Title&quot;)
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public String getTitle() { return title; }
public void setTitle(String title) { this.title = title; }
@DynamoDBAttribute(attributeName=&quot;ISBN&quot;)
public String getISBN() { return ISBN; }
public void setISBN(String ISBN) { this.ISBN = ISBN;}
@DynamoDBAttribute(attributeName = &quot;Authors&quot;)
public Set&lt;String&gt; getBookAuthors() { return bookAuthors; }
public void setBookAuthors(Set&lt;String&gt; bookAuthors) { this.bookAuthors = bookAuthors; }
@DynamoDBIgnore
public String getSomeProp() { return someProp;}
public void setSomeProp(String someProp) {this.someProp = someProp;}
}
@DynamoDBVersionAttribute
public Long getVersion() { return version; }
public void setVersion(Long version) { this.version = version;}
You can apply the @DynamoDBVersionAttribute annotation to nullable types provided by the primitive
wrappers classes that provide a nullable type, such as Long and Integer.
Optimistic locking has the following impact on these DynamoDBMapper methods:
• save — For a new item, the DynamoDBMapper assigns an initial version number 1. If you retrieve an
item, update one or more of its properties and attempt to save the changes, the save operation
succeeds only if the version number on the client-side and the server-side match. The DynamoDBMapper
increments the version number automatically.
• delete — The delete method takes an object as parameter and the DynamoDBMapper
performs a version check before deleting the item. The version check can be disabled if
DynamoDBMapperConfig.SaveBehavior.CLOBBER is speciﬁed in the request.
The internal implementation of optimistic locking within DynamoDBMapper uses conditional update and
conditional delete support provided by DynamoDB.
Disabling Optimistic Locking
To disable optimistic locking, you can change the DynamoDBMapperConfig.SaveBehavior enumeration
value from UPDATE to CLOBBER. You can do this by creating a DynamoDBMapperConfig instance
that skips version checking and use this instance for all your requests. For information about
DynamoDBMapperConfig.SaveBehavior and other optional DynamoDBMapper parameters, see Optional
Conﬁguration Settings for DynamoDBMapper (p. 209).
You can also set locking behavior for a speciﬁc operation only. For example, the following Java snippet
uses the DynamoDBMapper to save a catalog item. It speciﬁes DynamoDBMapperConfig.SaveBehavior by
adding the optional DynamoDBMapperConfig parameter to the save method.
Example
DynamoDBMapper mapper = new DynamoDBMapper(client);
// Load a catalog item.
CatalogItem item = mapper.load(CatalogItem.class, 101);
item.setTitle(&quot;This is a new title for the item&quot;);
...
// Save the item.
mapper.save(item,
new DynamoDBMapperConfig(
DynamoDBMapperConfig.SaveBehavior.CLOBBER));
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Mapping Arbitrary Data
In addition to the supported Java types (see Supported Data Types (p. 197)), you can use types in your
application for which there is no direct mapping to the DynamoDB types. To map these types, you must
provide an implementation that converts your complex type to a DynamoDB supported type and viceversa, and annotate the complex type accessor method using the @DynamoDBTypeConverted annotation.
The converter code transforms data when objects are saved or loaded. It is also used for all operations
that consume complex types. Note that when comparing data during query and scan operations, the
comparisons are made against the data stored in DynamoDB.
For example, consider the following CatalogItem class that deﬁnes a property, Dimension, that is of
DimensionType. This property stores the item dimensions, as height, width, and thickness. Assume that
you decide to store these item dimensions as a string (such as 8.5x11x.05) in DynamoDB. The following
example provides converter code that converts the DimensionType object to a string and a string to the
DimensionType.
Note
This code sample assumes that you have already loaded data into DynamoDB for your account
by following the instructions in the Creating Tables and Loading Sample Data (p. 280) section.
For step-by-step instructions to run the following example, see Java Code Samples (p. 285).
Example
package com.amazonaws.codesamples.datamodeling;
import
import
import
import
java.io.IOException;
java.util.Arrays;
java.util.HashSet;
java.util.Set;
import
import
import
import
import
import
import
import
import
com.amazonaws.regions.Regions;
com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBAttribute;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBHashKey;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBMapper;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBTypeConverted;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBTypeConverter;
com.amazonaws.services.dynamodbv2.datamodeling.DynamoDBTable;
public class DynamoDBMapperExample {
static AmazonDynamoDB client;
public static void main(String[] args) throws IOException {
// Set the AWS region you want to access.
Regions usWest2 = Regions.US_WEST_2;
client = AmazonDynamoDBClientBuilder.standard().withRegion(usWest2).build();
DimensionType dimType = new DimensionType();
dimType.setHeight(&quot;8.00&quot;);
dimType.setLength(&quot;11.0&quot;);
dimType.setThickness(&quot;1.0&quot;);
Book book = new Book();
book.setId(502);
book.setTitle(&quot;Book 502&quot;);
book.setISBN(&quot;555-5555555555&quot;);
book.setBookAuthors(new HashSet&lt;String&gt;(Arrays.asList(&quot;Author1&quot;, &quot;Author2&quot;)));
book.setDimensions(dimType);
DynamoDBMapper mapper = new DynamoDBMapper(client);
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mapper.save(book);
Book bookRetrieved = mapper.load(Book.class, 502);
System.out.println(&quot;Book info: &quot; + &quot;\n&quot; + bookRetrieved);
bookRetrieved.getDimensions().setHeight(&quot;9.0&quot;);
bookRetrieved.getDimensions().setLength(&quot;12.0&quot;);
bookRetrieved.getDimensions().setThickness(&quot;2.0&quot;);
mapper.save(bookRetrieved);
}
bookRetrieved = mapper.load(Book.class, 502);
System.out.println(&quot;Updated book info: &quot; + &quot;\n&quot; + bookRetrieved);
@DynamoDBTable(tableName = &quot;ProductCatalog&quot;)
public static class Book {
private int id;
private String title;
private String ISBN;
private Set&lt;String&gt; bookAuthors;
private DimensionType dimensionType;
// Partition key
@DynamoDBHashKey(attributeName = &quot;Id&quot;)
public int getId() {
return id;
}
public void setId(int id) {
this.id = id;
}
@DynamoDBAttribute(attributeName = &quot;Title&quot;)
public String getTitle() {
return title;
}
public void setTitle(String title) {
this.title = title;
}
@DynamoDBAttribute(attributeName = &quot;ISBN&quot;)
public String getISBN() {
return ISBN;
}
public void setISBN(String ISBN) {
this.ISBN = ISBN;
}
@DynamoDBAttribute(attributeName = &quot;Authors&quot;)
public Set&lt;String&gt; getBookAuthors() {
return bookAuthors;
}
public void setBookAuthors(Set&lt;String&gt; bookAuthors) {
this.bookAuthors = bookAuthors;
}
@DynamoDBTypeConverted(converter = DimensionTypeConverter.class)
@DynamoDBAttribute(attributeName = &quot;Dimensions&quot;)
public DimensionType getDimensions() {
return dimensionType;
}
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@DynamoDBAttribute(attributeName = &quot;Dimensions&quot;)
public void setDimensions(DimensionType dimensionType) {
this.dimensionType = dimensionType;
}
@Override
public String toString() {
return &quot;Book [ISBN=&quot; + ISBN + &quot;, bookAuthors=&quot; + bookAuthors + &quot;,
dimensionType= &quot;
+ dimensionType.getHeight() + &quot; X &quot; + dimensionType.getLength() + &quot; X &quot; +
dimensionType.getThickness()
+ &quot;, Id=&quot; + id + &quot;, Title=&quot; + title + &quot;]&quot;;
}
}
static public class DimensionType {
private String length;
private String height;
private String thickness;
public String getLength() {
return length;
}
public void setLength(String length) {
this.length = length;
}
public String getHeight() {
return height;
}
public void setHeight(String height) {
this.height = height;
}
public String getThickness() {
return thickness;
}
}
public void setThickness(String thickness) {
this.thickness = thickness;
}
// Converts the complex type DimensionType to a string and vice-versa.
static public class DimensionTypeConverter implements DynamoDBTypeConverter&lt;String,
DimensionType&gt; {
@Override
public String convert(DimensionType object) {
DimensionType itemDimensions = (DimensionType) object;
String dimension = null;
try {
if (itemDimensions != null) {
dimension = String.format(&quot;%s x %s x %s&quot;, itemDimensions.getLength(),
itemDimensions.getHeight(),
itemDimensions.getThickness());
}
}
catch (Exception e) {
e.printStackTrace();
}
return dimension;
}
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@Override
public DimensionType unconvert(String s) {
DimensionType itemDimension = new DimensionType();
try {
if (s != null &amp;&amp; s.length() != 0) {
String[] data = s.split(&quot;x&quot;);
itemDimension.setLength(data[0].trim());
itemDimension.setHeight(data[1].trim());
itemDimension.setThickness(data[2].trim());
}
}
catch (Exception e) {
e.printStackTrace();
}
}
}
}
return itemDimension;
.NET: Document Model
Topics
• Operations Not Supported by the Document Model (p. 232)
• Working with Items in DynamoDB Using the AWS SDK for .NET Document Model (p. 232)
• Getting an Item - Table.GetItem (p. 236)
• Deleting an Item - Table.DeleteItem (p. 237)
• Updating an Item - Table.UpdateItem (p. 238)
• Batch Write - Putting and Deleting Multiple Items (p. 239)
• Example: CRUD Operations Using the AWS SDK for .NET Document Model (p. 241)
• Example: Batch Operations Using AWS SDK for .NET Document Model API (p. 244)
• Querying Tables in DynamoDB Using the AWS SDK for .NET Document Model (p. 245)
The AWS SDK for .NET provides document model classes that wrap some of the low-level DynamoDB
operations, to further simplify your coding. In the document model, the primary classes are Table and
Document. The Table class provides data operation methods such as PutItem, GetItem, and DeleteItem. It
also provides the Query and the Scan methods. The Document class represents a single item in a table.
The preceding document model classes are available in the Amazon.DynamoDBv2.DocumentModel
namespace.
Operations Not Supported by the Document Model
You cannot use the document model classes to create, update, and delete tables. The document model
does support most common data operations, however.
Working with Items in DynamoDB Using the AWS SDK for .NET
Document Model
Topics
• Putting an Item - Table.PutItem Method (p. 233)
• Specifying Optional Parameters (p. 235)
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To perform data operations using the document model, you must ﬁrst call the Table.LoadTable method,
which creates an instance of the Table class that represents a speciﬁc table. The following C# snippet
creates a Table object that represents the ProductCatalog table in DynamoDB.
Example
Table table = Table.LoadTable(client, &quot;ProductCatalog&quot;);
Note
In general, you use the LoadTable method once at the beginning of your application because it
makes a DescribeTable call that adds to the round trip to DynamoDB.
You can then use the table object to perform various data operations. Each of these data operations have
two types of overloads; one that takes the minimum required parameters and another that also takes
operation speciﬁc optional conﬁguration information. For example, to retrieve an item, you must provide
the table's primary key value in which case you can use the following GetItem overload:
Example
// Get the item from a table that has a primary key that is composed of only a partition
key.
Table.GetItem(Primitive partitionKey);
// Get the item from a table whose primary key is composed of both a partition key and sort
key.
Table.GetItem(Primitive partitionKey, Primitive sortKey);
You can also pass optional parameters to these methods. For example, the preceding GetItem returns
the entire item including all its attributes. You can optionally specify a list of attributes to retrieve. In this
case, you use the following GetItem overload that takes in the operation speciﬁc conﬁguration object
parameter:
Example
// Configuration object that specifies optional parameters.
GetItemOperationConfig config = new GetItemOperationConfig()
{
AttributesToGet = new List&lt;string&gt;() { &quot;Id&quot;, &quot;Title&quot; },
};
// Pass in the configuration to the GetItem method.
// 1. Table that has only a partition key as primary key.
Table.GetItem(Primitive partitionKey, GetItemOperationConfig config);
// 2. Table that has both a partition key and a sort key.
Table.GetItem(Primitive partitionKey, Primitive sortKey, GetItemOperationConfig config);
You can use the conﬁguration object to specify several optional parameters such as request a speciﬁc list
of attributes or specify the page size (number of items per page). Each data operation method has its
own conﬁguration class. For example, the GetItemOperationConfig class enables you to provide options
for the GetItem operation and the PutItemOperationConfig class enables you to provide optional
parameters for the PutItem operation.
The following sections discuss each of the data operations that are supported by the Table class.
Putting an Item - Table.PutItem Method
The PutItem method uploads the input Document instance to the table. If an item that has a primary key
that is speciﬁed in the input Document exists in the table, then the PutItem operation replaces the entire
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existing item. The new item will be identical to the Document object that you provided to the PutItem
method. Note that this means that if your original item had any extra attributes, they are no longer
present in the new item. The following are the steps to put a new item into a table using the AWS SDK
for .NET document model.
1. Execute the Table.LoadTable method that provides the table name in which you want to put an item.
2. Create a Document object that has a list of attribute names and their values.
3. Execute Table.PutItem by providing the Document instance as a parameter.
The following C# code snippet demonstrates the preceding tasks. The example uploads an item to the
ProductCatalog table.
Example
Table table = Table.LoadTable(client, &quot;ProductCatalog&quot;);
var book = new Document();
book[&quot;Id&quot;] = 101;
book[&quot;Title&quot;] = &quot;Book 101 Title&quot;;
book[&quot;ISBN&quot;] = &quot;11-11-11-11&quot;;
book[&quot;Authors&quot;] = new List&lt;string&gt; { &quot;Author 1&quot;, &quot;Author 2&quot; };
book[&quot;InStock&quot;] = new DynamoDBBool(true);
book[&quot;QuantityOnHand&quot;] = new DynamoDBNull();
table.PutItem(book);
In the preceding example, the Document instance creates an item that has Number, String, String Set,
Boolean, and Null attributes. (Null is used to indicate that the QuantityOnHand for this product is
unknown.) For Boolean and Null, use the constructor methods DynamoDBBool and DynamoDBNull.
In DynamoDB, the List and Map data types can contain elements composed of other data types. Here is
how to map these data types to the document model API:.
• List — use the DynamoDBList constructor.
• Map — use the Document constructor.
You can modify the preceding example to add a List attribute to the item. To do this, use a DynamoDBList
constructor, as shown in the following code snippet:
Example
Table table = Table.LoadTable(client, &quot;ProductCatalog&quot;);
var book = new Document();
book[&quot;Id&quot;] = 101;
/*other attributes omitted for brevity...*/
var relatedItems = new DynamoDBList();
relatedItems.Add(341);
relatedItems.Add(472);
relatedItems.Add(649);
item.Add(&quot;RelatedItems&quot;, relatedItems);
table.PutItem(book);
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To add a Map attribute to the book, you deﬁne another Document. The following code snippet illustrates
how to do this.
Example
Table table = Table.LoadTable(client, &quot;ProductCatalog&quot;);
var book = new Document();
book[&quot;Id&quot;] = 101;
/*other attributes omitted for brevity...*/
var pictures = new Document();
pictures.Add(&quot;FrontView&quot;, &quot;http://example.com/products/101_front.jpg&quot; );
pictures.Add(&quot;RearView&quot;, &quot;http://example.com/products/101_rear.jpg&quot; );
book.Add(&quot;Pictures&quot;, pictures);
table.PutItem(book);
These examples are based on the item shown in Specifying Item Attributes (p. 338). The document
model lets you create complex nested attributes, such as the ProductReviews attribute shown in the case
study.
Specifying Optional Parameters
You can conﬁgure optional parameters for the PutItem operation by adding the
PutItemOperationConfig parameter. For a complete list of optional parameters, see PutItem. The
following C# code snippet puts an item in the ProductCatalog table. It speciﬁes the following optional
parameter:
• The ConditionalExpression parameter to make this a conditional put request. The example creates
an expression that speciﬁes the ISBN attribute must have a speciﬁc value that has to be present in the
item that you are replacing.
Example
Table table = Table.LoadTable(client, &quot;ProductCatalog&quot;);
var book = new Document();
book[&quot;Id&quot;] = 555;
book[&quot;Title&quot;] = &quot;Book 555 Title&quot;;
book[&quot;Price&quot;] = &quot;25.00&quot;;
book[&quot;ISBN&quot;] = &quot;55-55-55-55&quot;;
book[&quot;Name&quot;] = &quot;Item 1 updated&quot;;
book[&quot;Authors&quot;] = new List&lt;string&gt; { &quot;Author x&quot;, &quot;Author y&quot; };
book[&quot;InStock&quot;] = new DynamoDBBool(true);
book[&quot;QuantityOnHand&quot;] = new DynamoDBNull();
// Create a condition expression for the optional conditional put operation.
Expression expr = new Expression();
expr.ExpressionStatement = &quot;ISBN = :val&quot;;
expr.ExpressionAttributeValues[&quot;:val&quot;] = &quot;55-55-55-55&quot;;
PutItemOperationConfig config = new PutItemOperationConfig()
{
// Optional parameter.
ConditionalExpression = expr
};
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table.PutItem(book, config);
Getting an Item - Table.GetItem
The GetItem operation retrieves an item as a Document instance. You must provide the primary key of the
item that you want to retrieve as shown in the following C# code snippet:
Example
Table table = Table.LoadTable(client, &quot;ProductCatalog&quot;);
Document document = table.GetItem(101); // Primary key 101.
The GetItem operation returns all the attributes of the item and performs an eventually consistent read
(see Read Consistency (p. 15)) by default.
Specifying Optional Parameters
You can conﬁgure additional options for the GetItem operation by adding the GetItemOperationConfig
parameter. For a complete list of optional parameters, see GetItem. The following C# code snippet
retrieves an item from the ProductCatalog table. It speciﬁes the GetItemOperationConfig to provide the
following optional parameters:
• The AttributesToGet parameter to retrieve only the speciﬁed attributes.
• The ConsistentRead parameter to request the latest values for all the speciﬁed attributes. To learn
more about data consistency, see Read Consistency (p. 15).
Example
Table table = Table.LoadTable(client, &quot;ProductCatalog&quot;);
GetItemOperationConfig config = new GetItemOperationConfig()
{
AttributesToGet = new List&lt;string&gt;() { &quot;Id&quot;, &quot;Title&quot;, &quot;Authors&quot;, &quot;InStock&quot;,
&quot;QuantityOnHand&quot; },
ConsistentRead = true
};
Document doc = table.GetItem(101, config);
When you retrieve an item using the document model API, you can access individual elements within the
Document object is returned:
Example
int id = doc[&quot;Id&quot;].AsInt();
string title = doc[&quot;Title&quot;].AsString();
List&lt;string&gt; authors = doc[&quot;Authors&quot;].AsListOfString();
bool inStock = doc[&quot;InStock&quot;].AsBoolean();
DynamoDBNull quantityOnHand = doc[&quot;QuantityOnHand&quot;].AsDynamoDBNull();
For attributes that are of type List or Map, here is how to map these attributes to the document model
API:
• List — use the AsDynamoDBList method.
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• Map — use the AsDocument method.
The following code snippet shows how to retrieve a List (RelatedItems) and a Map (Pictures) from the
Document object:
Example
DynamoDBList relatedItems = doc[&quot;RelatedItems&quot;].AsDynamoDBList();
Document pictures = doc[&quot;Pictures&quot;].AsDocument();
Deleting an Item - Table.DeleteItem
The DeleteItem operation deletes an item from a table. You can either pass the item's primary key as a
parameter or if you have already read an item and have the corresponding Document object, you can pass
it as a parameter to the DeleteItem method as shown in the following C# code snippet.
Example
Table table = Table.LoadTable(client, &quot;ProductCatalog&quot;);
// Retrieve a book (a Document instance)
Document document = table.GetItem(111);
// 1) Delete using the Document instance.
table.DeleteItem(document);
// 2) Delete using the primary key.
int partitionKey = 222;
table.DeleteItem(partitionKey)
Specifying Optional Parameters
You can conﬁgure additional options for the Delete operation by adding the
DeleteItemOperationConfig parameter. For a complete list of optional parameters, see DeleteTable. The
following C# code snippet speciﬁes the two following optional parameters:
• The ConditionalExpression parameter to ensure that the book item being deleted has a speciﬁc value
for the ISBN attribute.
• The ReturnValues parameter to request that the Delete method return the item that it deleted.
Example
Table table = Table.LoadTable(client, &quot;ProductCatalog&quot;);
int partitionKey = 111;
Expression expr = new Expression();
expr.ExpressionStatement = &quot;ISBN = :val&quot;;
expr.ExpressionAttributeValues[&quot;:val&quot;] = &quot;11-11-11-11&quot;;
// Specify optional parameters for Delete operation.
DeleteItemOperationConfig config = new DeleteItemOperationConfig
{
ConditionalExpression = expr,
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ReturnValues = ReturnValues.AllOldAttributes // This is the only supported value when
using the document model.
};
// Delete the book.
Document d = table.DeleteItem(partitionKey, config);
Updating an Item - Table.UpdateItem
The UpdateItem operation updates an existing item if it is present. If the item that has the speciﬁed
primary key is not found, the UpdateItem operation adds a new item.
You can use the UpdateItem operation to update existing attribute values, add new attributes to the
existing collection, or delete attributes from the existing collection. You provide these updates by
creating a Document instance that describes the updates you wish to perform.
The UpdateItem action uses the following guidelines:
• If the item does not exist, UpdateItem adds a new item using the primary key that is speciﬁed in the
input.
• If the item exists, UpdateItem applies the updates as follows:
• Replaces the existing attribute values with the values in the update.
• If an attribute that you provide in the input does not exist, it adds a new attribute to the item.
• If the input attribute value is null, it deletes the attributes, if it is present.
Note
This mid-level UpdateItem operation does not support the Add action (see UpdateItem)
supported by the underlying DynamoDB operation.
Note
The PutItem operation (Putting an Item - Table.PutItem Method (p. 233)) can also can perform
an update. If you call PutItem to upload an item and the primary key exists, the PutItem
operation replaces the entire item. Note that, if there are attributes in the existing item and
those attributes are not speciﬁed on the Document that is being put, the PutItem operation
deletes those attributes. However, UpdateItem only updates the speciﬁed input attributes. Any
other existing attributes of that item will remain unchanged.
The following are the steps to update an item using the AWS SDK for .NET document model.
1. Execute the Table.LoadTable method by providing the name of the table in which you want to
perform the update operation.
2. Create a Document instance by providing all the updates that you wish to perform.
To delete an existing attribute, specify the attribute value as null.
3. Call the Table.UpdateItem method and provide the Document instance as an input parameter.
You must provide the primary key either in the Document instance or explicitly as a parameter.
The following C# code snippet demonstrates the preceding tasks. The code sample updates an item in
the Book table. The UpdateItem operation updates the existing Authors attribute, deletes the PageCount
attribute, and adds a new attribute XYZ. The Document instance includes the primary key of the book to
update.
Example
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Table table = Table.LoadTable(client, &quot;ProductCatalog&quot;);
var book = new Document();
// Set the attributes that you wish to update.
book[&quot;Id&quot;] = 111; // Primary key.
// Replace the authors attribute.
book[&quot;Authors&quot;] = new List&lt;string&gt; { &quot;Author x&quot;, &quot;Author y&quot; };
// Add a new attribute.
book[&quot;XYZ&quot;] = 12345;
// Delete the existing PageCount attribute.
book[&quot;PageCount&quot;] = null;
table.Update(book);
Specifying Optional Parameters
You can conﬁgure additional options for the UpdateItem operation by adding the
UpdateItemOperationConfig parameter. For a complete list of optional parameters, see UpdateItem.
The following C# code snippet updates a book item price to 25. It speciﬁes the two following optional
parameters:
• The ConditionalExpression parameter that identiﬁes the Price attribute with value 20 that you
expect to be present.
• The ReturnValues parameter to request the UpdateItem operation to return the item that is updated.
Example
Table table = Table.LoadTable(client, &quot;ProductCatalog&quot;);
string partitionKey = &quot;111&quot;;
var book = new Document();
book[&quot;Id&quot;] = partitionKey;
book[&quot;Price&quot;] = 25;
Expression expr = new Expression();
expr.ExpressionStatement = &quot;Price = :val&quot;;
expr.ExpressionAttributeValues[&quot;:val&quot;] = 20&quot;;
UpdateOperationConfig config = new UpdateOperationConfig()
{
ConditionalExpression = expr,
ReturnValues = ReturnValues.AllOldAttributes
};
Document d1 = table.Update(book, config);
Batch Write - Putting and Deleting Multiple Items
Batch write refers to putting and deleting multiple items in a batch. The operation enables you to put
and delete multiple items from one or more tables in a single call. The following are the steps to put or
delete multiple items from a table using the AWS SDK for .NET document model API.
1. Create a Table object by executing the Table.LoadTable method by providing the name of the table in
which you want to perform the batch operation.
2. Execute the CreateBatchWrite method on the table instance you created in the preceding step and
create DocumentBatchWrite object.
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3. Use DocumentBatchWrite object methods to specify documents you wish to upload or delete.
4. Call the DocumentBatchWrite.Execute method to execute the batch operation.
When using the document model API, you can specify any number of operations in a batch. However,
note that DynamoDB limits the number of operations in a batch and the total size of the batch in a
batch operation. For more information about the speciﬁc limits, see BatchWriteItem. If the document
model API detects your batch write request exceeded the number of allowed write requests or the
HTTP payload size of a batch exceeded the limit allowed by BatchWriteItem, it breaks the batch in
to several smaller batches. Additionally, if a response to a batch write returns unprocessed items, the
document model API will automatically send another batch request with those unprocessed items.
The following C# code snippet demonstrates the preceding steps. The code snippet uses batch write
operation to perform two writes; upload a book item and delete another book item.
Table productCatalog = Table.LoadTable(client, &quot;ProductCatalog&quot;);
var batchWrite = productCatalog.CreateBatchWrite();
var book1 = new Document();
book1[&quot;Id&quot;] = 902;
book1[&quot;Title&quot;] = &quot;My book1 in batch write using .NET document model&quot;;
book1[&quot;Price&quot;] = 10;
book1[&quot;Authors&quot;] = new List&lt;string&gt; { &quot;Author 1&quot;, &quot;Author 2&quot;, &quot;Author 3&quot; };
book1[&quot;InStock&quot;] = new DynamoDBBool(true);
book1[&quot;QuantityOnHand&quot;] = 5;
batchWrite.AddDocumentToPut(book1);
// specify delete item using overload that takes PK.
batchWrite.AddKeyToDelete(12345);
batchWrite.Execute();
For a working example, see Example: Batch Operations Using AWS SDK for .NET Document Model
API (p. 244).
You can use the batch write operation to perform put and delete operations on multiple tables. The
following are the steps to put or delete multiple items from multiple table using the AWS SDK for .NET
document model.
1. You create DocumentBatchWrite instance for each table in which you want to put or delete multiple
items as described in the preceding procedure.
2. Create an instance of the MultiTableDocumentBatchWrite and add the individual DocumentBatchWrite
objects in it.
3. Execute the MultiTableDocumentBatchWrite.Execute method.
The following C# code snippet demonstrates the preceding steps. The code snippet uses batch write
operation to perform the following write operations:
• Put a new item in the Forum table item
• Put an item in the Thread table and delete an item from the same table.
// 1. Specify item to add in the Forum table.
Table forum = Table.LoadTable(client, &quot;Forum&quot;);
var forumBatchWrite = forum.CreateBatchWrite();
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var forum1 = new Document();
forum1[&quot;Name&quot;] = &quot;Test BatchWrite Forum&quot;;
forum1[&quot;Threads&quot;] = 0;
forumBatchWrite.AddDocumentToPut(forum1);
// 2a. Specify item to add in the Thread table.
Table thread = Table.LoadTable(client, &quot;Thread&quot;);
var threadBatchWrite = thread.CreateBatchWrite();
var thread1 = new Document();
thread1[&quot;ForumName&quot;] = &quot;Amazon S3 forum&quot;;
thread1[&quot;Subject&quot;] = &quot;My sample question&quot;;
thread1[&quot;Message&quot;] = &quot;Message text&quot;;
thread1[&quot;KeywordTags&quot;] = new List&lt;string&gt;{ &quot;Amazon S3&quot;, &quot;Bucket&quot; };
threadBatchWrite.AddDocumentToPut(thread1);
// 2b. Specify item to delete from the Thread table.
threadBatchWrite.AddKeyToDelete(&quot;someForumName&quot;, &quot;someSubject&quot;);
// 3. Create multi-table batch.
var superBatch = new MultiTableDocumentBatchWrite();
superBatch.AddBatch(forumBatchWrite);
superBatch.AddBatch(threadBatchWrite);
superBatch.Execute();
Example: CRUD Operations Using the AWS SDK for .NET
Document Model
The following C# code example performs the following actions:
• Create a book item in the ProductCatalog table.
• Retrieve the book item.
• Update the book item. The code example shows a normal update that adds new attributes and
updates existing attributes. It also shows a conditional update which updates the book price only if the
existing price value is as speciﬁed in the code.
• Delete the book item.
For step-by-step instructions to test the following sample, see .NET Code Samples (p. 287).
Example
using
using
using
using
using
using
System;
System.Collections.Generic;
System.Linq;
Amazon.DynamoDBv2;
Amazon.DynamoDBv2.DocumentModel;
Amazon.Runtime;
namespace com.amazonaws.codesamples
{
class MidlevelItemCRUD
{
private static AmazonDynamoDBClient client = new AmazonDynamoDBClient();
private static string tableName = &quot;ProductCatalog&quot;;
// The sample uses the following id PK value to add book item.
private static int sampleBookId = 555;
static void Main(string[] args)
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{
try
{
Table productCatalog = Table.LoadTable(client, tableName);
CreateBookItem(productCatalog);
RetrieveBook(productCatalog);
// Couple of sample updates.
UpdateMultipleAttributes(productCatalog);
UpdateBookPriceConditionally(productCatalog);
// Delete.
DeleteBook(productCatalog);
Console.WriteLine(&quot;To continue, press Enter&quot;);
Console.ReadLine();
}
}
catch (AmazonDynamoDBException e) { Console.WriteLine(e.Message); }
catch (AmazonServiceException e) { Console.WriteLine(e.Message); }
catch (Exception e) { Console.WriteLine(e.Message); }
// Creates a sample book item.
private static void CreateBookItem(Table productCatalog)
{
Console.WriteLine(&quot;\n*** Executing CreateBookItem() ***&quot;);
var book = new Document();
book[&quot;Id&quot;] = sampleBookId;
book[&quot;Title&quot;] = &quot;Book &quot; + sampleBookId;
book[&quot;Price&quot;] = 19.99;
book[&quot;ISBN&quot;] = &quot;111-1111111111&quot;;
book[&quot;Authors&quot;] = new List&lt;string&gt; { &quot;Author 1&quot;, &quot;Author 2&quot;, &quot;Author 3&quot; };
book[&quot;PageCount&quot;] = 500;
book[&quot;Dimensions&quot;] = &quot;8.5x11x.5&quot;;
book[&quot;InPublication&quot;] = new DynamoDBBool(true);
book[&quot;InStock&quot;] = new DynamoDBBool(false);
book[&quot;QuantityOnHand&quot;] = 0;
}
productCatalog.PutItem(book);
private static void RetrieveBook(Table productCatalog)
{
Console.WriteLine(&quot;\n*** Executing RetrieveBook() ***&quot;);
// Optional configuration.
GetItemOperationConfig config = new GetItemOperationConfig
{
AttributesToGet = new List&lt;string&gt; { &quot;Id&quot;, &quot;ISBN&quot;, &quot;Title&quot;, &quot;Authors&quot;,
&quot;Price&quot; },
ConsistentRead = true
};
Document document = productCatalog.GetItem(sampleBookId, config);
Console.WriteLine(&quot;RetrieveBook: Printing book retrieved...&quot;);
PrintDocument(document);
}
private static void UpdateMultipleAttributes(Table productCatalog)
{
Console.WriteLine(&quot;\n*** Executing UpdateMultipleAttributes() ***&quot;);
Console.WriteLine(&quot;\nUpdating multiple attributes....&quot;);
int partitionKey = sampleBookId;
var book = new Document();
book[&quot;Id&quot;] = partitionKey;
// List of attribute updates.
// The following replaces the existing authors list.
book[&quot;Authors&quot;] = new List&lt;string&gt; { &quot;Author x&quot;, &quot;Author y&quot; };
book[&quot;newAttribute&quot;] = &quot;New Value&quot;;
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book[&quot;ISBN&quot;] = null; // Remove it.
// Optional parameters.
UpdateItemOperationConfig config = new UpdateItemOperationConfig
{
// Get updated item in response.
ReturnValues = ReturnValues.AllNewAttributes
};
Document updatedBook = productCatalog.UpdateItem(book, config);
Console.WriteLine(&quot;UpdateMultipleAttributes: Printing item after
updates ...&quot;);
PrintDocument(updatedBook);
}
private static void UpdateBookPriceConditionally(Table productCatalog)
{
Console.WriteLine(&quot;\n*** Executing UpdateBookPriceConditionally() ***&quot;);
int partitionKey = sampleBookId;
var book = new Document();
book[&quot;Id&quot;] = partitionKey;
book[&quot;Price&quot;] = 29.99;
// For conditional price update, creating a condition expression.
Expression expr = new Expression();
expr.ExpressionStatement = &quot;Price = :val&quot;;
expr.ExpressionAttributeValues[&quot;:val&quot;] = 19.00;
// Optional parameters.
UpdateItemOperationConfig config = new UpdateItemOperationConfig
{
ConditionalExpression = expr,
ReturnValues = ReturnValues.AllNewAttributes
};
Document updatedBook = productCatalog.UpdateItem(book, config);
Console.WriteLine(&quot;UpdateBookPriceConditionally: Printing item whose price was
conditionally updated&quot;);
PrintDocument(updatedBook);
}
private static void DeleteBook(Table productCatalog)
{
Console.WriteLine(&quot;\n*** Executing DeleteBook() ***&quot;);
// Optional configuration.
DeleteItemOperationConfig config = new DeleteItemOperationConfig
{
// Return the deleted item.
ReturnValues = ReturnValues.AllOldAttributes
};
Document document = productCatalog.DeleteItem(sampleBookId, config);
Console.WriteLine(&quot;DeleteBook: Printing deleted just deleted...&quot;);
PrintDocument(document);
}
private static void PrintDocument(Document updatedDocument)
{
foreach (var attribute in updatedDocument.GetAttributeNames())
{
string stringValue = null;
var value = updatedDocument[attribute];
if (value is Primitive)
stringValue = value.AsPrimitive().Value.ToString();
else if (value is PrimitiveList)
stringValue = string.Join(&quot;,&quot;, (from primitive
in value.AsPrimitiveList().Entries
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}
}
}
}
select primitive.Value).ToArray());
Console.WriteLine(&quot;{0} - {1}&quot;, attribute, stringValue);
Example: Batch Operations Using AWS SDK for .NET Document
Model API
Topics
• Example: Batch Write Using AWS SDK for .NET Document Model (p. 244)
Example: Batch Write Using AWS SDK for .NET Document Model
The following C# code example illustrates single table and multi-table batch write operations. The
example performs the following tasks:
• To illustrate a single table batch write, it adds two items to the ProductCatalog table.
• To illustrate a multi-table batch write, it adds an item to both the Forum and Thread tables and
deletes and item from the Thread table.
If you followed the steps in Creating Tables and Loading Sample Data (p. 280), you already have
the ProductCatalog, Forum and Thread tables created. You can also create these sample tables
programmatically. For more information, see Creating Example Tables and Uploading Data Using the
AWS SDK for .NET (p. 749). For step-by-step instructions to test the following sample, see .NET Code
Samples (p. 287).
Example
using
using
using
using
using
System;
System.Collections.Generic;
Amazon.DynamoDBv2;
Amazon.DynamoDBv2.DocumentModel;
Amazon.Runtime;
namespace com.amazonaws.codesamples
{
class MidLevelBatchWriteItem
{
private static AmazonDynamoDBClient client = new AmazonDynamoDBClient();
static void Main(string[] args)
{
try
{
SingleTableBatchWrite();
MultiTableBatchWrite();
}
catch (AmazonDynamoDBException e) { Console.WriteLine(e.Message); }
catch (AmazonServiceException e) { Console.WriteLine(e.Message); }
catch (Exception e) { Console.WriteLine(e.Message); }
}
Console.WriteLine(&quot;To continue, press Enter&quot;);
Console.ReadLine();
private static void SingleTableBatchWrite()
{
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Table productCatalog = Table.LoadTable(client, &quot;ProductCatalog&quot;);
var batchWrite = productCatalog.CreateBatchWrite();
var book1 = new Document();
book1[&quot;Id&quot;] = 902;
book1[&quot;Title&quot;] = &quot;My book1 in batch write using .NET helper classes&quot;;
book1[&quot;ISBN&quot;] = &quot;902-11-11-1111&quot;;
book1[&quot;Price&quot;] = 10;
book1[&quot;ProductCategory&quot;] = &quot;Book&quot;;
book1[&quot;Authors&quot;] = new List&lt;string&gt; { &quot;Author 1&quot;, &quot;Author 2&quot;, &quot;Author 3&quot; };
book1[&quot;Dimensions&quot;] = &quot;8.5x11x.5&quot;;
book1[&quot;InStock&quot;] = new DynamoDBBool(true);
book1[&quot;QuantityOnHand&quot;] = new DynamoDBNull(); //Quantity is unknown at this
time
}
batchWrite.AddDocumentToPut(book1);
// Specify delete item using overload that takes PK.
batchWrite.AddKeyToDelete(12345);
Console.WriteLine(&quot;Performing batch write in SingleTableBatchWrite()&quot;);
batchWrite.Execute();
private static void MultiTableBatchWrite()
{
// 1. Specify item to add in the Forum table.
Table forum = Table.LoadTable(client, &quot;Forum&quot;);
var forumBatchWrite = forum.CreateBatchWrite();
var forum1 = new Document();
forum1[&quot;Name&quot;] = &quot;Test BatchWrite Forum&quot;;
forum1[&quot;Threads&quot;] = 0;
forumBatchWrite.AddDocumentToPut(forum1);
// 2a. Specify item to add in the Thread table.
Table thread = Table.LoadTable(client, &quot;Thread&quot;);
var threadBatchWrite = thread.CreateBatchWrite();
var thread1 = new Document();
thread1[&quot;ForumName&quot;] = &quot;S3 forum&quot;;
thread1[&quot;Subject&quot;] = &quot;My sample question&quot;;
thread1[&quot;Message&quot;] = &quot;Message text&quot;;
thread1[&quot;KeywordTags&quot;] = new List&lt;string&gt; { &quot;S3&quot;, &quot;Bucket&quot; };
threadBatchWrite.AddDocumentToPut(thread1);
// 2b. Specify item to delete from the Thread table.
threadBatchWrite.AddKeyToDelete(&quot;someForumName&quot;, &quot;someSubject&quot;);
}
}
}
// 3. Create multi-table batch.
var superBatch = new MultiTableDocumentBatchWrite();
superBatch.AddBatch(forumBatchWrite);
superBatch.AddBatch(threadBatchWrite);
Console.WriteLine(&quot;Performing batch write in MultiTableBatchWrite()&quot;);
superBatch.Execute();
Querying Tables in DynamoDB Using the AWS SDK for .NET
Document Model
Topics
• Table.Query Method in the AWS SDK for .NET (p. 246)
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• Table.Scan Method in the AWS SDK for .NET (p. 250)
Table.Query Method in the AWS SDK for .NET
The Query method enables you to query your tables. You can only query the tables that have a
composite primary key (partition key and sort key). If your table's primary key is made of only a partition
key, then the Query operation is not supported. By default, Query internally performs queries that are
eventually consistent. To learn about the consistency model, see Read Consistency (p. 15).
The Query method provides two overloads. The minimum required parameters to the Query method are
a partition key value and a sort key ﬁlter. You can use the following overload to provide these minimum
required parameters.
Example
Query(Primitive partitionKey, RangeFilter Filter);
For example, the following C# code snippet queries for all forum replies that were posted in the last 15
days.
Example
string tableName = &quot;Reply&quot;;
Table table = Table.LoadTable(client, tableName);
DateTime twoWeeksAgoDate = DateTime.UtcNow - TimeSpan.FromDays(15);
RangeFilter filter = new RangeFilter(QueryOperator.GreaterThan, twoWeeksAgoDate);
Search search = table.Query(&quot;DynamoDB Thread 2&quot;, filter);
This creates a Search object. You can now call the Search.GetNextSet method iteratively to retrieve one
page of results at a time as shown in the following C# code snippet. The code prints the attribute values
for each item that the query returns.
Example
List&lt;Document&gt; documentSet = new List&lt;Document&gt;();
do
{
documentSet = search.GetNextSet();
foreach (var document in documentSet)
PrintDocument(document);
} while (!search.IsDone);
{
private static void PrintDocument(Document document)
Console.WriteLine();
foreach (var attribute in document.GetAttributeNames())
{
string stringValue = null;
var value = document[attribute];
if (value is Primitive)
stringValue = value.AsPrimitive().Value;
else if (value is PrimitiveList)
stringValue = string.Join(&quot;,&quot;, (from primitive
in value.AsPrimitiveList().Entries
select primitive.Value).ToArray());
Console.WriteLine(&quot;{0} - {1}&quot;, attribute, stringValue);
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}
}
Specifying Optional Parameters
You can also specify optional parameters for Query, such as specifying a list of attributes to retrieve,
strongly consistent reads, page size, and the number of items returned per page. For a complete list of
parameters, see Query. To specify optional parameters, you must use the following overload in which
you provide the QueryOperationConfig object.
Example
Query(QueryOperationConfig config);
Assume that you want to execute the query in the preceding example (retrieve forum replies posted in
the last 15 days). However, assume that you want to provide optional query parameters to retrieve only
speciﬁc attributes and also request a strongly consistent read. The following C# code snippet constructs
the request using the QueryOperationConfig object.
Example
Table table = Table.LoadTable(client, &quot;Reply&quot;);
DateTime twoWeeksAgoDate = DateTime.UtcNow - TimeSpan.FromDays(15);
QueryOperationConfig config = new QueryOperationConfig()
{
HashKey = &quot;DynamoDB Thread 2&quot;, //Partition key
AttributesToGet = new List&lt;string&gt;
{ &quot;Subject&quot;, &quot;ReplyDateTime&quot;, &quot;PostedBy&quot; },
ConsistentRead = true,
Filter = new RangeFilter(QueryOperator.GreaterThan, twoWeeksAgoDate)
};
Search search = table.Query(config);
Example: Query using the Table.Query method
The following C# code example uses the Table.Query method to execute the following sample queries:
• The following queries are executed against the Reply table.
• Find forum thread replies that were posted in the last 15 days.
This query is executed twice. In the ﬁrst Table.Query call, the example provides only the required
query parameters. In the second Table.Query call, you provide optional query parameters to request
a strongly consistent read and a list of attributes to retrieve.
• Find forum thread replies posted during a period of time.
This query uses the Between query operator to ﬁnd replies posted in between two dates.
• Get a product from the ProductCatalog table.
Because the ProductCatalog table has a primary key that is only a partition key, you can only get items;
you cannot query the table. The example retrieves a speciﬁc product item using the item Id.
Example
using System;
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using
using
using
using
using
using
System.Collections.Generic;
System.Linq;
Amazon.DynamoDBv2;
Amazon.DynamoDBv2.DocumentModel;
Amazon.Runtime;
Amazon.SecurityToken;
namespace com.amazonaws.codesamples
{
class MidLevelQueryAndScan
{
private static AmazonDynamoDBClient client = new AmazonDynamoDBClient();
static void Main(string[] args)
{
try
{
// Query examples.
Table replyTable = Table.LoadTable(client, &quot;Reply&quot;);
string forumName = &quot;Amazon DynamoDB&quot;;
string threadSubject = &quot;DynamoDB Thread 2&quot;;
FindRepliesInLast15Days(replyTable, forumName, threadSubject);
FindRepliesInLast15DaysWithConfig(replyTable, forumName, threadSubject);
FindRepliesPostedWithinTimePeriod(replyTable, forumName, threadSubject);
// Get Example.
Table productCatalogTable = Table.LoadTable(client, &quot;ProductCatalog&quot;);
int productId = 101;
GetProduct(productCatalogTable, productId);
Console.WriteLine(&quot;To continue, press Enter&quot;);
Console.ReadLine();
}
}
catch (AmazonDynamoDBException e) { Console.WriteLine(e.Message); }
catch (AmazonServiceException e) { Console.WriteLine(e.Message); }
catch (Exception e) { Console.WriteLine(e.Message); }
private static void GetProduct(Table tableName, int productId)
{
Console.WriteLine(&quot;*** Executing GetProduct() ***&quot;);
Document productDocument = tableName.GetItem(productId);
if (productDocument != null)
{
PrintDocument(productDocument);
}
else
{
Console.WriteLine(&quot;Error: product &quot; + productId + &quot; does not exist&quot;);
}
}
private static void FindRepliesInLast15Days(Table table, string forumName, string
threadSubject)
{
string Attribute = forumName + &quot;#&quot; + threadSubject;
DateTime twoWeeksAgoDate = DateTime.UtcNow - TimeSpan.FromDays(15);
QueryFilter filter = new QueryFilter(&quot;Id&quot;, QueryOperator.Equal, partitionKey);
filter.AddCondition(&quot;ReplyDateTime&quot;, QueryOperator.GreaterThan,
twoWeeksAgoDate);
// Use Query overloads that takes the minimum required query parameters.
Search search = table.Query(filter);
List&lt;Document&gt; documentSet = new List&lt;Document&gt;();
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do
{
}
documentSet = search.GetNextSet();
Console.WriteLine(&quot;\nFindRepliesInLast15Days: printing ............&quot;);
foreach (var document in documentSet)
PrintDocument(document);
} while (!search.IsDone);
private static void FindRepliesPostedWithinTimePeriod(Table table, string
forumName, string threadSubject)
{
DateTime startDate = DateTime.UtcNow.Subtract(new TimeSpan(21, 0, 0, 0));
DateTime endDate = DateTime.UtcNow.Subtract(new TimeSpan(1, 0, 0, 0));
QueryFilter filter = new QueryFilter(&quot;Id&quot;, QueryOperator.Equal, forumName + &quot;#&quot;
+ threadSubject);
filter.AddCondition(&quot;ReplyDateTime&quot;, QueryOperator.Between, startDate,
endDate);
QueryOperationConfig config = new QueryOperationConfig()
{
Limit = 2, // 2 items/page.
Select = SelectValues.SpecificAttributes,
AttributesToGet = new List&lt;string&gt; { &quot;Message&quot;,
&quot;ReplyDateTime&quot;,
&quot;PostedBy&quot; },
ConsistentRead = true,
Filter = filter
};
Search search = table.Query(config);
List&lt;Document&gt; documentList = new List&lt;Document&gt;();
do
{
documentList = search.GetNextSet();
Console.WriteLine(&quot;\nFindRepliesPostedWithinTimePeriod: printing replies
posted within dates: {0} and {1} ............&quot;, startDate, endDate);
foreach (var document in documentList)
{
PrintDocument(document);
}
} while (!search.IsDone);
}
private static void FindRepliesInLast15DaysWithConfig(Table table, string
forumName, string threadName)
{
DateTime twoWeeksAgoDate = DateTime.UtcNow - TimeSpan.FromDays(15);
QueryFilter filter = new QueryFilter(&quot;Id&quot;, QueryOperator.Equal, forumName + &quot;#&quot;
+ threadName);
filter.AddCondition(&quot;ReplyDateTime&quot;, QueryOperator.GreaterThan,
twoWeeksAgoDate);
// You are specifying optional parameters so use QueryOperationConfig.
QueryOperationConfig config = new QueryOperationConfig()
{
Filter = filter,
// Optional parameters.
Select = SelectValues.SpecificAttributes,
AttributesToGet = new List&lt;string&gt; { &quot;Message&quot;, &quot;ReplyDateTime&quot;,
&quot;PostedBy&quot; },
ConsistentRead = true
};
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Search search = table.Query(config);
List&lt;Document&gt; documentSet = new List&lt;Document&gt;();
do
{
documentSet = search.GetNextSet();
Console.WriteLine(&quot;\nFindRepliesInLast15DaysWithConfig:
printing ............&quot;);
foreach (var document in documentSet)
PrintDocument(document);
} while (!search.IsDone);
}
}
}
private static void PrintDocument(Document document)
{
//
count++;
Console.WriteLine();
foreach (var attribute in document.GetAttributeNames())
{
string stringValue = null;
var value = document[attribute];
if (value is Primitive)
stringValue = value.AsPrimitive().Value.ToString();
else if (value is PrimitiveList)
stringValue = string.Join(&quot;,&quot;, (from primitive
in value.AsPrimitiveList().Entries
select primitive.Value).ToArray());
Console.WriteLine(&quot;{0} - {1}&quot;, attribute, stringValue);
}
}
Table.Scan Method in the AWS SDK for .NET
The Scan method performs a full table scan. It provides two overloads. The only parameter required by
the Scan method is the scan ﬁlter which you can provide using the following overload.
Example
Scan(ScanFilter filter);
For example, assume that you maintain a table of forum threads tracking information such as thread
subject (primary), the related message, forum Id to which the thread belongs, Tags, and other
information. Assume that the subject is the primary key.
Example
Thread(Subject, Message, ForumId, Tags, LastPostedDateTime, .... )
This is a simpliﬁed version of forums and threads that you see on AWS forums (see Discussion Forums).
The following C# code snippet queries all threads in a speciﬁc forum (ForumId = 101) that are tagged
&quot;sortkey&quot;. Because the ForumId is not a primary key, the example scans the table. The ScanFilter
includes two conditions. Query returns all the threads that satisfy both of the conditions.
Example
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string tableName = &quot;Thread&quot;;
Table ThreadTable = Table.LoadTable(client, tableName);
ScanFilter scanFilter = new ScanFilter();
scanFilter.AddCondition(&quot;ForumId&quot;, ScanOperator.Equal, 101);
scanFilter.AddCondition(&quot;Tags&quot;, ScanOperator.Contains, &quot;sortkey&quot;);
Search search = ThreadTable.Scan(scanFilter);
Specifying Optional Parameters
You can also specify optional parameters to Scan, such as a speciﬁc list of attributes to retrieve or
whether to perform a strongly consistent read. To specify optional parameters, you must create a
ScanOperationConfig object that includes both the required and optional parameters and use the
following overload.
Example
Scan(ScanOperationConfig config);
The following C# code snippet executes the same preceding query (ﬁnd forum threads in which the
ForumId is 101 and the Tag attribute contains the &quot;sortkey&quot; keyword). However, this time assume that
you want to add an optional parameter to retrieve only a speciﬁc attribute list. In this case, you must
create a ScanOperationConfig object by providing all the parameters, required and optional as shown in
the following code example.
Example
string tableName = &quot;Thread&quot;;
Table ThreadTable = Table.LoadTable(client, tableName);
ScanFilter scanFilter = new ScanFilter();
scanFilter.AddCondition(&quot;ForumId&quot;, ScanOperator.Equal, forumId);
scanFilter.AddCondition(&quot;Tags&quot;, ScanOperator.Contains, &quot;sortkey&quot;);
ScanOperationConfig config = new ScanOperationConfig()
{
AttributesToGet = new List&lt;string&gt; { &quot;Subject&quot;, &quot;Message&quot; } ,
Filter = scanFilter
};
Search search = ThreadTable.Scan(config);
Example: Scan using the Table.Scan method
The Scan operation performs a full table scan making it a potentially expensive operation. You should
use queries instead. However, there are times when you might need to execute a scan against a table.
For example, you might have a data entry error in the product pricing and you must scan the table as
shown in the following C# code example. The example scans the ProductCatalog table to ﬁnd products
for which the price value is less than 0. The example illustrates the use of the two Table.Scan overloads.
• Table.Scan that takes the ScanFilter object as a parameter.
You can pass the ScanFilter parameter when passing in only the required parameters.
• Table.Scan that takes the ScanOperationConfig object as a parameter.
You must use the ScanOperationConfig parameter if you want to pass any optional parameters to the
Scan method.
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Example
using
using
using
using
using
System;
System.Collections.Generic;
System.Linq;
Amazon.DynamoDBv2;
Amazon.DynamoDBv2.DocumentModel;
namespace com.amazonaws.codesamples
{
class MidLevelScanOnly
{
private static AmazonDynamoDBClient client = new AmazonDynamoDBClient();
static void Main(string[] args)
{
Table productCatalogTable = Table.LoadTable(client, &quot;ProductCatalog&quot;);
// Scan example.
FindProductsWithNegativePrice(productCatalogTable);
FindProductsWithNegativePriceWithConfig(productCatalogTable);
}
Console.WriteLine(&quot;To continue, press Enter&quot;);
Console.ReadLine();
private static void FindProductsWithNegativePrice(Table productCatalogTable)
{
// Assume there is a price error. So we scan to find items priced &lt; 0.
ScanFilter scanFilter = new ScanFilter();
scanFilter.AddCondition(&quot;Price&quot;, ScanOperator.LessThan, 0);
Search search = productCatalogTable.Scan(scanFilter);
List&lt;Document&gt; documentList = new List&lt;Document&gt;();
do
{
documentList = search.GetNextSet();
Console.WriteLine(&quot;\nFindProductsWithNegativePrice:
printing ............&quot;);
foreach (var document in documentList)
PrintDocument(document);
} while (!search.IsDone);
}
private static void FindProductsWithNegativePriceWithConfig(Table
productCatalogTable)
{
// Assume there is a price error. So we scan to find items priced &lt; 0.
ScanFilter scanFilter = new ScanFilter();
scanFilter.AddCondition(&quot;Price&quot;, ScanOperator.LessThan, 0);
ScanOperationConfig config = new ScanOperationConfig()
{
Filter = scanFilter,
Select = SelectValues.SpecificAttributes,
AttributesToGet = new List&lt;string&gt; { &quot;Title&quot;, &quot;Id&quot; }
};
Search search = productCatalogTable.Scan(config);
List&lt;Document&gt; documentList = new List&lt;Document&gt;();
do
{
documentList = search.GetNextSet();
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Console.WriteLine(&quot;\nFindProductsWithNegativePriceWithConfig:
printing ............&quot;);
foreach (var document in documentList)
PrintDocument(document);
} while (!search.IsDone);
}
}
}
private static void PrintDocument(Document document)
{
//
count++;
Console.WriteLine();
foreach (var attribute in document.GetAttributeNames())
{
string stringValue = null;
var value = document[attribute];
if (value is Primitive)
stringValue = value.AsPrimitive().Value.ToString();
else if (value is PrimitiveList)
stringValue = string.Join(&quot;,&quot;, (from primitive
in value.AsPrimitiveList().Entries
select primitive.Value).ToArray());
Console.WriteLine(&quot;{0} - {1}&quot;, attribute, stringValue);
}
}
.NET: Object Persistence Model
Topics
• DynamoDB Attributes (p. 255)
• DynamoDBContext Class (p. 257)
• Supported Data Types (p. 261)
• Optimistic Locking Using Version Number with DynamoDB Using the AWS SDK for .NET Object
Persistence Model (p. 262)
• Mapping Arbitrary Data with DynamoDB Using the AWS SDK for .NET Object Persistence
Model (p. 263)
• Batch Operations Using AWS SDK for .NET Object Persistence Model (p. 266)
• Example: CRUD Operations Using the AWS SDK for .NET Object Persistence Model (p. 269)
• Example: Batch Write Operation Using the AWS SDK for .NET Object Persistence Model (p. 271)
• Example: Query and Scan in DynamoDB Using the AWS SDK for .NET Object Persistence
Model (p. 275)
The AWS SDK for .NET provides an object persistence model that enables you to map your client-side
classes to the DynamoDB tables. Each object instance then maps to an item in the corresponding tables.
To save your client-side objects to the tables the object persistence model provides the DynamoDBContext
class, an entry point to DynamoDB. This class provides you a connection to DynamoDB and enables you
to access tables, perform various CRUD operations, and execute queries.
The object persistence model provides a set of attributes to map client-side classes to tables, and
properties/ﬁelds to table attributes.
Note
The object persistence model does not provide an API to create, update, or delete tables. It
provides only data operations. You can use only the AWS SDK for .NET low-level API to create,
update, and delete tables. For more information, see Working with Tables: .NET (p. 321).
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To show you how the object persistence model works, let's walk through an example. We'll start with the
ProductCatalog table. It has Id as the primary key.
ProductCatalog(Id, ...)
Suppose you have a Book class with Title, ISBN, and Authors properties. You can map the Book class to
the ProductCatalog table by adding the attributes deﬁned by the object persistence model, as shown in
the following C# code snippet.
Example
[DynamoDBTable(&quot;ProductCatalog&quot;)]
public class Book
{
[DynamoDBHashKey]
public int Id { get; set; }
public string Title { get; set; }
public int ISBN { get; set; }
[DynamoDBProperty(&quot;Authors&quot;)]
public List&lt;string&gt; BookAuthors { get; set; }
}
[DynamoDBIgnore]
public string CoverPage { get; set; }
In the preceding example, the DynamoDBTable attribute maps the Book class to the ProductCatalog table.
The object persistence model supports both the explicit and default mapping between class properties
and table attributes.
• Explicit mapping—To map a property to a primary key, you must use the DynamoDBHashKey and
DynamoDBRangeKey object persistence model attributes. Additionally, for the non-primary key
attributes, if a property name in your class and the corresponding table attribute to which you want to
map it are not the same, then you must deﬁne the mapping by explicitly adding the DynamoDBProperty
attribute.
In the preceding example, Id property maps to the primary key with the same name and the
BookAuthors property maps to the Authors attribute in the ProductCatalog table.
• Default mapping—By default, the object persistence model maps the class properties to the
attributes with the same name in the table.
In the preceding example, the properties Title and ISBN map to the attributes with the same name in
the ProductCatalog table.
You don't have to map every single class property. You identify these properties by adding the
DynamoDBIgnore attribute. When you save a Book instance to the table, the DynamoDBContext does
not include the CoverPage property. It also does not return this property when you retrieve the book
instance.
You can map properties of .NET primitive types such as int and string. You can also map any arbitrary
data types as long as you provide an appropriate converter to map the arbitrary data to one of the
DynamoDB types. To learn about mapping arbitrary types, see Mapping Arbitrary Data with DynamoDB
Using the AWS SDK for .NET Object Persistence Model (p. 263).
The object persistence model supports optimistic locking. During an update operation this ensures you
have the latest copy of the item you are about to update. For more information, see Optimistic Locking
Using Version Number with DynamoDB Using the AWS SDK for .NET Object Persistence Model (p. 262).
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DynamoDB Attributes
This section describes the attributes the object persistence model oﬀers so you can map your classes and
properties to DynamoDB tables and attributes.
Note
In the following attributes, only DynamoDBTable and DynamoDBHashKey are required.
DynamoDBGlobalSecondaryIndexHashKey
Maps a class property to the partition key of a global secondary index. Use this attribute if you need to
Query a global secondary index.
DynamoDBGlobalSecondaryIndexRangeKey
Maps a class property to the sort key of a global secondary index. Use this attribute if you need to Query
a global secondary index and want to reﬁne your results using the index sort key.
DynamoDBHashKey
Maps a class property to the partition key of the table's primary key. The primary key attributes cannot
be a collection type.
The following C# code examples maps the Book class to the ProductCatalog table, and the Id property to
the table's primary key partition key.
[DynamoDBTable(&quot;ProductCatalog&quot;)]
public class Book {
[DynamoDBHashKey]
public int Id { get; set; }
}
// Additional properties go here.
DynamoDBIgnore
Indicates that the associated property should be ignored. If you don't want to save any of your class
properties you can add this attribute to instruct DynamoDBContext not to include this property when
saving objects to the table.
DynamoDBLocalSecondaryIndexRangeKey
Maps a class property to the sort key of a local secondary index. Use this attribute if you need to Query a
local secondary index and want to reﬁne your results using the index sort key.
DynamoDBProperty
Maps a class property to a table attribute. If the class property maps to the same name table attribute,
then you don't need to specify this attribute. However, if the names are not the same, you can use this
tag to provide the mapping. In the following C# statement the DynamoDBProperty maps the BookAuthors
property to the Authors attribute in the table.
[DynamoDBProperty(&quot;Authors&quot;)]
public List&lt;string&gt; BookAuthors { get; set; }
DynamoDBContext uses this mapping information to create the Authors attribute when saving object data
to the corresponding table.
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DynamoDBRenamable
Speciﬁes an alternative name for a class property. This is useful if you are writing a custom converter
for mapping arbitrary data to a DynamoDB table where the name of a class property is diﬀerent from a
table attribute.
DynamoDBRangeKey
Maps a class property to the sort key of the table's primary key. If the table has a composite
primary key (partition key and sort key), then you must specify both the DynamoDBHashKey and
DynamoDBRangeKey attributes in your class mapping.
For example, the sample table Reply has a primary key made of the Id partition key and Replenishment
sort key. The following C# code example maps the Reply class to the Reply table. The class deﬁnition also
indicates that two of its properties map to the primary key.
For more information about sample tables, see Creating Tables and Loading Sample Data (p. 280).
[DynamoDBTable(&quot;Reply&quot;)]
public class Reply {
[DynamoDBHashKey]
public int ThreadId { get; set; }
[DynamoDBRangeKey]
public string Replenishment { get; set; }
// Additional properties go here.
}
DynamoDBTable
Identiﬁes the target table in DynamoDB to which the class maps. For example, the following C# code
example maps the Developer class to the People table in DynamoDB.
[DynamoDBTable(&quot;People&quot;)]
public class Developer { ...}
This attribute can be inherited or overridden.
• The DynamoDBTable attribute can be inherited. In the preceding example, if you add a new class, Lead,
that inherits from the Developer class, it also maps to the People table. Both the Developer and Lead
objects are stored in the People table.
• The DynamoDBTable attribute can also be overridden. In the following C# code example, the Manager
class inherits from the Developer class, however the explicit addition of the DynamoDBTable attribute
maps the class to another table (Managers).
[DynamoDBTable(&quot;Managers&quot;)]
public class Manager extends Developer { ...}
You can add the optional parameter, LowerCamelCaseProperties, to request DynamoDB to lower case
the ﬁrst letter of the property name when storing the objects to a table as shown in the following C#
snippet.
[DynamoDBTable(&quot;People&quot;, LowerCamelCaseProperties=true)]
public class Developer {
string DeveloperName;
...}
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When saving instances of the Developer class, DynamoDBContext saves the DeveloperName property as the
developerName.
DynamoDBVersion
Identiﬁes a class property for storing the item version number. To more information about versioning,
see Optimistic Locking Using Version Number with DynamoDB Using the AWS SDK for .NET Object
Persistence Model (p. 262).
DynamoDBContext Class
The DynamoDBContext class is the entry point to the DynamoDB database. It provides a connection to
DynamoDB and enables you to access your data in various tables, perform various CRUD operations, and
execute queries. The DynamoDBContext class provides the following methods:
CreateMultiTableBatchGet
Creates a MultiTableBatchGet object, composed of multiple individual BatchGet objects. Each of these
BatchGet objects can be used for retrieving items from a single DynamoDB table.
To retrieve the items from the table(s), use the ExecuteBatchGet method, passing the
MultiTableBatchGet object as a parameter.
CreateMultiTableBatchWrite
Creates a MultiTableBatchWrite object, composed of multiple individual BatchWrite objects. Each of
these BatchWrite objects can be used for writing or deleting items in a single DynamoDB table.
To write to the table(s), use the ExecuteBatchWrite method, passing the MultiTableBatchWrite object
as a parameter.
CreateBatchGet
Creates a BatchGet object that you can use to retrieve multiple items from a table. For more information,
see Batch Get: Getting Multiple Items (p. 268).
CreateBatchWrite
Creates a BatchWrite object that you can use to put multiple items into a table, or to delete multiple
items from a table. For more information, see Batch Write: Putting and Deleting Multiple Items
(p. 266).
Delete
Deletes an item from the table. The method requires the primary key of the item you want to delete.
You can provide either the primary key value or a client-side object containing a primary key value as a
parameter to this method.
• If you specify a client-side object as a parameter and you have enabled optimistic locking, the delete
succeeds only if the client-side and the server-side versions of the object match.
• If you specify only the primary key value as a parameter, the delete succeeds regardless of whether
you have enabled optimistic locking or not.
Note
To perform this operation in the background, use the DeleteAsync method instead.
Dispose
Disposes of all managed and unmanaged resources.
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ExecuteBatchGet
Reads data from one or more tables, processing all of the BatchGet objects in a MultiTableBatchGet.
Note
To perform this operation in the background, use the ExecuteBatchGetAsync method instead.
ExecuteBatchWrite
Writes or deletes data in one or more tables, processing all of the BatchWrite objects in a
MultiTableBatchWrite.
Note
To perform this operation in the background, use the ExecuteBatchWriteAsync method instead.
FromDocument
Given an instance of a Document, the FromDocument method returns an instance of a client-side class.
This is helpful if you want to use the document model classes along with the object persistence model to
perform any data operations. For more information about the document model classes provided by the
AWS SDK for .NET, see .NET: Document Model (p. 232).
Suppose you have a Document object named doc, containing a representation of a Forum item. (To
see how to construct this object, see the description for the ToDocument method below.) You can use
FromDocument to retrieve the Forum item from the Document as shown in the following C# code snippet.
Example
forum101 = context.FromDocument&lt;Forum&gt;(101);
Note
If your Document object implements the IEnumerable interface, you can use the FromDocuments
method instead. This will allow you to iterate over all of the class instances in the Document.
FromQuery
Executes a Query operation, with the query parameters deﬁned in a QueryOperationConfig object.
Note
To perform this operation in the background, use the FromQueryAsync method instead.
FromScan
Executes a Scan operation, with the scan parameters deﬁned in a ScanOperationConfig object.
Note
To perform this operation in the background, use the FromScanAsync method instead.
GetTargetTable
Retrieves the target table for the speciﬁed type. This is useful if you are writing a custom converter for
mapping arbitrary data to a DynamoDB table and need to determine which table is associated with a
custom data type.
Load
Retrieves an item from a table. The method requires only the primary key of the item you want to
retrieve.
By default, DynamoDB returns the item with values that are eventually consistent. For information on
the eventual consistency model, see Read Consistency (p. 15).
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Note
To perform this operation in the background, use the LoadAsync method instead.
Query
Queries a table based on query parameters you provide.
You can query a table only if it has a composite primary key (partition key and sort key). When querying,
you must specify a partition key and a condition that applies to the sort key.
Suppose you have a client-side Reply class mapped to the Reply table in DynamoDB. The following
C# code snippet queries the Reply table to ﬁnd forum thread replies posted in the past 15 days. The
Reply table has a primary key that has the Id partition key and the ReplyDateTime sort key. For more
information about the Reply table, see Creating Tables and Loading Sample Data (p. 280).
Example
DynamoDBContext context = new DynamoDBContext(client);
string replyId = &quot;DynamoDB#DynamoDB Thread 1&quot;; //Partition key
DateTime twoWeeksAgoDate = DateTime.UtcNow.Subtract(new TimeSpan(14, 0, 0, 0)); // Date to
compare.
IEnumerable&lt;Reply&gt; latestReplies = context.Query&lt;Reply&gt;(replyId, QueryOperator.GreaterThan,
twoWeeksAgoDate);
This returns a collection of Reply objects.
The Query method returns a &quot;lazy-loaded&quot; IEnumerable collection. It initially returns only one page of
results, and then makes a service call for the next page if needed. To obtain all the matching items, you
only need to iterate over the IEnumerable.
If your table has a simple primary key (partition key), then you cannot use the Query method. Instead,
you can use the Load method and provide the partition key to retrieve the item.
Note
To perform this operation in the background, use the QueryAsync method instead.
Save
Saves the speciﬁed object to the table. If the primary key speciﬁed in the input object does not exist
in the table, the method adds a new item to the table. If primary key exists, the method updates the
existing item.
If you have optimistic locking conﬁgured, the update succeeds only if the client and the server side
versions of the item match. For more information, see Optimistic Locking Using Version Number with
DynamoDB Using the AWS SDK for .NET Object Persistence Model (p. 262).
Note
To perform this operation in the background, use the SaveAsync method instead.
Scan
Performs an entire table scan.
You can ﬁlter scan result by specifying a scan condition. The condition can be evaluated on any
attributes in the table. Suppose you have a client-side class Book mapped to the ProductCatalog table in
DynamoDB. The following C# snippet scans the table and returns only the book items priced less than 0.
Example
IEnumerable&lt;Book&gt; itemsWithWrongPrice = context.Scan&lt;Book&gt;(
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new ScanCondition(&quot;Price&quot;, ScanOperator.LessThan, price),
new ScanCondition(&quot;ProductCategory&quot;, ScanOperator.Equal, &quot;Book&quot;)
The Scan method returns a &quot;lazy-loaded&quot; IEnumerable collection. It initially returns only one page of
results, and then makes a service call for the next page if needed. To obtain all the matching items, you
only need to iterate over the IEnumerable.
For performance reasons you should query your tables and avoid a table scan.
Note
To perform this operation in the background, use the ScanAsync method instead.
ToDocument
Returns an instance of the Document document model class from your class instance.
This is helpful if you want to use the document model classes along with the object persistence model to
perform any data operations. For more information about the document model classes provided by the
AWS SDK for .NET, see .NET: Document Model (p. 232).
Suppose you have a client-side class mapped to the sample Forum table. You can then use a
DynamoDBContext to get an item, as a Document object, from the Forum table as shown in the following
C# code snippet.
Example
DynamoDBContext context = new DynamoDBContext(client);
Forum forum101 = context.Load&lt;Forum&gt;(101); // Retrieve a forum by primary key.
Document doc = context.ToDocument&lt;Forum&gt;(forum101);
Specifying Optional Parameters for DynamoDBContext
When using the object persistence model, you can specify the following optional parameters for the
DynamoDBContext.
• ConsistentRead—When retrieving data using the Load, Query or Scan operations you can optionally
add this parameter to request the latest values for the data.
• IgnoreNullValues—This parameter informs DynamoDBContext to ignore null values on attributes
during a Save operation. If this parameter is false (or if it is not set), then a null value is interpreted as
directives to delete the speciﬁc attribute.
• SkipVersionCheck— - This parameter informs DynamoDBContext to not compare versions when saving
or deleting an item. For more information about versioning, see Optimistic Locking Using Version
Number with DynamoDB Using the AWS SDK for .NET Object Persistence Model (p. 262).
• TableNamePreﬁx— - Preﬁxes all table names with a speciﬁc string. If this parameter is null (or if it is
not set), then no preﬁx is used.
The following C# snippet creates a new DynamoDBContext by specifying two of the preceding optional
parameters.
Example
AmazonDynamoDBClient client = new AmazonDynamoDBClient();
...
DynamoDBContext context =
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new DynamoDBContext(client, new DynamoDBContextConfig { ConsistentRead = true,
SkipVersionCheck = true});
DynamoDBContext includes these optional parameters with each request you send using this context.
Instead of setting these parameters at the DynamoDBContext level, you can specify them for individual
operations you execute using DynamoDBContext as shown in the following C# code snippet. The example
loads a speciﬁc book item. The Load method of DynamoDBContext speciﬁes the preceding optional
parameters.
Example
AmazonDynamoDBClient client = new AmazonDynamoDBClient();
...
DynamoDBContext context = new DynamoDBContext(client);
Book bookItem = context.Load&lt;Book&gt;(productId,new DynamoDBContextConfig{ ConsistentRead =
true, SkipVersionCheck = true });
In this case DynamoDBContext includes these parameters only when sending the Get request.
Supported Data Types
The object persistence model supports a set of primitive .NET data types, collections, and arbitrary data
types. The model supports the following primitive data types.
• bool
• byte
• char
• DateTime
• decimal
• double
• float
• Int16
• Int32
• Int64
• SByte
• string
• UInt16
• UInt32
• UInt64
The object persistence model also supports the .NET collection types. DynamoDBContext is able to convert
concrete collection types and simple Plain Old CLR Objects (POCOs).
The following table summarizes the mapping of the preceding .NET types to the DynamoDB types.
.NET primitive type
DynamoDB type
All number types
N (number type)
All string types
S (string type)
MemoryStream, byte[]
B (binary type)
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.NET primitive type
DynamoDB type
bool
N (number type), 0 represents false and 1
represents true.
Collection types
BS (binary set) type, SS (string set) type, and NS
DateTime
S (string type). The DateTime values are stored as
(number set) type
ISO-8601 formatted strings.
The object persistence model also supports arbitrary data types. However, you must provide converter
code to map the complex types to the DynamoDB types.
Optimistic Locking Using Version Number with DynamoDB
Using the AWS SDK for .NET Object Persistence Model
The optimistic locking support in the object persistence model ensures that the item version for your
application is same as the item version on the server-side before updating or deleting the item. Suppose
you retrieve an item for update. However, before you send your updates back, some other application
updates the same item. Now your application has a stale copy of the item. Without optimistic locking,
any update you perform will overwrite the update made by the other application.
The optimistic locking feature of the object persistence model provides the DynamoDBVersion tag that
you can use to enable optimistic locking. To use this feature you add a property to your class for storing
the version number. You add the DynamoDBVersion attribute on the property. When you ﬁrst save the
object, the DynamoDBContext assigns a version number and increments this value each time you update
the item.
Your update or delete request succeeds only if the client-side object version matches the corresponding
version number of the item on the server-side. If your application has a stale copy, it must get the latest
version from the server before it can update or delete that item.
The following C# code snippet deﬁnes a Book class with object persistence attributes mapping it to the
ProductCatalog table. The VersionNumber property in the class decorated with the DynamoDBVersion
attribute stores the version number value.
Example
[DynamoDBTable(&quot;ProductCatalog&quot;)]
public class Book
{
[DynamoDBHashKey]
//Partition key
public int Id { get; set; }
[DynamoDBProperty]
public string Title { get; set; }
[DynamoDBProperty]
public string ISBN { get; set; }
[DynamoDBProperty(&quot;Authors&quot;)]
public List&lt;string&gt; BookAuthors { get; set; }
[DynamoDBVersion]
public int? VersionNumber { get; set; }
}
Note
You can apply the DynamoDBVersion attribute only to a nullable numeric primitive type (such as
int?).
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Optimistic locking has the following impact on DynamoDBContext operations:
• For a new item, DynamoDBContext assigns initial version number 0. If you retrieve an existing
item, and then update one or more of its properties and attempt to save the changes, the save
operation succeeds only if the version number on the client-side and the server-side match. The
DynamoDBContext increments the version number. You don't need to set the version number.
• The Delete method provides overloads that can take either a primary key value or an object as
parameter as shown in the following C# code snippet.
Example
DynamoDBContext context = new DynamoDBContext(client);
...
// Load a book.
Book book = context.Load&lt;ProductCatalog&gt;(111);
// Do other operations.
// Delete 1 - Pass in the book object.
context.Delete&lt;ProductCatalog&gt;(book);
// Delete 2 - pass in the Id (primary key)
context.Delete&lt;ProductCatalog&gt;(222);
If you provide an object as the parameter, then the delete succeeds only if the object version matches
the corresponding server-side item version. However, if you provide a primary key value as the
parameter, the DynamoDBContext is unaware of any version numbers and it deletes the item without
making the version check.
Note that the internal implementation of optimistic locking in the object persistence model code uses
the conditional update and the conditional delete API actions in DynamoDB.
Disabling Optimistic Locking
To disable optimistic locking you use the SkipVersionCheck conﬁguration property. You can set
this property when creating DynamoDBContext. In this case, optimistic locking is disabled for any
requests you make using the context. For more information, see Specifying Optional Parameters for
DynamoDBContext (p. 260).
Instead of setting the property at the context level, you can disable optimistic locking for a speciﬁc
operation as shown in the following C# code snippet. The code example uses the context to delete a
book item. The Delete method sets the optional SkipVersionCheck property to true, disabling version
check.
Example
DynamoDBContext context = new DynamoDBContext(client);
// Load a book.
Book book = context.Load&lt;ProductCatalog&gt;(111);
...
// Delete the book.
context.Delete&lt;Book&gt;(book, new DynamoDBContextConfig { SkipVersionCheck = true });
Mapping Arbitrary Data with DynamoDB Using the AWS SDK
for .NET Object Persistence Model
In addition to the supported .NET types (see Supported Data Types (p. 261)), you can use types in your
application for which there is no direct mapping to the DynamoDB types. The object persistence model
supports storing data of arbitrary types as long as you provide the converter to convert data from the
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arbitrary type to the DynamoDB type and vice-versa. The converter code transforms data during both
the saving and loading of the objects.
You can create any types on the client-side, however the data stored in the tables is one of the
DynamoDB types and during query and scan any data comparisons made are against the data stored in
DynamoDB.
The following C# code example deﬁnes a Book class with Id, Title, ISBN, and Dimension properties. The
Dimension property is of the DimensionType that describes Height, Width, and Thickness properties.
The example code provides the converter methods, ToEntry and FromEntry to convert data between the
DimensionType and the DynamoDB string types. For example, when saving a Book instance, the converter
creates a book Dimension string such as &quot;8.5x11x.05&quot;, and when you retrieve a book, it converts the
string to a DimensionType instance.
The example maps the Book type to the ProductCatalog table. For illustration, it saves a sample Book
instance, retrieves it, updates its dimensions and saves the updated Book again.
For step-by-step instructions on how to test the following sample, see .NET Code Samples (p. 287).
Example
using
using
using
using
using
using
using
System;
System.Collections.Generic;
Amazon.DynamoDBv2;
Amazon.DynamoDBv2.DataModel;
Amazon.DynamoDBv2.DocumentModel;
Amazon.Runtime;
Amazon.SecurityToken;
namespace com.amazonaws.codesamples
{
class HighLevelMappingArbitraryData
{
private static AmazonDynamoDBClient client = new AmazonDynamoDBClient();
static void Main(string[] args)
{
try
{
DynamoDBContext context = new DynamoDBContext(client);
// 1. Create a book.
DimensionType myBookDimensions = new DimensionType()
{
Length = 8M,
Height = 11M,
Thickness = 0.5M
};
Data&quot;,
Book myBook = new Book
{
Id = 501,
Title = &quot;AWS SDK for .NET Object Persistence Model Handling Arbitrary
};
ISBN = &quot;999-9999999999&quot;,
BookAuthors = new List&lt;string&gt; { &quot;Author 1&quot;, &quot;Author 2&quot; },
Dimensions = myBookDimensions
context.Save(myBook);
// 2. Retrieve the book.
Book bookRetrieved = context.Load&lt;Book&gt;(501);
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// 3. Update property (book dimensions).
bookRetrieved.Dimensions.Height += 1;
bookRetrieved.Dimensions.Length += 1;
bookRetrieved.Dimensions.Thickness += 0.2M;
// Update the book.
context.Save(bookRetrieved);
Console.WriteLine(&quot;To continue, press Enter&quot;);
Console.ReadLine();
}
catch (AmazonDynamoDBException e) { Console.WriteLine(e.Message); }
catch (AmazonServiceException e) { Console.WriteLine(e.Message); }
catch (Exception e) { Console.WriteLine(e.Message); }
}
}
[DynamoDBTable(&quot;ProductCatalog&quot;)]
public class Book
{
[DynamoDBHashKey] //Partition key
public int Id
{
get; set;
}
[DynamoDBProperty]
public string Title
{
get; set;
}
[DynamoDBProperty]
public string ISBN
{
get; set;
}
// Multi-valued (set type) attribute.
[DynamoDBProperty(&quot;Authors&quot;)]
public List&lt;string&gt; BookAuthors
{
get; set;
}
// Arbitrary type, with a converter to map it to DynamoDB type.
[DynamoDBProperty(typeof(DimensionTypeConverter))]
public DimensionType Dimensions
{
get; set;
}
}
public class DimensionType
{
public decimal Length
{
get; set;
}
public decimal Height
{
get; set;
}
public decimal Thickness
{
get; set;
}
}
// Converts the complex type DimensionType to string and vice-versa.
public class DimensionTypeConverter : IPropertyConverter
{
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public DynamoDBEntry ToEntry(object value)
{
DimensionType bookDimensions = value as DimensionType;
if (bookDimensions == null) throw new ArgumentOutOfRangeException();
string data = string.Format(&quot;{1}{0}{2}{0}{3}&quot;, &quot; x &quot;,
bookDimensions.Length, bookDimensions.Height,
bookDimensions.Thickness);
}
DynamoDBEntry entry = new Primitive
{
Value = data
};
return entry;
public object FromEntry(DynamoDBEntry entry)
{
Primitive primitive = entry as Primitive;
if (primitive == null || !(primitive.Value is String) ||
string.IsNullOrEmpty((string)primitive.Value))
throw new ArgumentOutOfRangeException();
string[] data = ((string)(primitive.Value)).Split(new string[] { &quot; x &quot; },
StringSplitOptions.None);
if (data.Length != 3) throw new ArgumentOutOfRangeException();
}
}
}
DimensionType complexData = new DimensionType
{
Length = Convert.ToDecimal(data[0]),
Height = Convert.ToDecimal(data[1]),
Thickness = Convert.ToDecimal(data[2])
};
return complexData;
Batch Operations Using AWS SDK for .NET Object Persistence
Model
Batch Write: Putting and Deleting Multiple Items
To put or delete multiple objects from a table in a single request, do the following:
• Execute CreateBatchWrite method of the DynamoDBContext and create an instance of the BatchWrite
class.
• Specify the items you want to put or delete.
• To put one or more items, use either the AddPutItem or the AddPutItems method.
• To delete one or more items, you can either specify the primary key of the item or a client-side
object that maps to the item you want to delete. Use the AddDeleteItem, AddDeleteItems, and the
AddDeleteKey methods to specify the list of items to delete.
• Call the BatchWrite.Execute method to put and delete all the speciﬁed items from the table.
Note
When using object persistence model, you can specify any number of operations in a batch.
However, note that DynamoDB limits the number of operations in a batch and the total
size of the batch in a batch operation. For more information about the speciﬁc limits, see
BatchWriteItem. If the API detects your batch write request exceeded the allowed number of
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write requests or exceeded the maximum allowed HTTP payload size, it breaks the batch in to
several smaller batches. Additionally, if a response to a batch write returns unprocessed items,
the API will automatically send another batch request with those unprocessed items.
Suppose that you have deﬁned a C# class Book class that maps to the ProductCatalog table in
DynamoDB. The following C# code snippet uses the BatchWrite object to upload two items and delete
one item from the ProductCatalog table.
Example
DynamoDBContext context = new DynamoDBContext(client);
var bookBatch = context.CreateBatchWrite&lt;Book&gt;();
// 1. Specify two books to add.
Book book1 = new Book
{
Id = 902,
ISBN = &quot;902-11-11-1111&quot;,
ProductCategory = &quot;Book&quot;,
Title = &quot;My book3 in batch write&quot;
};
Book book2 = new Book
{
Id = 903,
ISBN = &quot;903-11-11-1111&quot;,
ProductCategory = &quot;Book&quot;,
Title = &quot;My book4 in batch write&quot;
};
bookBatch.AddPutItems(new List&lt;Book&gt; { book1, book2 });
// 2. Specify one book to delete.
bookBatch.AddDeleteKey(111);
bookBatch.Execute();
To put or delete objects from multiple tables, do the following:
• Create one instance of the BatchWrite class for each type and specify the items you want to put or
delete as described in the preceding section.
• Create an instance of MultiTableBatchWrite using one of the following methods:
• Execute the Combine method on one of the BatchWrite objects that you created in the preceding
step.
• Create an instance of the MultiTableBatchWrite type by providing a list of BatchWrite objects.
• Execute the CreateMultiTableBatchWrite method of DynamoDBContext and pass in your list of
BatchWrite objects.
• Call the Execute method of MultiTableBatchWrite, which performs the speciﬁed put and delete
operations on various tables.
Suppose that you have deﬁned Forum and Thread C# classes that map to the Forum and Thread tables
in DynamoDB. Also, suppose that the Thread class has versioning enabled. Because versioning is not
supported when using batch operations, you must explicitly disable versioning as shown in the following
C# code snippet. The code snippet uses the MultiTableBatchWrite object to perform a multi-table
update.
Example
DynamoDBContext context = new DynamoDBContext(client);
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// Create BatchWrite objects for each of the Forum and Thread classes.
var forumBatch = context.CreateBatchWrite&lt;Forum&gt;();
DynamoDBOperationConfig config = new DynamoDBOperationConfig();
config.SkipVersionCheck = true;
var threadBatch = context.CreateBatchWrite&lt;Thread&gt;(config);
// 1. New Forum item.
Forum newForum = new Forum
{
Name = &quot;Test BatchWrite Forum&quot;,
Threads = 0
};
forumBatch.AddPutItem(newForum);
// 2. Specify a forum to delete by specifying its primary key.
forumBatch.AddDeleteKey(&quot;Some forum&quot;);
// 3. New Thread item.
Thread newThread = new Thread
{
ForumName = &quot;Amazon S3 forum&quot;,
Subject = &quot;My sample question&quot;,
KeywordTags = new List&lt;string&gt; { &quot;Amazon S3&quot;, &quot;Bucket&quot; },
Message = &quot;Message text&quot;
};
threadBatch.AddPutItem(newThread);
// Now execute multi-table batch write.
var superBatch = new MultiTableBatchWrite(forumBatch, threadBatch);
superBatch.Execute();
For a working example, see Example: Batch Write Operation Using the AWS SDK for .NET Object
Persistence Model (p. 271).
Note
DynamoDB batch API limits the number of writes in batch and also limits the size of the batch.
For more information, see BatchWriteItem. When using the .NET object persistence model API,
you can specify any number of operations. However, if either the number of operations in a
batch or size exceed the limit, the .NET API breaks the batch write request into smaller batches
and sends multiple batch write requests to DynamoDB.
Batch Get: Getting Multiple Items
To retrieve multiple items from a table in a single request, do the following:
• Create an instance of the CreateBatchGet class.
• Specify a list of primary keys to retrieve.
• Call the Execute method. The response returns the items in the Results property.
The following C# code sample retrieves three items from the ProductCatalog table. The items in the
result are not necessarily in the same order in which you speciﬁed the primary keys.
Example
DynamoDBContext context = new DynamoDBContext(client);
var bookBatch = context.CreateBatchGet&lt;ProductCatalog&gt;();
bookBatch.AddKey(101);
bookBatch.AddKey(102);
bookBatch.AddKey(103);
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bookBatch.Execute();
// Process result.
Console.WriteLine(devBatch.Results.Count);
Book book1 = bookBatch.Results[0];
Book book2 = bookBatch.Results[1];
Book book3 = bookBatch.Results[2];
To retrieve objects from multiple tables, do the following:
• For each type, create an instance of the CreateBatchGet type and provide the primary key values you
want to retrieve from each table.
• Create an instance of the MultiTableBatchGet class using one of the following methods:
• Execute the Combine method on one of the BatchGet objects you created in the preceding step.
• Create an instance of the MultiBatchGet type by providing a list of BatchGet objects.
• Execute the CreateMultiTableBatchGet method of DynamoDBContext and pass in your list of
BatchGet objects.
• Call the Execute method of MultiTableBatchGet which returns the typed results in the individual
BatchGet objects.
The following C# code snippet retrieves multiple items from the Order and OrderDetail tables using the
CreateBatchGet method.
Example
var orderBatch = context.CreateBatchGet&lt;Order&gt;();
orderBatch.AddKey(101);
orderBatch.AddKey(102);
var orderDetailBatch = context.CreateBatchGet&lt;OrderDetail&gt;();
orderDetailBatch.AddKey(101, &quot;P1&quot;);
orderDetailBatch.AddKey(101, &quot;P2&quot;);
orderDetailBatch.AddKey(102, &quot;P3&quot;);
orderDetailBatch.AddKey(102, &quot;P1&quot;);
var orderAndDetailSuperBatch = orderBatch.Combine(orderDetailBatch);
orderAndDetailSuperBatch.Execute();
Console.WriteLine(orderBatch.Results.Count);
Console.WriteLine(orderDetailBatch.Results.Count);
Order order1 = orderBatch.Results[0];
Order order2 = orderDetailBatch.Results[1];
OrderDetail orderDetail1 = orderDetailBatch.Results[0];
Example: CRUD Operations Using the AWS SDK for .NET Object
Persistence Model
The following C# code example declares a Book class with Id, title, ISBN, and Authors properties. It uses
the object persistence attributes to map these properties to the ProductCatalog table in DynamoDB. The
code example then uses the DynamoDBContext to illustrate typical CRUD operations. The example creates
a sample Book instance and saves it to the ProductCatalog table. The example then retrieves the book
item, and updates its ISBN and Authors properties. Note that the update replaces the existing authors
list. The example ﬁnally deletes the book item.
For more information about the ProductCatalog table used in this example, see Creating Tables and
Loading Sample Data (p. 280). For step-by-step instructions to test the following sample, see .NET
Code Samples (p. 287).
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Note
The following example does not work with .NET core as it does not support synchronous
methods. For more information, see AWS Asynchronous APIs for .NET.
Example
using
using
using
using
using
System;
System.Collections.Generic;
Amazon.DynamoDBv2;
Amazon.DynamoDBv2.DataModel;
Amazon.Runtime;
namespace com.amazonaws.codesamples
{
class HighLevelItemCRUD
{
private static AmazonDynamoDBClient client = new AmazonDynamoDBClient();
static void Main(string[] args)
{
try
{
DynamoDBContext context = new DynamoDBContext(client);
TestCRUDOperations(context);
Console.WriteLine(&quot;To continue, press Enter&quot;);
Console.ReadLine();
}
catch (AmazonDynamoDBException e) { Console.WriteLine(e.Message); }
catch (AmazonServiceException e) { Console.WriteLine(e.Message); }
catch (Exception e) { Console.WriteLine(e.Message); }
}
private static void TestCRUDOperations(DynamoDBContext context)
{
int bookID = 1001; // Some unique value.
Book myBook = new Book
{
Id = bookID,
Title = &quot;object persistence-AWS SDK for.NET SDK-Book 1001&quot;,
ISBN = &quot;111-1111111001&quot;,
BookAuthors = new List&lt;string&gt; { &quot;Author 1&quot;, &quot;Author 2&quot; },
};
// Save the book.
context.Save(myBook);
// Retrieve the book.
Book bookRetrieved = context.Load&lt;Book&gt;(bookID);
// Update few properties.
bookRetrieved.ISBN = &quot;222-2222221001&quot;;
bookRetrieved.BookAuthors = new List&lt;string&gt; { &quot; Author 1&quot;, &quot;Author x&quot; }; //
Replace existing authors list with this.
context.Save(bookRetrieved);
// Retrieve the updated book. This time add the optional ConsistentRead
parameter using DynamoDBContextConfig object.
Book updatedBook = context.Load&lt;Book&gt;(bookID, new DynamoDBContextConfig
{
ConsistentRead = true
});
// Delete the book.
context.Delete&lt;Book&gt;(bookID);
// Try to retrieve deleted book. It should return null.
Book deletedBook = context.Load&lt;Book&gt;(bookID, new DynamoDBContextConfig
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{
}
}
}
ConsistentRead = true
});
if (deletedBook == null)
Console.WriteLine(&quot;Book is deleted&quot;);
[DynamoDBTable(&quot;ProductCatalog&quot;)]
public class Book
{
[DynamoDBHashKey] //Partition key
public int Id
{
get; set;
}
[DynamoDBProperty]
public string Title
{
get; set;
}
[DynamoDBProperty]
public string ISBN
{
get; set;
}
[DynamoDBProperty(&quot;Authors&quot;)] //String Set datatype
public List&lt;string&gt; BookAuthors
{
get; set;
}
}
Example: Batch Write Operation Using the AWS SDK for .NET
Object Persistence Model
The following C# code example declares Book, Forum, Thread, and Reply classes and maps them to the
DynamoDB tables using the object persistence model attributes.
The code example then uses the DynamoDBContext to illustrate the following batch write operations.
• BatchWrite object to put and delete book items from the ProductCatalog table.
• MultiTableBatchWrite object to put and delete items from the Forum and the Thread tables.
For more information about the tables used in this example, see Creating Tables and Loading
Sample Data (p. 280). For step-by-step instructions to test the following sample, see .NET Code
Samples (p. 287).
Note
The following example does not work with .NET core as it does not support synchronous
methods. For more information, see AWS Asynchronous APIs for .NET.
Example
using
using
using
using
using
using
System;
System.Collections.Generic;
Amazon.DynamoDBv2;
Amazon.DynamoDBv2.DataModel;
Amazon.Runtime;
Amazon.SecurityToken;
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namespace com.amazonaws.codesamples
{
class HighLevelBatchWriteItem
{
private static AmazonDynamoDBClient client = new AmazonDynamoDBClient();
static void Main(string[] args)
{
try
{
DynamoDBContext context = new DynamoDBContext(client);
SingleTableBatchWrite(context);
MultiTableBatchWrite(context);
}
catch (AmazonServiceException e) { Console.WriteLine(e.Message); }
catch (Exception e) { Console.WriteLine(e.Message); }
}
Console.WriteLine(&quot;To continue, press Enter&quot;);
Console.ReadLine();
private static void SingleTableBatchWrite(DynamoDBContext context)
{
Book book1 = new Book
{
Id = 902,
InPublication = true,
ISBN = &quot;902-11-11-1111&quot;,
PageCount = &quot;100&quot;,
Price = 10,
ProductCategory = &quot;Book&quot;,
Title = &quot;My book3 in batch write&quot;
};
Book book2 = new Book
{
Id = 903,
InPublication = true,
ISBN = &quot;903-11-11-1111&quot;,
PageCount = &quot;200&quot;,
Price = 10,
ProductCategory = &quot;Book&quot;,
Title = &quot;My book4 in batch write&quot;
};
var bookBatch = context.CreateBatchWrite&lt;Book&gt;();
bookBatch.AddPutItems(new List&lt;Book&gt; { book1, book2 });
}
Console.WriteLine(&quot;Performing batch write in SingleTableBatchWrite().&quot;);
bookBatch.Execute();
private static void MultiTableBatchWrite(DynamoDBContext context)
{
// 1. New Forum item.
Forum newForum = new Forum
{
Name = &quot;Test BatchWrite Forum&quot;,
Threads = 0
};
var forumBatch = context.CreateBatchWrite&lt;Forum&gt;();
forumBatch.AddPutItem(newForum);
// 2. New Thread item.
Thread newThread = new Thread
{
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};
ForumName = &quot;S3 forum&quot;,
Subject = &quot;My sample question&quot;,
KeywordTags = new List&lt;string&gt; { &quot;S3&quot;, &quot;Bucket&quot; },
Message = &quot;Message text&quot;
DynamoDBOperationConfig config = new DynamoDBOperationConfig();
config.SkipVersionCheck = true;
var threadBatch = context.CreateBatchWrite&lt;Thread&gt;(config);
threadBatch.AddPutItem(newThread);
threadBatch.AddDeleteKey(&quot;some partition key value&quot;, &quot;some sort key value&quot;);
}
}
var superBatch = new MultiTableBatchWrite(forumBatch, threadBatch);
Console.WriteLine(&quot;Performing batch write in MultiTableBatchWrite().&quot;);
superBatch.Execute();
[DynamoDBTable(&quot;Reply&quot;)]
public class Reply
{
[DynamoDBHashKey] //Partition key
public string Id
{
get; set;
}
[DynamoDBRangeKey] //Sort key
public DateTime ReplyDateTime
{
get; set;
}
}
// Properties included implicitly.
public string Message
{
get; set;
}
// Explicit property mapping with object persistence model attributes.
[DynamoDBProperty(&quot;LastPostedBy&quot;)]
public string PostedBy
{
get; set;
}
// Property to store version number for optimistic locking.
[DynamoDBVersion]
public int? Version
{
get; set;
}
[DynamoDBTable(&quot;Thread&quot;)]
public class Thread
{
// PK mapping.
[DynamoDBHashKey]
//Partition key
public string ForumName
{
get; set;
}
[DynamoDBRangeKey]
//Sort key
public String Subject
{
get; set;
}
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}
// Implicit mapping.
public string Message
{
get; set;
}
public string LastPostedBy
{
get; set;
}
public int Views
{
get; set;
}
public int Replies
{
get; set;
}
public bool Answered
{
get; set;
}
public DateTime LastPostedDateTime
{
get; set;
}
// Explicit mapping (property and table attribute names are different.
[DynamoDBProperty(&quot;Tags&quot;)]
public List&lt;string&gt; KeywordTags
{
get; set;
}
// Property to store version number for optimistic locking.
[DynamoDBVersion]
public int? Version
{
get; set;
}
[DynamoDBTable(&quot;Forum&quot;)]
public class Forum
{
[DynamoDBHashKey]
//Partition key
public string Name
{
get; set;
}
// All the following properties are explicitly mapped,
// only to show how to provide mapping.
[DynamoDBProperty]
public int Threads
{
get; set;
}
[DynamoDBProperty]
public int Views
{
get; set;
}
[DynamoDBProperty]
public string LastPostBy
{
get; set;
}
[DynamoDBProperty]
public DateTime LastPostDateTime
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{
}
}
get; set;
}
[DynamoDBProperty]
public int Messages
{
get; set;
}
[DynamoDBTable(&quot;ProductCatalog&quot;)]
public class Book
{
[DynamoDBHashKey] //Partition key
public int Id
{
get; set;
}
public string Title
{
get; set;
}
public string ISBN
{
get; set;
}
public int Price
{
get; set;
}
public string PageCount
{
get; set;
}
public string ProductCategory
{
get; set;
}
public bool InPublication
{
get; set;
}
}
Example: Query and Scan in DynamoDB Using the AWS SDK
for .NET Object Persistence Model
The C# example in this section deﬁnes the following classes and maps them to the tables in DynamoDB.
For more information about creating the tables used in this example, see Creating Tables and Loading
Sample Data (p. 280).
• Book class maps to ProductCatalog table
• Forum, Thread, and Reply classes maps to the same name tables.
The example then executes the following query and scan operations using the DynamoDBContext.
• Get a book by Id.
The ProductCatalog table has Id as its primary key. It does not have a sort key as part of its primary
key. Therefore, you cannot query the table. You can get an item using its Id value.
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• Execute the following queries against the Reply table (the Reply table's primary key is composed of Id
and ReplyDateTime attributes. The ReplyDateTime is a sort key. Therefore, you can query this table).
• Find replies to a forum thread posted in the last 15 days.
• Find replies to a forum thread posted in a speciﬁc date range.
• Scan ProductCatalog table to ﬁnd books whose price is less than zero.
For performance reasons, you should use a query instead of a scan operation. However, there are times
you might need to scan a table. Suppose there was a data entry error and one of the book prices is set
to less than 0. This example scans the ProductCategory table to ﬁnd book items (ProductCategory is
book) at price of less than 0.
For instructions to create a working sample, see .NET Code Samples (p. 287).
Note
The following example does not work with .NET core as it does not support synchronous
methods. For more information, see AWS Asynchronous APIs for .NET.
Example
using
using
using
using
using
using
using
System;
System.Collections.Generic;
System.Configuration;
Amazon.DynamoDBv2;
Amazon.DynamoDBv2.DataModel;
Amazon.DynamoDBv2.DocumentModel;
Amazon.Runtime;
namespace com.amazonaws.codesamples
{
class HighLevelQueryAndScan
{
private static AmazonDynamoDBClient client = new AmazonDynamoDBClient();
static void Main(string[] args)
{
try
{
DynamoDBContext context = new DynamoDBContext(client);
// Get item.
GetBook(context, 101);
// Sample forum and thread to test queries.
string forumName = &quot;Amazon DynamoDB&quot;;
string threadSubject = &quot;DynamoDB Thread 1&quot;;
// Sample queries.
FindRepliesInLast15Days(context, forumName, threadSubject);
FindRepliesPostedWithinTimePeriod(context, forumName, threadSubject);
// Scan table.
FindProductsPricedLessThanZero(context);
Console.WriteLine(&quot;To continue, press Enter&quot;);
Console.ReadLine();
}
}
catch (AmazonDynamoDBException e) { Console.WriteLine(e.Message); }
catch (AmazonServiceException e) { Console.WriteLine(e.Message); }
catch (Exception e) { Console.WriteLine(e.Message); }
private static void GetBook(DynamoDBContext context, int productId)
{
Book bookItem = context.Load&lt;Book&gt;(productId);
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}
Console.WriteLine(&quot;\nGetBook: Printing result.....&quot;);
Console.WriteLine(&quot;Title: {0} \n No.Of threads:{1} \n No. of messages: {2}&quot;,
bookItem.Title, bookItem.ISBN, bookItem.PageCount);
private static void FindRepliesInLast15Days(DynamoDBContext context,
string forumName,
string threadSubject)
{
string replyId = forumName + &quot;#&quot; + threadSubject;
DateTime twoWeeksAgoDate = DateTime.UtcNow - TimeSpan.FromDays(15);
IEnumerable&lt;Reply&gt; latestReplies =
context.Query&lt;Reply&gt;(replyId, QueryOperator.GreaterThan, twoWeeksAgoDate);
Console.WriteLine(&quot;\nFindRepliesInLast15Days: Printing result.....&quot;);
foreach (Reply r in latestReplies)
Console.WriteLine(&quot;{0}\t{1}\t{2}\t{3}&quot;, r.Id, r.PostedBy, r.Message,
r.ReplyDateTime);
}
private static void FindRepliesPostedWithinTimePeriod(DynamoDBContext context,
string forumName,
string threadSubject)
{
string forumId = forumName + &quot;#&quot; + threadSubject;
Console.WriteLine(&quot;\nFindRepliesPostedWithinTimePeriod: Printing
result.....&quot;);
DateTime startDate = DateTime.UtcNow - TimeSpan.FromDays(30);
DateTime endDate = DateTime.UtcNow - TimeSpan.FromDays(1);
IEnumerable&lt;Reply&gt; repliesInAPeriod = context.Query&lt;Reply&gt;(forumId,
QueryOperator.Between, startDate, endDate);
foreach (Reply r in repliesInAPeriod)
Console.WriteLine(&quot;{0}\t{1}\t{2}\t{3}&quot;, r.Id, r.PostedBy, r.Message,
r.ReplyDateTime);
}
}
private static void FindProductsPricedLessThanZero(DynamoDBContext context)
{
int price = 0;
IEnumerable&lt;Book&gt; itemsWithWrongPrice = context.Scan&lt;Book&gt;(
new ScanCondition(&quot;Price&quot;, ScanOperator.LessThan, price),
new ScanCondition(&quot;ProductCategory&quot;, ScanOperator.Equal, &quot;Book&quot;)
);
Console.WriteLine(&quot;\nFindProductsPricedLessThanZero: Printing result.....&quot;);
foreach (Book r in itemsWithWrongPrice)
Console.WriteLine(&quot;{0}\t{1}\t{2}\t{3}&quot;, r.Id, r.Title, r.Price, r.ISBN);
}
[DynamoDBTable(&quot;Reply&quot;)]
public class Reply
{
[DynamoDBHashKey] //Partition key
public string Id
{
get; set;
}
[DynamoDBRangeKey] //Sort key
public DateTime ReplyDateTime
{
get; set;
}
// Properties included implicitly.
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}
public string Message
{
get; set;
}
// Explicit property mapping with object persistence model attributes.
[DynamoDBProperty(&quot;LastPostedBy&quot;)]
public string PostedBy
{
get; set;
}
// Property to store version number for optimistic locking.
[DynamoDBVersion]
public int? Version
{
get; set;
}
[DynamoDBTable(&quot;Thread&quot;)]
public class Thread
{
// PK mapping.
[DynamoDBHashKey] //Partition key
public string ForumName
{
get; set;
}
[DynamoDBRangeKey] //Sort key
public DateTime Subject
{
get; set;
}
// Implicit mapping.
public string Message
{
get; set;
}
public string LastPostedBy
{
get; set;
}
public int Views
{
get; set;
}
public int Replies
{
get; set;
}
public bool Answered
{
get; set;
}
public DateTime LastPostedDateTime
{
get; set;
}
// Explicit mapping (property and table attribute names are different.
[DynamoDBProperty(&quot;Tags&quot;)]
public List&lt;string&gt; KeywordTags
{
get; set;
}
// Property to store version number for optimistic locking.
[DynamoDBVersion]
public int? Version
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{
}
}
get; set;
[DynamoDBTable(&quot;Forum&quot;)]
public class Forum
{
[DynamoDBHashKey]
public string Name
{
get; set;
}
// All the following properties are explicitly mapped,
// only to show how to provide mapping.
[DynamoDBProperty]
public int Threads
{
get; set;
}
[DynamoDBProperty]
public int Views
{
get; set;
}
[DynamoDBProperty]
public string LastPostBy
{
get; set;
}
[DynamoDBProperty]
public DateTime LastPostDateTime
{
get; set;
}
[DynamoDBProperty]
public int Messages
{
get; set;
}
}
[DynamoDBTable(&quot;ProductCatalog&quot;)]
public class Book
{
[DynamoDBHashKey] //Partition key
public int Id
{
get; set;
}
public string Title
{
get; set;
}
public string ISBN
{
get; set;
}
public int Price
{
get; set;
}
public string PageCount
{
get; set;
}
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}
}
public string ProductCategory
{
get; set;
}
public bool InPublication
{
get; set;
}
Running the Code Samples In This Developer
Guide
The AWS SDKs provide broad support for DynamoDB in Java, JavaScript in the browser, .NET, Node.js,
PHP, Python, Ruby, C++, Go, Android, and iOS. To get started quickly with these languages, see Getting
Started with DynamoDB (p. 52).
The code samples in this Developer Guide provide more in-depth coverage of DynamoDB operations,
using the following programming languages:
• Java Code Samples (p. 285)
• .NET Code Samples (p. 287)
Before you can begin with this exercise, you will need to sign up for AWS, get your access key and secret
key, and set up the AWS Command Line Interface on your computer. If you haven't done so, see Setting
Up DynamoDB (Web Service) (p. 46).
Note
If you are using the downloadable version of DynamoDB, you need to use the AWS CLI to create
the tables and sample data. You also need to specify the --endpoint-url parameter with each
AWS CLI command. For more information, see Setting the Local Endpoint (p. 44).
Creating Tables and Loading Sample Data
In this section, you will use the AWS Management Console to create tables in DynamoDB. You will then
load data into these tables using the AWS Command Line Interface (AWS CLI).
These tables and their data are used as examples throughout this Developer Guide.
Note
If you are an application developer, we recommend that you also read Getting Started with
DynamoDB, where you use the downloadable version of DynamoDB. This lets you learn about
the DynamoDB low-level API for free, without having to pay any fees for throughput, storage, or
data transfer. For more information, see Getting Started with DynamoDB (p. 52).
Topics
• Step 1: Create Example Tables (p. 281)
• Step 2: Load Data into Tables (p. 283)
• Step 3: Query the Data (p. 284)
• Step 4: (Optional) Clean up (p. 285)
• Summary (p. 285)
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Step 1: Create Example Tables
In this section, you will use the AWS Management Console to create tables in DynamoDB for two simple
use cases.
Use Case 1: Product Catalog
Suppose you want to store product information in DynamoDB. Each product has its own distinct
attributes, so you will need to store diﬀerent information about each of these products.
You can create a ProductCatalog table, where each item is uniquely identiﬁed by a single, numeric
attribute: Id.
Table Name
Primary Key
ProductCatalog
Partition key: Id (Number)
Use Case 2: Forum Application
Suppose you want to build an application for message boards, or discussion forums. The Amazon
Web Services Discussion Forums is one example of such an application: Customers can engage with
the developer community, ask questions, or reply to other customers' posts. Each AWS service has a
dedicated forum. Anyone can start a new discussion thread by posting a message in a forum. Each thread
might receive any number of replies.
You can model this application by creating three tables: Forum, Thread, and Reply.
Table Name
Primary Key
Forum
Partition key: Name (String)
Thread
Partition key: ForumName (String)
Sort key: Subject (String)
Reply
Partition key: Id (String)
Sort key: ReplyDateTime (String)
The Reply table has a global secondary index named PostedBy-Message-Index. This index will facilitate
queries on two non-key attributes of the Reply table.
Index Name
Primary Key
PostedBy-Message-Index
Partition key: PostedBy (String)
Sort key: Message (String)
Create the ProductCatalog Table
1.
Open the DynamoDB console at https://console.aws.amazon.com/dynamodb/.
2.
Choose Create Table.
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3.
4.
In the Create DynamoDB table screen, do the following:
a.
In the Table name ﬁeld, type ProductCatalog.
b.
For the Primary key, in the Partition key ﬁeld, type Id. Set the data type to Number.
When the settings are as you want them, choose Create.
Create the Forum Table
1.
Open the DynamoDB console at https://console.aws.amazon.com/dynamodb/.
2.
Choose Create Table.
3.
In the Create DynamoDB table screen, do the following:
4.
a.
In the Table name ﬁeld, type Forum.
b.
For the Primary key, in the Partition key ﬁeld, type Name. Set the data type to String.
When the settings are as you want them, choose Create.
Create the Thread Table
1.
Open the DynamoDB console at https://console.aws.amazon.com/dynamodb/.
2.
Choose Create Table.
3.
In the Create DynamoDB table screen, do the following:
a.
In the Table name ﬁeld, type Thread.
b.
For the Primary key, do the following:
• In the Partition key ﬁeld, type ForumName. Set the data type to String.
• Choose Add sort key.
• In the Sort key ﬁeld, type Subject. Set the data type to String.
4.
When the settings are as you want them, choose Create.
Create the Reply Table
1.
Open the DynamoDB console at https://console.aws.amazon.com/dynamodb/.
2.
Choose Create Table.
3.
In the Create DynamoDB table screen, do the following:
a.
In the Table name ﬁeld, type Reply.
b.
For the Primary key, do the following:
• In the Partition key ﬁeld, type Id. Set the data type to String.
• Choose Add sort key.
• In the Sort key ﬁeld, type ReplyDateTime. Set the data type to String.
c.
In the Table settings section, deselect Use default settings.
d.
In the Secondary indexes section, choose Add index.
e.
In the Add index window, do the following:
• For the Primary key, do the following:
• In the Partition key ﬁeld, type PostedBy. Set the data type to String.
• Select Add sort key.
• In the Sort key ﬁeld, type Message. Set the data type to String.
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• In the Index name ﬁeld, type PostedBy-Message-Index.
• Set the Projected attributes to All.
• Choose Add index.
4.
When the settings are as you want them, choose Create.
Step 2: Load Data into Tables
In this step, you will load sample data into the tables that you created. You could enter the data
manually into the DynamoDB console; however, to save time, you will use the AWS Command Line
Interface instead.
Note
If you have not yet set up the AWS CLI, see Using the CLI (p. 49) for instructions.
You will download a .zip archive that contains JSON ﬁles with sample data for each table. For each ﬁle,
you will use the AWS CLI to load the data into DynamoDB. Each successful data load will produce the
following output:
{
}
&quot;UnprocessedItems&quot;: {}
Download the Sample Data File Archive
1.
Download the sample data archive (sampledata.zip) using this link:
• sampledata.zip
2.
Extract the .json data ﬁles from the archive.
3.
Copy the .json data ﬁles to your current directory.
Load the Sample Data Into DynamoDB Tables
1.
To load the ProductCatalog table with data, enter the following command:
aws dynamodb batch-write-item --request-items file://ProductCatalog.json
2.
To load the Forum table with data, enter the following command:
aws dynamodb batch-write-item --request-items file://Forum.json
3.
To load the Thread table with data, enter the following command:
aws dynamodb batch-write-item --request-items file://Thread.json
4.
To load the Reply table with data, enter the following command:
aws dynamodb batch-write-item --request-items file://Reply.json
Verify Data Load
You can use the AWS Management Console to verify the data that you loaded into the tables.
To verify the data using the AWS Management Console
1.
Open the DynamoDB console at https://console.aws.amazon.com/dynamodb/.
2.
In the navigation pane, choose Tables.
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3.
In the list of tables, choose ProductCatalog.
4.
Choose the Items tab to view the data that you loaded into the table.
5.
To view an item in the table, choose its Id. (If you want, you can also edit the item.)
6.
To return to the list of tables, choose Cancel.
Repeat this procedure for each of the other tables you created:
• Forum
• Thread
• Reply
Step 3: Query the Data
In this step, you will try some simple queries against the tables that you created, using the DynamoDB
console.
1.
Open the DynamoDB console at https://console.aws.amazon.com/dynamodb/.
2.
In the navigation pane, choose Tables.
3.
In the list of tables, choose Reply.
4.
Choose the Items tab to view the data that you loaded into the table.
5.
Choose the data ﬁltering link, located just below the Create item button.
When you do this, the console reveals a data ﬁltering pane.
6.
7.
In the data ﬁltering pane, do the following:
a.
Change the operation from Scan to Query.
b.
For the Partition key, enter the value Amazon DynamoDB#DynamoDB Thread 1.
c.
Choose Start. Only the items that match your query criteria are returned from the Reply table.
The Reply table has a global secondary index on the PostedBy and Message attributes. You can use
the data ﬁltering pane to query the index. Do the following:
a.
Change the query source from this:
[Table] Reply: Id, ReplyDateTime
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to this:
[Index] PostedBy-Message-Index: PostedBy, Message
b.
For the Partition key, enter the value User A.
c.
Choose Start. Only the items that match your query criteria are returned from PostedByMessage-Index.
Take some time to explore your other tables using the DynamoDB console:
• ProductCatalog
• Forum
• Thread
Step 4: (Optional) Clean up
This Amazon DynamoDB Developer Guide refers to these sample tables repeatedly, to help illustrate
table and item operations using the DynamoDB low-level API and various AWS SDKs. You might ﬁnd
these tables useful for reference, if you plan to read the rest of this Developer Guide.
However, if you don't want to keep these tables, you should delete them to avoid being charged for
resources you don't need.
To Delete the Sample Tables
1.
Open the DynamoDB console at https://console.aws.amazon.com/dynamodb/.
2.
In the navigation pane, choose Tables.
3.
In the list of tables, choose ProductCatalog.
4.
Choose Delete Table. You will be asked to conﬁrm your selection.
Repeat this procedure for each of the other tables you created:
• Forum
• Thread
• Reply
Summary
In this exercise, you used the DynamoDB console to create several tables in DynamoDB. You then used
the AWS CLI to load data into the tables, and performed some basic operations on the data using the
DynamoDB console.
The DynamoDB console and the AWS CLI are helpful for getting started quickly. However, you probably
want to learn more about how DynamoDB works, and how to write application programs with
DynamoDB. The rest of this Developer Guide addresses those topics.
Java Code Samples
Topics
• Java: Setting Your AWS Credentials (p. 286)
• Java: Setting the AWS Region and Endpoint (p. 287)
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This Developer Guide contains Java code snippets and ready-to-run programs. You can ﬁnd these code
samples in the following sections:
• Working with Items in DynamoDB (p. 327)
• Working with Tables in DynamoDB (p. 290)
• Working with Queries (p. 410)
• Working with Scans (p. 427)
• Improving Data Access with Secondary Indexes (p. 446)
• Java: DynamoDBMapper (p. 195)
• Capturing Table Activity with DynamoDB Streams (p. 518)
You can get started quickly by using Eclipse with the AWS Toolkit for Eclipse. In addition to a fullfeatured IDE, you also get the AWS SDK for Java with automatic updates, and preconﬁgured templates
for building AWS applications.
To Run the Java Code Samples (using Eclipse)
1.
Download and install the Eclipse IDE.
2.
Download and install the AWS Toolkit for Eclipse.
3.
Start Eclipse and from the Eclipse menu, choose File, New, and then Other.
4.
In Select a wizard, choose AWS, choose AWS Java Project, and then choose Next.
5.
In Create an AWS Java, do the following:
a.
In Project name, type a name for your project.
b.
In Select Account, choose your credentials proﬁle from the list.
If this is your ﬁrst time using the AWS Toolkit for Eclipse, choose Conﬁgure AWS Accounts to
set up your AWS credentials.
6.
Choose Finish to create the project.
7.
From the Eclipse menu, choose File, New, and then Class.
8.
In Java Class, type a name for your class in Name (use the same name as the code sample that you
want to run), and then choose Finish to create the class.
9.
Copy the code sample from the documentation page you are reading into the Eclipse editor.
10. To run the code, choose Run in the Eclipse menu.
The SDK for Java provides thread-safe clients for working with DynamoDB. As a best practice, your
applications should create one client and reuse the client between threads.
For more information, see the AWS SDK for Java.
Note
The code samples in this Developer Guide are intended for use with the latest version of the
AWS SDK for Java.
If you are using the AWS Toolkit for Eclipse, you can conﬁgure automatic updates for the SDK
for Java. To do this in Eclipse, go to Preferences and choose AWS Toolkit --&gt; AWS SDK for Java
--&gt; Download new SDKs automatically.
Java: Setting Your AWS Credentials
The SDK for Java requires that you provide AWS credentials to your application at runtime. The code
samples in this Developer Guide assume that you are using an AWS credentials ﬁle, as described in Set
Up Your AWS Credentials in the AWS SDK for Java Developer Guide.
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The following is an example of an AWS credentials ﬁle named ~/.aws/credentials, where the tilde
character (~) represents your home directory:
[default]
aws_access_key_id = AWS access key ID goes here
aws_secret_access_key = Secret key goes here
Java: Setting the AWS Region and Endpoint
By default, the code samples access DynamoDB in the US West (Oregon) region. You can change the
region by modifying the AmazonDynamoDB properties.
The following code snippet instantiates a new AmazonDynamoDB:
import com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
import com.amazonaws.regions.Regions;
...
// This client will default to US West (Oregon)
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard()
.withRegion(Regions.US_WEST_2)
.build();
You can use the withRegion method to run your code against Amazon DynamoDB in any region where
it is available. For a complete list, see AWS Regions and Endpoints in the Amazon Web Services General
Reference.
If you want to run the code samples using DynamoDB locally on your computer, you need to set the
endpoint, like this:
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().withEndpointConfiguration(
new AwsClientBuilder.EndpointConfiguration(&quot;http://localhost:8000&quot;, &quot;us-west-2&quot;))
.build();
.NET Code Samples
Topics
• .NET: Setting Your AWS Credentials (p. 288)
• .NET: Setting the AWS Region and Endpoint (p. 289)
This Developer Guide contains .NET code snippets and ready-to-run programs. You can ﬁnd these code
samples in the following sections:
•
•
•
•
Working with Items in DynamoDB (p. 327)
Working with Tables in DynamoDB (p. 290)
Working with Queries (p. 410)
Working with Scans (p. 427)
•
•
•
•
Improving Data Access with Secondary Indexes (p. 446)
.NET: Document Model (p. 232)
.NET: Object Persistence Model (p. 253)
Capturing Table Activity with DynamoDB Streams (p. 518)
You can get started quickly by using the AWS SDK for .NET with the Toolkit for Visual Studio.
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To Run the .NET Code Samples (using Visual Studio)
1.
Download and install Microsoft Visual Studio.
2.
Download and install the Toolkit for Visual Studio.
3.
Start Visual Studio and choose File, New, and then Project.
4.
In New Project, choose AWS Empty Project, and then choose OK.
5.
In AWS Access Credentials, choose Use existing proﬁle, choose your credentials proﬁle from the
list, and then choose OK.
If this is your ﬁrst time using Toolkit for Visual Studio, choose Use a new proﬁle to set up your AWS
credentials.
6.
In your Visual Studio project, choose the tab for your program's source code (Program.cs). Copy the
code sample from the documentation page you are reading into the Visual Studio editor, replacing
any other code that you see in the editor.
7.
If you see error messages of the form The type or namespace name...could not be found, you
need to install the AWS SDK assembly for DynamoDB as follows:
8.
a.
In Solution Explorer, open the context (right-click) menu for your project, and then choose
Manage NuGet Packages.
b.
In NuGet Package Manager, choose Browse.
c.
In the search box, type AWSSDK.DynamoDBv2 and wait for the search to complete.
d.
Choose AWSSDK.DynamoDBv2, and then choose Install.
e.
When the installation is complete, choose the Program.cs tab to return to your program.
To run the code, choose the Start button in the Visual Studio toolbar.
The AWS SDK for .NET provides thread-safe clients for working with DynamoDB. As a best practice, your
applications should create one client and reuse the client between threads.
For more information, see AWS SDK for .NET.
Note
The code samples in this Developer Guide are intended for use with the latest version of the
AWS SDK for .NET.
.NET: Setting Your AWS Credentials
The AWS SDK for .NET requires that you provide AWS credentials to your application at runtime. The
code samples in this Developer Guide assume that you are using the SDK Store to manage your AWS
credentials ﬁle, as described in Using the SDK Store in the AWS SDK for .NET Developer Guide.
The Toolkit for Visual Studio supports multiple sets of credentials from any number of accounts. Each
set is referred to as a proﬁle. Visual Studio adds entries to the project's App.config ﬁle so that your
application can ﬁnd the AWS credentials at runtime.
The following example shows the default App.config ﬁle that is generated when you create a new
project using Toolkit for Visual Studio:
&lt;?xml version=&quot;1.0&quot; encoding=&quot;utf-8&quot; ?&gt;
&lt;configuration&gt;
&lt;appSettings&gt;
&lt;add key=&quot;AWSProfileName&quot; value=&quot;default&quot;/&gt;
&lt;add key=&quot;AWSRegion&quot; value=&quot;us-west-2&quot; /&gt;
&lt;/appSettings&gt;
&lt;/configuration&gt;
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At runtime, the program uses the default set of AWS credentials, as speciﬁed by the AWSProfileName
entry. The AWS credentials themselves are kept in the SDK Store, in encrypted form. The Toolkit for
Visual Studio provides a graphical user interface for managing your credentials, all from within Visual
Studio. For more information, see Specifying Credentials in the AWS Toolkit for Visual Studio User Guide.
Note
By default, the code samples access DynamoDB in the US West (Oregon) region. You can change
the region by modifying the AWSRegion entry in the App.conﬁg ﬁle. You can set AWSRegion to
any AWS region where Amazon DynamoDB is available. For a complete list, see AWS Regions
and Endpoints in the Amazon Web Services General Reference.
.NET: Setting the AWS Region and Endpoint
By default, the code samples access DynamoDB in the US West (Oregon) region. You can change the
region by modifying the AWSRegion entry in the App.config ﬁle. Alternatively, you can change the region
by modifying the AmazonDynamoDBClient properties.
The following code snippet instantiates a new AmazonDynamoDBClient. The client is modiﬁed so that the
code runs against DynamoDB in a diﬀerent region.
AmazonDynamoDBConfig clientConfig = new AmazonDynamoDBConfig();
// This client will access the US East 1 region.
clientConfig.RegionEndpoint = RegionEndpoint.USEast1;
AmazonDynamoDBClient client = new AmazonDynamoDBClient(clientConfig);
For a complete list of regions, see AWS Regions and Endpoints in the Amazon Web Services General
Reference.
If you want to run the code samples using DynamoDB locally on your computer, you need to set the
endpoint:
AmazonDynamoDBConfig clientConfig = new AmazonDynamoDBConfig();
// Set the endpoint URL
clientConfig.ServiceURL = &quot;http://localhost:8000&quot;;
AmazonDynamoDBClient client = new AmazonDynamoDBClient(clientConfig);
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Working with DynamoDB
This chapter goes into details about the following topics:
Topics
• Working with Tables in DynamoDB (p. 290)
• Working with Items in DynamoDB (p. 327)
• Working with Queries (p. 410)
• Working with Scans (p. 427)
• Improving Data Access with Secondary Indexes (p. 446)
• Capturing Table Activity with DynamoDB Streams (p. 518)
Working with Tables in DynamoDB
This section describes how to use the AWS CLI and the AWS SDKs to create, update, and delete tables.
Note
You can also perform these same tasks using the AWS Management Console. For more
information, see Using the Console (p. 48))
This section also provides more information about throughput capacity, using DynamoDB auto scaling or
manually setting provisioned throughput.
Topics
• Basic Operations for Tables (p. 291)
• Throughput Settings for Reads and Writes (p. 294)
• Item Sizes and Capacity Unit Consumption (p. 296)
• Managing Throughput Capacity Automatically with DynamoDB Auto Scaling (p. 298)
• Tagging for DynamoDB (p. 314)
• Working with Tables: Java (p. 316)
• Working with Tables: .NET (p. 321)
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Basic Operations for Tables
Topics
• Creating a Table (p. 291)
• Describing a Table (p. 292)
• Updating a Table (p. 292)
• Deleting a Table (p. 293)
• Listing Table Names (p. 293)
• Describing Provisioned Throughput Limits (p. 293)
Creating a Table
Use the CreateTable operation to create a table. You must provide the following information:
• Table name. The name must conform to the DynamoDB naming rules, and must be unique for the
current AWS account and region. For example, you could create a People table in US East (N. Virginia)
and another People table in EU (Ireland) - however, these two tables would be entirely diﬀerent from
each other. For more information, see Naming Rules and Data Types (p. 11).
• Primary key. The primary key can consist of one attribute (partition key) or two attributes (partition
key and sort key). You need to provide the attribute names, data types, and the role of each attribute:
HASH (for a partition key) and RANGE (for a sort key). For more information, see Primary Key (p. 5).
• Throughput settings. You must specify the initial read and write throughput settings for the table.
You can modify these settings later, or enable DynamoDB auto scaling to manage the settings for
you. For more information, see Throughput Settings for Reads and Writes (p. 294) and Managing
Throughput Capacity Automatically with DynamoDB Auto Scaling (p. 298).
Example
The following AWS CLI example shows how to create a table (Music). The primary key consists of
Artist (partition key) and SongTitle (sort key), each of which has a data type of String. The maximum
throughput for this table is 10 read capacity units and 5 write capacity units.
aws dynamodb create-table \
--table-name Music \
--attribute-definitions \
AttributeName=Artist,AttributeType=S \
AttributeName=SongTitle,AttributeType=S \
--key-schema \
AttributeName=Artist,KeyType=HASH \
AttributeName=SongTitle,KeyType=RANGE \
--provisioned-throughput \
ReadCapacityUnits=10, \
WriteCapacityUnits=5
The CreateTable operation returns metadata for the table, as shown below:
{
&quot;TableDescription&quot;: {
&quot;AttributeDefinitions&quot;: [
{
&quot;AttributeName&quot;: &quot;Artist&quot;,
&quot;AttributeType&quot;: &quot;S&quot;
},
{
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&quot;AttributeName&quot;: &quot;SongTitle&quot;,
&quot;AttributeType&quot;: &quot;S&quot;
}
}
}
],
&quot;TableName&quot;: &quot;Music&quot;,
&quot;KeySchema&quot;: [
{
&quot;AttributeName&quot;: &quot;Artist&quot;,
&quot;KeyType&quot;: &quot;HASH&quot;
},
{
&quot;AttributeName&quot;: &quot;SongTitle&quot;,
&quot;KeyType&quot;: &quot;RANGE&quot;
}
],
&quot;TableStatus&quot;: &quot;CREATING&quot;,
&quot;CreationDateTime&quot;: 1491338657.039,
&quot;ProvisionedThroughput&quot;: {
&quot;NumberOfDecreasesToday&quot;: 0,
&quot;ReadCapacityUnits&quot;: 10,
&quot;WriteCapacityUnits&quot;: 5
},
&quot;TableSizeBytes&quot;: 0,
&quot;ItemCount&quot;: 0,
&quot;TableArn&quot;: &quot;arn:aws:dynamodb:us-east-1:123456789012:table/Music&quot;
The TableStatus element indicates the current state of the table (CREATING). It might take a while to
create the table, depending on the values you specify for ReadCapacityUnits and WriteCapacityUnits.
Larger values for these will require DynamoDB to allocate more resources for the table.
Describing a Table
To view details about a table, use the DescribeTable operation. You must provide the table name. The
output from DescribeTable is in the same format as that from CreateTable; it includes the timestamp
when the table was created, its key schema, its provisioned throughput settings, its estimated size, and
any secondary indexes that are present.
Example
aws dynamodb describe-table --table-name Music
The table is ready for use when the TableStatus has changed from CREATING to ACTIVE.
Note
If you issue a DescribeTable request immediately after a CreateTable request, DynamoDB
might return an error (ResourceNotFoundException). This is because DescribeTable uses an
eventually consistent query, and the metadata for your table might not be available at that
moment. Wait for a few seconds, and then try the DescribeTable request again.
For billing purposes, your DynamoDB storage costs include a per-item overhead of 100 bytes.
(For more information, go to DynamoDB Pricing). This extra 100 bytes per item is not used in
capacity unit calculations or by the DescribeTable operation.
Updating a Table
The UpdateTable operation allows you to do one of the following:
• Modify a table's provisioned throughput settings.
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• Manipulate global secondary indexes on the table (see Global Secondary Indexes (p. 448)).
• Enable or disable DynamoDB Streams on the table (see Capturing Table Activity with DynamoDB
Streams (p. 518)).
Example
This AWS CLI example shows how to modify a table's provisioned throughput settings:
aws dynamodb update-table --table-name Music \
--provisioned-throughput ReadCapacityUnits=20,WriteCapacityUnits=10
Note
When you issue an UpdateTable request, the status of the table changes from AVAILABLE to
UPDATING. The table remains fully available for use while it is UPDATING. When this process is
completed, the table status changes from UPDATING to AVAILABLE.
Deleting a Table
You can remove an unused table with the DeleteTable operation. Note that deleting a table is an
unrecoverable operation.
This AWS CLI example shows how to delete a table:
aws dynamodb delete-table --table-name Music
When you issue a DeleteTable request, the table's status changes from ACTIVE to DELETING. It might take
a while to delete the table, depending on the resources it uses (such as the data stored in the table, and
any streams or indexes on the table).
When the DeleteTable operation concludes, the table no longer exists in DynamoDB.
Listing Table Names
The ListTables operation returns the names of the DynamoDB tables for the current AWS account and
region.
Example
aws dynamodb list-tables
Describing Provisioned Throughput Limits
The DescribeLimits operation returns the current read and write capacity limits for the current AWS
account and region.
Example
aws dynamodb describe-limits
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The output shows the upper limits of read and write capacity units for the current AWS account and
region.
For more information about these limits, and how to request limit increases, see Provisioned Throughput
Default Limits (p. 724).
Throughput Settings for Reads and Writes
Topics
• Read Capacity Units (p. 294)
• Write Capacity Units (p. 295)
• Request Throttling and Burst Capacity (p. 295)
• Choosing Initial Throughput Settings (p. 295)
• Modifying Throughput Settings (p. 296)
When you create a new table in DynamoDB, you must specify its provisioned throughput capacity—the
amount of read and write activity that the table will be able to support. DynamoDB uses this information
to reserve suﬃcient system resources to meet your throughput requirements.
Note
You can optionally allow DynamoDB auto scaling to manage your table's throughput capacity;
however, you still must provide initial settings for read and write capacity when you create the
table. DynamoDB auto scaling uses these initial settings as a starting point, and then adjusts
them dynamically in response to your application's requirements.
For more information, see Managing Throughput Capacity Automatically with DynamoDB Auto
Scaling (p. 298).
DynamoDB automatically distributes your data across partitions, which are stored on multiple servers
in the AWS Cloud. (For more information, see Partitions and Data Distribution (p. 18).) For optimal
throughput, you should distribute read requests as evenly as possible across these partitions. For
example, suppose that you provision a table with 10,000 read capacity units. If you issue 10,000 read
requests for a single item in the table, all of the read activity will be concentrated on a single partition.
However, if you spread your requests across all items in the table, DynamoDB can access the partitions in
parallel.
As your application data and access requirements change, you might need to adjust your table's
throughput settings. If you're using DynamoDB auto scaling, the throughput settings are automatically
adjusted in response to actual workloads. You can also use the UpdateTable operation to manually
adjust your table's throughput capacity. You might decide to do this if you need to bulk-load data from
an existing data store into your new DynamoDB table. You could create the table with a large write
throughput setting and then reduce this setting after the bulk data load is complete.
You specify throughput requirements in terms of capacity units—the amount of data your application
needs to read or write per second. You can modify these settings later, if needed, or enable DynamoDB
auto scaling to modify them automatically.
Read Capacity Units
A read capacity unit represents one strongly consistent read per second, or two eventually consistent
reads per second, for an item up to 4 KB in size.
Note
To learn more about DynamoDB read consistency models, see Read Consistency (p. 15).
For example, suppose that you create a table with 10 provisioned read capacity units. This will allow you
to perform 10 strongly consistent reads per second, or 20 eventually consistent reads per second, for
items up to 4 KB.
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Reading an item larger than 4 KB consumes more read capacity units. For example a strongly consistent
read of an item that is 8 KB (4 KB &times; 2) consumes 2 read capacity units. An eventually consistent read on
that same item consumes only 1 read capacity unit.
Item sizes for reads are rounded up to the next 4 KB multiple. For example, reading a 3,500-byte item
will consume the same throughput as reading a 4 KB item.
Write Capacity Units
A write capacity unit represents one write per second, for an item up to 1 KB in size.
For example, suppose that you create a table with 10 write capacity units. This will allow you to perform
10 writes per second, for items up to 1 KB size per second.
Item sizes for writes are rounded up to the next 1 KB multiple. For example, writing a 500-byte item will
consume the same throughput as writing a 1 KB item.
Request Throttling and Burst Capacity
If your application performs reads or writes at a higher rate than your table can support, DynamoDB
will begin to throttle those requests. When DynamoDB throttles a read or write, it returns a
ProvisionedThroughputExceededException to the caller. The application can then take appropriate
action, such as waiting for a short interval before retrying the request.
Note
We recommend that you use the AWS SDKs for software development. The AWS SDKs provide
built-in support for retrying throttled requests; you do not need to write this logic yourself. For
more information, see Error Retries and Exponential Backoﬀ (p. 193).
The DynamoDB console displays Amazon CloudWatch metrics for your tables, so you can monitor
throttled read requests and write requests. If you encounter excessive throttling, you should consider
increasing your table's provisioned throughput settings.
In some cases, DynamoDB will use burst capacity to accommodate reads or writes in excess of your
table's throughput settings. With burst capacity, unexpected read or write requests can succeed where
they otherwise would be throttled. Burst capacity is available on a best-eﬀort basis, and DynamoDB
does not guarantee that this capacity is always available. For more information, see Use Burst Capacity
Sparingly (p. 666).
Choosing Initial Throughput Settings
Every application has diﬀerent requirements for reading and writing from a database. When you are
determining the initial throughput settings for a DynamoDB table, take the following inputs into
consideration:
• Item sizes. Some items are small enough that they can be read or written using a single capacity unit.
Larger items will require multiple capacity units. By estimating the sizes of the items that will be in
your table, you can specify accurate settings for your table's provisioned throughput.
• Expected read and write request rates. In addition to item size, you should estimate the number of
reads and writes you need to perform per second.
• Read consistency requirements. Read capacity units are based on strongly consistent read operations,
which consume twice as many database resources as eventually consistent reads. You should
determine whether your application requires strongly consistent reads, or whether it can relax this
requirement and perform eventually consistent reads instead. (Read operations in DynamoDB are
eventually consistent, by default; you can request strongly consistent reads for these operations if
necessary.)
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Note
For recommendations on provisioned throughput and related topics, see Best Practices for
Tables (p. 659).
Modifying Throughput Settings
If you have enabled DynamoDB auto scaling for a table, then its throughput capacity will be dynamically
adjusted in response to actual usage. No manual intervention is required.
You can modify your table's provisioned throughput settings using the AWS Management Console
or the UpdateTable operation . You can increase throughput capacity as often as needed, and
decrease it up to nine times per table in a single UTC calendar day. For more information, see Limits in
DynamoDB (p. 724).
Item Sizes and Capacity Unit Consumption
Topics
• Capacity Unit Consumption for Reads (p. 296)
• Capacity Unit Consumption for Writes (p. 297)
Before you choose read and write capacity settings for your table, you should ﬁrst understand your data
and how your application will access it. These inputs can help you determine your table's overall storage
and throughput needs, and how much throughput capacity your application will require. DynamoDB
tables are schemaless, except for the primary key, so the items in a table can all have diﬀerent attributes,
sizes, and data types.
The total size of an item is the sum of the lengths of its attribute names and values. You can use the
following guidelines to estimate attribute sizes:
• Strings are Unicode with UTF-8 binary encoding. The size of a string is (length of attribute name) +
(number of UTF-8-encoded bytes).
• Numbers are variable length, with up to 38 signiﬁcant digits. Leading and trailing zeroes are trimmed.
The size of a number is approximately (length of attribute name) + (1 byte per two signiﬁcant digits) +
(1 byte).
• A binary value must be encoded in base64 format before it can be sent to DynamoDB, but the value's
raw byte length is used for calculating size. The size of a binary attribute is (length of attribute name) +
(number of raw bytes).
• The size of a null attribute or a Boolean attribute is (length of attribute name) + (1 byte).
• An attribute of type List or Map requires 3 bytes of overhead, regardless of its contents. The size of
a List or Map is (length of attribute name) + sum (size of nested elements) + (3 bytes) . The size of an
empty List or Map is (length of attribute name) + (3 bytes).
Note
We recommend that you choose shorter attribute names rather than long ones. This will help
you optimize capacity unit consumption and reduce the amount of storage required for your
data.
Capacity Unit Consumption for Reads
The following describes how DynamoDB read operations consume read capacity units:
• GetItem—reads a single item from a table. To determine the number of capacity units GetItem will
consume, take the item size and round it up to the next 4 KB boundary. If you speciﬁed a strongly
consistent read, this is the number of capacity units required. For an eventually consistent read (the
default), take this number and divide it by two.
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For example, if you read an item that is 3.5 KB, DynamoDB rounds the item size to 4 KB. If you read an
item of 10 KB, DynamoDB rounds the item size to 12 KB.
• BatchGetItem—reads up to 100 items, from one or more tables. DynamoDB processes each item in the
batch as an individual GetItem request, so DynamoDB ﬁrst rounds up the size of each item to the next
4 KB boundary, and then calculates the total size. The result is not necessarily the same as the total
size of all the items. For example, if BatchGetItem reads a 1.5 KB item and a 6.5 KB item, DynamoDB
will calculate the size as 12 KB (4 KB + 8 KB), not 8 KB (1.5 KB + 6.5 KB).
• Query—reads multiple items that have the same partition key value. All of the items returned are
treated as a single read operation, where DynamoDB computes the total size of all items and then
rounds up to the next 4 KB boundary. For example, suppose your query returns 10 items whose
combined size is 40.8 KB. DynamoDB rounds the item size for the operation to 44 KB. If a query
returns 1500 items of 64 bytes each, the cumulative size is 96 KB.
• Scan—reads all of the items in a table. DynamoDB considers the size of the items that are evaluated,
not the size of the items returned by the scan.
If you perform a read operation on an item that does not exist, DynamoDB will still consume provisioned
read throughput: A strongly consistent read request consumes one read capacity unit, while an
eventually consistent read request consumes 0.5 of a read capacity unit.
For any operation that returns items, you can request a subset of attributes to retrieve; however, doing so
has no impact on the item size calculations. In addition, Query and Scan can return item counts instead of
attribute values. Getting the count of items uses the same quantity of read capacity units and is subject
to the same item size calculations, because DynamoDB has to read each item in order to increment the
count.
Read Operations and Read Consistency
The preceding calculations assume strongly consistent read requests. For an eventually consistent read
request, the operation consumes only half the capacity units. For an eventually consistent read, if total
item size is 80 KB, the operation consumes only 10 capacity units.
Capacity Unit Consumption for Writes
The following describes how DynamoDB write operations consume write capacity units:
• PutItem—writes a single item to a table. If an item with the same primary key exists in the table, the
operation replaces the item. For calculating provisioned throughput consumption, the item size that
matters is the larger of the two.
• UpdateItem—modiﬁes a single item in the table. DynamoDB considers the size of the item as it
appears before and after the update. The provisioned throughput consumed reﬂects the larger of
these item sizes. Even if you update just a subset of the item's attributes, UpdateItem will still consume
the full amount of provisioned throughput (the larger of the &quot;before&quot; and &quot;after&quot; item sizes).
• DeleteItem—removes a single item from a table. The provisioned throughput consumption is based on
the size of the deleted item.
• BatchWriteItem—writes up to 25 items to one or more tables. DynamoDB processes each item in the
batch as an individual PutItem or DeleteItem request (updates are not supported), so DynamoDB ﬁrst
rounds up the size of each item to the next 1 KB boundary, and then calculates the total size. The
result is not necessarily the same as the total size of all the items. For example, if BatchWriteItem
writes a 500 byte item and a 3.5 KB item, DynamoDB will calculate the size as 5 KB (1 KB + 4 KB), not 4
KB (500 bytes + 3.5 KB).
For PutItem, UpdateItem, and DeleteItem operations, DynamoDB rounds the item size up to the next 1
KB. For example, if you put or delete an item of 1.6 KB, DynamoDB rounds the item size up to 2 KB.
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PutItem, UpdateItem, and DeleteItem allow conditional writes, where you specify an expression that
must evaluate to true in order for the operation to succeed. If the expression evaluates to false,
DynamoDB will still consume write capacity units from the table:
• If the item exists, the number of write capacity units consumed depends on the size of the item. (For
example, a failed conditional write of a 1 KB item would consume one write capacity unit; if the item
were twice that size, the failed conditional write would consume two write capacity units.)
• If the item does not exist, DynamoDB will consume one write capacity unit.
Managing Throughput Capacity Automatically with
DynamoDB Auto Scaling
Note
To get started quickly with DynamoDB auto scaling, see Using the AWS Management Console
With DynamoDB Auto Scaling (p. 300).
Many database workloads are cyclical in nature or are diﬃcult to predict in advance. For example,
consider a social networking app where most of the users are active during daytime hours. The database
must be able to handle the daytime activity, but there's no need for the same levels of throughput
at night. Another example might be a new mobile gaming app that is experiencing rapid adoption.
If the game becomes too popular, it could exceed the available database resources, resulting in slow
performance and unhappy customers. These kinds of workloads often require manual intervention to
scale database resources up or down in response to varying usage levels.
DynamoDB auto scaling uses the AWS Application Auto Scaling service to dynamically adjust provisioned
throughput capacity on your behalf, in response to actual traﬃc patterns. This enables a table or a global
secondary index to increase its provisioned read and write capacity to handle sudden increases in traﬃc,
without throttling. When the workload decreases, Application Auto Scaling decreases the throughput so
that you don't pay for unused provisioned capacity.
Note
If you use the AWS Management Console to create a table or a global secondary index,
DynamoDB auto scaling is enabled by default. You can modify your auto scaling settings at any
time. For more information, see Using the AWS Management Console With DynamoDB Auto
Scaling (p. 300).
With Application Auto Scaling, you create a scaling policy for a table or a global secondary index. The
scaling policy speciﬁes whether you want to scale read capacity or write capacity (or both), and the
minimum and maximum provisioned capacity unit settings for the table or index.
The scaling policy also contains a target utilization—the percentage of consumed provisioned
throughput at a point in time. Application Auto Scaling uses a target tracking algorithm to adjust the
provisioned throughput of the table (or index) upward or downward in response to actual workloads, so
that the actual capacity utilization remains at or near your target utilization.
Note
In addition to tables, DynamoDB auto scaling also supports global secondary indexes. Every
global secondary index has its own provisioned throughput capacity, separate from that of its
base table. When you create a scaling policy for a global secondary index, Application Auto
Scaling adjusts the provisioned throughput settings for the index to ensure that its actual
utilization stays at or near your desired utilization ratio.
How DynamoDB Auto Scaling Works
Note
To get started quickly with DynamoDB auto scaling, see Using the AWS Management Console
With DynamoDB Auto Scaling (p. 300).
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The following diagram provides a high-level overview of how DynamoDB auto scaling manages
throughput capacity for a table:
The following steps summarize the auto scaling process as shown in the previous diagram:
1. You create an Application Auto Scaling policy for your DynamoDB table.
2. DynamoDB publishes consumed capacity metrics to Amazon CloudWatch.
3. If the table's consumed capacity exceeds your target utilization (or falls below the target) for a
speciﬁc length of time, Amazon CloudWatch triggers an alarm. You can view the alarm on the AWS
Management Console and receive notiﬁcations using Amazon Simple Notiﬁcation Service (Amazon
SNS).
4. The CloudWatch alarm invokes Application Auto Scaling to evaluate your scaling policy.
5. Application Auto Scaling issues an UpdateTable request to adjust your table's provisioned throughput.
6. DynamoDB processes the UpdateTable request, dynamically increasing (or decreasing) the table's
provisioned throughput capacity so that it approaches your target utilization.
To understand how DynamoDB auto scaling works, suppose that you have a table named ProductCatalog.
The table is bulk-loaded with data infrequently, so it doesn't incur very much write activity. However,
it does experience a high degree of read activity, which varies over time. By monitoring the Amazon
CloudWatch metrics for ProductCatalog, you determine that the table requires 1,200 read capacity
units (to avoid DynamoDB throttling read requests when activity is at its peak). You also determine that
ProductCatalog requires 150 read capacity units at a minimum, when read traﬃc is at its lowest point.
Within the range of 150 to 1,200 read capacity units, you decide that a target utilization of 70 percent
would be appropriate for the ProductCatalog table. Target utilization is the ratio of consumed capacity
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units to provisioned capacity units, expressed as a percentage. Application Auto Scaling uses its target
tracking algorithm to ensure that the provisioned read capacity of ProductCatalog is adjusted as required
so that utilization remains at or near 70 percent.
Note
DynamoDB auto scaling modiﬁes provisioned throughput settings only when the actual
workload stays elevated (or depressed) for a sustained period of several minutes. The
Application Auto Scaling target tracking algorithm seeks to keep the target utilization at or near
your chosen value over the long term.
Sudden, short-duration spikes of activity are accommodated by the table's built-in burst
capacity. For more information, see Use Burst Capacity Sparingly (p. 666).
To enable DynamoDB auto scaling for the ProductCatalog table, you create a scaling policy. This policy
speciﬁes the table or global secondary index that you want to manage, which capacity type to manage
(read capacity or write capacity), the upper and lower boundaries for the provisioned throughput
settings, and your target utilization.
When you create a scaling policy, Application Auto Scaling creates a pair of Amazon CloudWatch alarms
on your behalf. Each pair represents your upper and lower boundaries for provisioned throughput
settings. These CloudWatch alarms are triggered when the table's actual utilization deviates from your
target utilization for a sustained period of time.
When one of the CloudWatch alarms is triggered, Amazon SNS sends you a notiﬁcation (if you have
enabled it). The CloudWatch alarm then invokes Application Auto Scaling, which in turn notiﬁes
DynamoDB to adjust the ProductCatalog table's provisioned capacity upward or downward, as
appropriate.
Usage Notes
Before you begin using DynamoDB auto scaling, you should be aware of the following:
• DynamoDB auto scaling can increase read capacity or write capacity as often as necessary,
in accordance with your auto scaling policy. You can decrease the ReadCapacityUnits or
WriteCapacityUnits settings for a table up to four times any time per day. A day is deﬁned according
to the GMT time zone. Additionally, if there was no decrease in the past four hours, an additional
dial down is allowed, eﬀectively bringing maximum number of decreases in a day to nine times (4
decreases in the ﬁrst 4 hours, and 1 decrease for each of the subsequent 4 hour windows in a day). All
other DynamoDB limits remain in eﬀect, as described in Limits in DynamoDB.
• DynamoDB auto scaling doesn't prevent you from manually modifying provisioned throughput
settings. These manual adjustments don't aﬀect any existing CloudWatch alarms that are related
to DynamoDB auto scaling. If you make manual adjustments, we recommend that you refresh your
Application Auto Scaling policy so that the CloudWatch thresholds are updated accordingly.
• If you enable DynamoDB auto scaling for a table that has one or more global secondary indexes, we
highly recommend that you also apply auto scaling uniformly to those indexes. You can do this by
choosing Apply same settings to global secondary indexes in the AWS Management Console. For
more information, see Enabling DynamoDB Auto Scaling on Existing Tables (p. 302).
Using the AWS Management Console With DynamoDB Auto
Scaling
Topics
• Before You Begin: Grant User Permissions for DynamoDB Auto Scaling (p. 301)
• Creating a New Table with Auto Scaling Enabled (p. 302)
• Enabling DynamoDB Auto Scaling on Existing Tables (p. 302)
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• Viewing Auto Scaling Activities in the Console (p. 303)
• Modifying or Disabling DynamoDB Auto Scaling Settings (p. 303)
When you use the AWS Management Console to create a new table, DynamoDB auto scaling is enabled
for that table by default. You can also use the console to enable auto scaling for existing tables, modify
auto scaling settings, or disable auto scaling.
Before You Begin: Grant User Permissions for DynamoDB Auto Scaling
In AWS Identity and Access Management (IAM), the AWS-managed policy DynamoDBFullAccess provides
the required permissions for using the DynamoDB console. However, for DynamoDB auto scaling, IAM
users will require some additional privileges.
Important
application-autoscaling:* permissions are required to delete an autoscaling enabled table.
The AWS-managed policy DynamoDBFullAccess attached next includes such permissions.
To set up an IAM user for DynamoDB console access and DynamoDB auto scaling, add the following two
policies:
To attach the AmazonDynamoDBFullAccess policy
1.
Open the IAM console at https://console.aws.amazon.com/iam/.
2.
On the IAM console dashboard, choose Users, and then choose your IAM user from the list.
3.
On the Summary page, choose Add permissions.
4.
Choose Attach existing policies directly.
5.
From the list of policies, choose AmazonDynamoDBFullAccess, and then choose Next: Review.
6.
Choose Add permissions.
To add a custom inline policy
1.
On the IAM console dashboard, choose Users, and then choose your IAM user from the list.
2.
On the Summary page, choose Add inline policy.
3.
On the Set Permissions page, choose Custom Policy, and then choose Select.
4.
On the Review Policy page, do the following:
a.
Policy Name—type a name for the policy. For example: MyDynamoDBAutoscalingPolicy
b.
Policy Document—copy and paste the following:
{
}
5.
&quot;Version&quot;: &quot;2012-10-17&quot;,
&quot;Statement&quot;: [
{
&quot;Effect&quot;: &quot;Allow&quot;,
&quot;Action&quot;: [
&quot;iam:AttachRolePolicy&quot;,
&quot;iam:CreatePolicy&quot;,
&quot;iam:CreateRole&quot;
],
&quot;Resource&quot;: &quot;*&quot;
}
]
After you have done this, choose Apply Policy.
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Creating a New Table with Auto Scaling Enabled
Note
DynamoDB auto scaling requires the presence of a role (DynamoDBAutoscaleRole) that performs
auto scaling actions on your behalf. You do not need to create this role yourself. Instead, the
DynamoDB console creates the role automatically, when you create a new table with auto
scaling for the ﬁrst time.
To create a new table with auto scaling enabled
1.
2.
Open the DynamoDB console at https://console.aws.amazon.com/dynamodb/.
Choose Create Table.
3.
On the Create DynamoDB table page, enter a Table name and Primary key details.
4.
If you see the following message, then your AWS account does not currently have the
DynamoDBAutoscaleRole:
In this case, do the following:
1. Deselect Use default settings.
2. In the Auto scaling section, ensure that New role: DynamoDBAutoscaleRole is selected.
5.
Otherwise, simply ensure that Use default settings is selected. (Your AWS account already has
DynamoDBAutoscaleRole.)
When the settings are as you want them, choose Create. Your table will be created with default auto
scaling parameters.
Enabling DynamoDB Auto Scaling on Existing Tables
Note
DynamoDB auto scaling requires the presence of a role (DynamoDBAutoscaleRole) that performs
auto scaling actions on your behalf. The DynamoDB console will create the role for you when
you create a new table with auto scaling for the ﬁrst time.
If you have never used DynamoDB auto scaling before, see Creating a New Table with
Auto Scaling Enabled (p. 302). The DynamoDB console creates DynamoDBAutoscaleRole
automatically, when you create a new table with auto scaling for the ﬁrst time.
To enable DynamoDB auto scaling for an existing table, do the following:
1.
Open the DynamoDB console at https://console.aws.amazon.com/dynamodb/.
2.
3.
Choose the table that you want to work with, and then choose Capacity.
In the Auto Scaling section, do the following:
•
Select Read capacity, Write capacity, or both. (For write capacity, note that you can choose
Same settings as read.) For each of these, do the following:
•
•
•
•
Target utilization—Type your target utilization percentage for the table.
Minimum provisioned capacity—Type your lower boundary for the auto scaling range.
Maximum provisioned capacity—Type your upper boundary for the auto scaling range.
Apply same settings to global secondary indexes—Leave this option at its default setting
(enabled).
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Note
For best performance, we recommend that you enable Apply same settings to
global secondary indexes. This option allows DynamoDB auto scaling to uniformly
scale all the global secondary indexes on the base table. This includes existing global
secondary indexes, and any others that you create for this table in the future.
With this option enabled, you can't set a scaling policy on an individual global
secondary index.
(For Write capacity, note that you can choose Same settings as read.)
In the IAM Role section, ensure that Existing role with pre-deﬁned policies is selected, and
that Role Name is set to DynamoDBAutoscaleRole.
4.
When the settings are as you want them, choose Save.
Viewing Auto Scaling Activities in the Console
As your application drives read and write traﬃc to your table, DynamoDB auto scaling dynamically
modiﬁes the table's throughput settings.
To view these auto scaling activities in the DynamoDB console, choose the table that you want to work
with. Choose Capacity, and then expand the Scaling activities section. When your table's throughput
settings are modiﬁed, you will see informational messages here.
Modifying or Disabling DynamoDB Auto Scaling Settings
You can use the AWS Management Console to modify your DynamoDB auto scaling settings. To do this,
go to the Capacity tab for your table and modify the settings in the Auto Scaling section. For more
information about these settings, see Enabling DynamoDB Auto Scaling on Existing Tables (p. 302).
To disable DynamoDB auto scaling, go to the Capacity tab for your table and clear Read capacity, Write
capacity, or both.
Using the AWS CLI to Manage DynamoDB Auto Scaling
Topics
• Before You Begin (p. 304)
• Step 1: Create a Service Role for Application Auto Scaling (p. 304)
• Step 2: Create a DynamoDB Table (p. 305)
• Step 3: Register a Scalable Target (p. 306)
• Step 4: Create a Scaling Policy (p. 306)
• Step 5: Drive Write Traﬃc to TestTable (p. 308)
• Step 6: View Application Auto Scaling Actions (p. 308)
• (Optional) Step 7: Clean Up (p. 309)
Instead of using the AWS Management Console, you can use the AWS Command Line Interface (AWS
CLI) to manage DynamoDB auto scaling. The tutorial in this section demonstrates how to install and
conﬁgure the AWS CLI for managing DynamoDB auto scaling . In this tutorial, you do the following:
• Create a DynamoDB table named TestTable. The initial throughput settings are 5 read capacity units
and 5 write capacity units.
• Create an Application Auto Scaling policy for TestTable. The policy seeks to maintain a 50 percent
target ratio between consumed write capacity and provisioned write capacity. The range for this
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metric is between 5 and 10 write capacity units. (Application Auto Scaling is not allowed to adjust the
throughput beyond this range.)
• Run a Python program to drive write traﬃc to TestTable. When the target ratio exceeds 50 percent for
a sustained period of time, Application Auto Scaling notiﬁes DynamoDB to adjust the throughput of
TestTable upward, so that the 50 percent target utilization can be maintained.
• Verify that DynamoDB has successfully adjusted the provisioned write capacity for TestTable.
Before You Begin
You need to complete the following tasks before starting the tutorial.
Install the AWS CLI
If you haven't already done so, you must install and conﬁgure the AWS CLI. To do this, go to the AWS
Command Line Interface User Guide and follow these instructions:
• Installing the AWS CLI
• Conﬁguring the AWS CLI
Install Python
Part of this tutorial requires you to run a Python program (see Step 5: Drive Write Traﬃc to
TestTable (p. 308)). If you don't already have Python installed, you can download it using this link:
https://www.python.org/downloads
Step 1: Create a Service Role for Application Auto Scaling
Before you can work with Application Auto Scaling, you must create a service role for it. A service role
is an IAM role that authorizes an AWS service to act on your behalf. The service role allows Application
Auto Scaling to modify the provisioned throughput settings for your DynamoDB resources, as if you were
modifying them yourself.
In this step, you create an IAM policy and attach that policy to an IAM role. You can then assign the role
to Application Auto Scaling so that it can perform DynamoDB operations on your behalf.
1.
Create a ﬁle named trust-relationship.json with the following contents:
{
}
2.
&quot;Version&quot;: &quot;2012-10-17&quot;,
&quot;Statement&quot;: [
{
&quot;Effect&quot;: &quot;Allow&quot;,
&quot;Principal&quot;: {
&quot;Service&quot;: &quot;application-autoscaling.amazonaws.com&quot;
},
&quot;Action&quot;: &quot;sts:AssumeRole&quot;
}
]
Create the service role:
aws iam create-role \
--role-name MyIAMAutoscalingServiceRole \
--assume-role-policy-document file://trust-relationship.json
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3.
Create a ﬁle named service-role-policy.json with the following contents:
{
}
4.
&quot;Version&quot;: &quot;2012-10-17&quot;,
&quot;Statement&quot;: [
{
&quot;Effect&quot;: &quot;Allow&quot;,
&quot;Action&quot;: [
&quot;dynamodb:DescribeTable&quot;,
&quot;dynamodb:UpdateTable&quot;,
&quot;cloudwatch:PutMetricAlarm&quot;,
&quot;cloudwatch:DescribeAlarms&quot;,
&quot;cloudwatch:DeleteAlarms&quot;
],
&quot;Resource&quot;: &quot;*&quot;
}
]
Create an IAM policy for the service role:
aws iam create-policy \
--policy-name MyIAMAutoscalingServicePolicy \
--policy-document file://service-role-policy.json
In the output, take note of the Amazon Resource Name (ARN) for the policy you created. For
example: arn:aws:iam::111122223333:policy/MyIAMAutoscalingServicePolicy
5.
Attach the policy to the service role:
aws iam attach-role-policy \
--role-name MyIAMAutoscalingServiceRole \
--policy-arn arn
Replace arn with the actual policy ARN from the previous step.
Step 2: Create a DynamoDB Table
In this step, you use the AWS CLI to create TestTable. The primary key consists of pk (partition key) and
sk (sort key). Both of these attributes are of type Number. The initial throughput settings are 5 read
capacity units and 5 write capacity units.
1.
Use the following AWS CLI command to create the table:
aws dynamodb create-table \
--table-name TestTable \
--attribute-definitions \
AttributeName=pk,AttributeType=N \
AttributeName=sk,AttributeType=N \
--key-schema \
AttributeName=pk,KeyType=HASH \
AttributeName=sk,KeyType=RANGE \
--provisioned-throughput ReadCapacityUnits=5,WriteCapacityUnits=5
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2.
To check the status of the table, use the following command:
aws dynamodb describe-table \
--table-name TestTable \
--query &quot;Table.[TableName,TableStatus,ProvisionedThroughput]&quot;
The table is ready for use when its status is ACTIVE.
Step 3: Register a Scalable Target
You will now register the table's write capacity as a scalable target with Application Auto Scaling. This
allows Application Auto Scaling to adjust the provisioned write capacity for TestTable, but only within the
range of 5 to 10 capacity units.
1.
When you register the scalable target, you specify the ARN for MyIAMAutoscalingServiceRole,
which you created in Step 1: Create a Service Role for Application Auto Scaling (p. 304). Type the
following command to retrieve the role ARN:
aws iam get-role \
--role-name MyIAMAutoscalingServiceRole \
--query &quot;Role.Arn&quot;
Now type the following command to register the scalable target. (Replace roleARN with the ARN for
MyIAMAutoscalingServiceRole.)
aws application-autoscaling register-scalable-target \
--service-namespace dynamodb \
--resource-id &quot;table/TestTable&quot; \
--scalable-dimension &quot;dynamodb:table:WriteCapacityUnits&quot; \
--min-capacity 5 \
--max-capacity 10 \
--role-arn roleARN
2.
To verify the registration, use the following command:
aws application-autoscaling describe-scalable-targets \
--service-namespace dynamodb \
--resource-id &quot;table/TestTable&quot;
Step 4: Create a Scaling Policy
In this step, you create a scaling policy for TestTable. The policy deﬁnes the details under which
Application Auto Scaling can adjust your table's provisioned throughput, and what actions to take when
it does so. You associate this policy with the scalable target that you deﬁned in the previous step (write
capacity units for the TestTable table).
The policy contains the following elements:
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• PredefinedMetricSpecification—The metric that Application Auto Scaling is allowed to adjust. For
DynamoDB, the following values are valid values for PredefinedMetricType:
• DynamoDBReadCapacityUtilization
• DynamoDBWriteCapacityUtilization
• ScaleOutCooldown—The minimum amount of time (in seconds) between each Application Auto Scaling
event that increases provisioned throughput. This parameter allows Application Auto Scaling to
continuously, but not aggressively, increase the throughput in response to real-world workloads. The
default setting for ScaleOutCooldown is 0.
• ScaleInCooldown—The minimum amount of time (in seconds) between each Application Auto Scaling
event that decreases provisioned throughput. This parameter allows Application Auto Scaling to
decrease the throughput gradually and predictably. The default setting for ScaleInCooldown is 0.
• TargetValue—Application Auto Scaling ensures that the ratio of consumed capacity to provisioned
capacity stays at or near this value. You deﬁne TargetValue as a percentage.
Note
To further understand how TargetValue works, suppose that you have a table with a
provisioned throughput setting of 200 write capacity units. You decide to create a scaling policy
for this table, with a TargetValue of 70 percent.
Now suppose that you begin driving write traﬃc to the table so that the actual write throughput
is 150 capacity units. The consumed-to-provisioned ratio is now (150 / 200), or 75 percent. This
ratio exceeds your target, so Application Auto Scaling increases the provisioned write capacity to
215 so that the ratio is (150 / 215), or 69.77 percent—as close to your TargetValue as possible,
but not exceeding it.
For TestTable, you set TargetValue to 50 percent. Application Auto Scaling adjusts the table's provisioned
throughput within the range of 5 to 10 capacity units (see Step 3: Register a Scalable Target (p. 306))
so that the consumed-to-provisioned ratio remains at or near 50 percent. You set the values for
ScaleOutCooldown and ScaleInCooldown to 60 seconds.
1.
Create a ﬁle named scaling-policy.json with the following contents:
{
}
2.
&quot;PredefinedMetricSpecification&quot;: {
&quot;PredefinedMetricType&quot;: &quot;DynamoDBWriteCapacityUtilization&quot;
},
&quot;ScaleOutCooldown&quot;: 60,
&quot;ScaleInCooldown&quot;: 60,
&quot;TargetValue&quot;: 50.0
Use the following AWS CLI command to create the policy:
aws application-autoscaling put-scaling-policy \
--service-namespace dynamodb \
--resource-id &quot;table/TestTable&quot; \
--scalable-dimension &quot;dynamodb:table:WriteCapacityUnits&quot; \
--policy-name &quot;MyScalingPolicy&quot; \
--policy-type &quot;TargetTrackingScaling&quot; \
--target-tracking-scaling-policy-configuration file://scaling-policy.json
3.
In the output, note that Application Auto Scaling has created two CloudWatch alarms—one each for
the upper and lower boundary of the scaling target range.
4.
Use the following AWS CLI command to view more details about the scaling policy:
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aws application-autoscaling describe-scaling-policies \
--service-namespace dynamodb \
--resource-id &quot;table/TestTable&quot; \
--policy-name &quot;MyScalingPolicy&quot;
5.
In the output, verify that the policy settings match your speciﬁcations from Step 3: Register a
Scalable Target (p. 306) and Step 4: Create a Scaling Policy (p. 306).
Step 5: Drive Write Traﬃc to TestTable
Now you can test your scaling policy by writing data to TestTable. To do this, you will run a Python
program.
1.
Create a ﬁle named bulk-load-test-table.py with the following contents:
import boto3
dynamodb = boto3.resource('dynamodb')
table = dynamodb.Table(&quot;TestTable&quot;)
filler = &quot;x&quot; * 100000
i = 0
while (i &lt; 10):
j = 0
while (j &lt; 10):
print (i, j)
table.put_item(
Item={
'pk':i,
'sk':j,
'filler':{&quot;S&quot;:filler}
}
)
j += 1
i += 1
2.
Type the following command to run the program:
python bulk-load-test-table.py
The provisioned write capacity for TestTable is very low (5 write capacity units), so the program stalls
occasionally due to write throttling. This is expected behavior.
Let the program continue running, while you move on to the next step.
Step 6: View Application Auto Scaling Actions
In this step, you view the Application Auto Scaling actions that are initiated on your behalf. You also
verify that Application Auto Scaling has updated the provisioned write capacity for TestTable.
1.
Type the following command to view the Application Auto Scaling actions:
aws application-autoscaling describe-scaling-activities \
--service-namespace dynamodb
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Rerun this command occasionally, while the Python program is running. (It will take several minutes
before your scaling policy is invoked.) You should eventually see the following output:
...
{
&quot;ScalableDimension&quot;: &quot;dynamodb:table:WriteCapacityUnits&quot;,
&quot;Description&quot;: &quot;Setting write capacity units to 10.&quot;,
&quot;ResourceId&quot;: &quot;table/TestTable&quot;,
&quot;ActivityId&quot;: &quot;0cc6fb03-2a7c-4b51-b67f-217224c6b656&quot;,
&quot;StartTime&quot;: 1489088210.175,
&quot;ServiceNamespace&quot;: &quot;dynamodb&quot;,
&quot;EndTime&quot;: 1489088246.85,
&quot;Cause&quot;: &quot;monitor alarm AutoScaling-table/TestTable-AlarmHigh-1bb3c8db-1b97-4353baf1-4def76f4e1b9 in state ALARM triggered policy MyScalingPolicy&quot;,
&quot;StatusMessage&quot;: &quot;Successfully set write capacity units to 10. Change successfully
fulfilled by dynamodb.&quot;,
&quot;StatusCode&quot;: &quot;Successful&quot;
},
...
This indicates that Application Auto Scaling has issued an UpdateTable request to DynamoDB.
2.
Type the following command to verify that DynamoDB increased the table's write capacity:
aws dynamodb describe-table \
--table-name TestTable \
--query &quot;Table.[TableName,TableStatus,ProvisionedThroughput]&quot;
The WriteCapacityUnits should have been scaled from 5 to 10.
(Optional) Step 7: Clean Up
In this tutorial, you created several resources. You can delete these resources if you no longer need them.
1.
Delete the scaling policy for TestTable:
aws application-autoscaling delete-scaling-policy \
--service-namespace dynamodb \
--resource-id &quot;table/TestTable&quot; \
--scalable-dimension &quot;dynamodb:table:WriteCapacityUnits&quot; \
--policy-name &quot;MyScalingPolicy&quot;
2.
Deregister the scalable target:
aws application-autoscaling deregister-scalable-target \
--service-namespace dynamodb \
--resource-id &quot;table/TestTable&quot; \
--scalable-dimension &quot;dynamodb:table:WriteCapacityUnits&quot;
3.
Delete the TestTable table:
aws dynamodb delete-table --table-name TestTable
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4.
To delete the IAM policy, you must ﬁrst determine its ARN:
aws iam list-policies --scope Local
In the output, take note of the ARN for MyIAMAutoscalingServicePolicy. For example:
arn:aws:iam::111122223333:policy/MyIAMAutoscalingServicePolicy
5.
Detach the policy from the service role:
aws iam detach-role-policy \
--role-name MyIAMAutoscalingServiceRole \
--policy-arn arn
Replace arn with the actual policy ARN from the previous step.
You can now delete the policy:
aws iam delete-policy \
--policy-arn arn
Finally, delete the service role:
aws iam delete-role \
--role-name MyIAMAutoscalingServiceRole
Application Programming With DynamoDB Auto Scaling
In addition to using the AWS Management Console and AWS CLI, you can write applications that interact
with DynamoDB auto scaling. This section contains two Java programs that you can use to test this
functionality:
• EnableDynamoDBAutoscaling.java
• DisableDynamoDBAutoscaling.java
Enabling Application Auto Scaling for a Table
The following program shows an example of setting up an auto scaling policy for a DynamoDB table
(TestTable). It proceeds as follows:
• The program registers write capacity units as a scalable target for TestTable. The range for this metric
is between 5 and 10 write capacity units.
• After the scalable target is created, the program builds a target tracking conﬁguration. The policy
seeks to maintain a 50 percent target ratio between consumed write capacity and provisioned write
capacity.
• The program then creates the scaling policy, based on the target tracking conﬁguration.
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The program requires that you supply an ARN for a valid Application Auto Scaling service role. (For
example: &quot;arn:aws:iam::122517410325:role/MyIAMAutoscalingServiceRole.) In the following program,
replace SERVICE_ROLE_ARN_GOES_HERE with the actual ARN. For more information, see Step 1: Create a
Service Role for Application Auto Scaling (p. 304).
package com.amazonaws.codesamples.autoscaling;
import com.amazonaws.services.applicationautoscaling.AWSApplicationAutoScalingClient;
import com.amazonaws.services.applicationautoscaling.model.DescribeScalableTargetsRequest;
import com.amazonaws.services.applicationautoscaling.model.DescribeScalableTargetsResult;
import com.amazonaws.services.applicationautoscaling.model.DescribeScalingPoliciesRequest;
import com.amazonaws.services.applicationautoscaling.model.DescribeScalingPoliciesResult;
import com.amazonaws.services.applicationautoscaling.model.MetricType;
import com.amazonaws.services.applicationautoscaling.model.PolicyType;
import com.amazonaws.services.applicationautoscaling.model.PredefinedMetricSpecification;
import com.amazonaws.services.applicationautoscaling.model.PutScalingPolicyRequest;
import com.amazonaws.services.applicationautoscaling.model.RegisterScalableTargetRequest;
import com.amazonaws.services.applicationautoscaling.model.ScalableDimension;
import com.amazonaws.services.applicationautoscaling.model.ServiceNamespace;
import
com.amazonaws.services.applicationautoscaling.model.TargetTrackingScalingPolicyConfiguration;
public class EnableDynamoDBAutoscaling {
static AWSApplicationAutoScalingClient aaClient = new
AWSApplicationAutoScalingClient();
public static void main(String args[]) {
ServiceNamespace ns = ServiceNamespace.Dynamodb;
ScalableDimension tableWCUs = ScalableDimension.DynamodbTableWriteCapacityUnits;
String resourceID = &quot;table/TestTable&quot;;
// Define the scalable target
RegisterScalableTargetRequest rstRequest = new RegisterScalableTargetRequest()
.withServiceNamespace(ns)
.withResourceId(resourceID)
.withScalableDimension(tableWCUs)
.withMinCapacity(5)
.withMaxCapacity(10)
.withRoleARN(&quot;SERVICE_ROLE_ARN_GOES_HERE&quot;);
try {
aaClient.registerScalableTarget(rstRequest);
} catch (Exception e) {
System.err.println(&quot;Unable to register scalable target: &quot;);
System.err.println(e.getMessage());
}
// Verify that the target was created
DescribeScalableTargetsRequest dscRequest = new DescribeScalableTargetsRequest()
.withServiceNamespace(ns)
.withScalableDimension(tableWCUs)
.withResourceIds(resourceID);
try {
DescribeScalableTargetsResult dsaResult =
aaClient.describeScalableTargets(dscRequest);
System.out.println(&quot;DescribeScalableTargets result: &quot;);
System.out.println(dsaResult);
System.out.println();
} catch (Exception e) {
System.err.println(&quot;Unable to describe scalable target: &quot;);
System.err.println(e.getMessage());
}
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System.out.println();
// Configure a scaling policy
TargetTrackingScalingPolicyConfiguration targetTrackingScalingPolicyConfiguration =
new TargetTrackingScalingPolicyConfiguration()
.withPredefinedMetricSpecification(
new PredefinedMetricSpecification()
.withPredefinedMetricType(MetricType. DynamoDBWriteCapacityUtilization))
.withTargetValue(50.0)
.withScaleInCooldown(60)
.withScaleOutCooldown(60);
// Create the scaling policy, based on your configuration
PutScalingPolicyRequest pspRequest = new PutScalingPolicyRequest()
.withServiceNamespace(ns)
.withScalableDimension(tableWCUs)
.withResourceId(resourceID)
.withPolicyName(&quot;MyScalingPolicy&quot;)
.withPolicyType(PolicyType.TargetTrackingScaling)
.withTargetTrackingScalingPolicyConfiguration(targetTrackingScalingPolicyConfiguration);
try {
aaClient.putScalingPolicy(pspRequest);
} catch (Exception e) {
System.err.println(&quot;Unable to put scaling policy: &quot;);
System.err.println(e.getMessage());
}
// Verify that the scaling policy was created
DescribeScalingPoliciesRequest dspRequest = new DescribeScalingPoliciesRequest()
.withServiceNamespace(ns)
.withScalableDimension(tableWCUs)
.withResourceId(resourceID);
try {
DescribeScalingPoliciesResult dspResult =
aaClient.describeScalingPolicies(dspRequest);
System.out.println(&quot;DescribeScalingPolicies result: &quot;);
System.out.println(dspResult);
} catch (Exception e) {
e.printStackTrace();
System.err.println(&quot;Unable to describe scaling policy: &quot;);
System.err.println(e.getMessage());
}
}
}
Disabling Application Auto Scaling for a Table
The following program reverses the previous process. It removes the auto scaling policy, and then
deregisters the scalable target.
package com.amazonaws.codesamples.autoscaling;
import
import
import
import
import
import
import
import
com.amazonaws.services.applicationautoscaling.AWSApplicationAutoScalingClient;
com.amazonaws.services.applicationautoscaling.model.DeleteScalingPolicyRequest;
com.amazonaws.services.applicationautoscaling.model.DeregisterScalableTargetRequest;
com.amazonaws.services.applicationautoscaling.model.DescribeScalableTargetsRequest;
com.amazonaws.services.applicationautoscaling.model.DescribeScalableTargetsResult;
com.amazonaws.services.applicationautoscaling.model.DescribeScalingPoliciesRequest;
com.amazonaws.services.applicationautoscaling.model.DescribeScalingPoliciesResult;
com.amazonaws.services.applicationautoscaling.model.ScalableDimension;
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import com.amazonaws.services.applicationautoscaling.model.ServiceNamespace;
public class DisableDynamoDBAutoscaling {
static AWSApplicationAutoScalingClient aaClient = new
AWSApplicationAutoScalingClient();
public static void main(String args[]) {
ServiceNamespace ns = ServiceNamespace.Dynamodb;
ScalableDimension tableWCUs = ScalableDimension.DynamodbTableWriteCapacityUnits;
String resourceID = &quot;table/TestTable&quot;;
// Delete the scaling policy
DeleteScalingPolicyRequest delSPRequest = new DeleteScalingPolicyRequest()
.withServiceNamespace(ns)
.withScalableDimension(tableWCUs)
.withResourceId(resourceID)
.withPolicyName(&quot;MyScalingPolicy&quot;);
try {
aaClient.deleteScalingPolicy(delSPRequest);
} catch (Exception e) {
System.err.println(&quot;Unable to delete scaling policy: &quot;);
System.err.println(e.getMessage());
}
// Verify that the scaling policy was deleted
DescribeScalingPoliciesRequest descSPRequest = new DescribeScalingPoliciesRequest()
.withServiceNamespace(ns)
.withScalableDimension(tableWCUs)
.withResourceId(resourceID);
try {
DescribeScalingPoliciesResult dspResult =
aaClient.describeScalingPolicies(descSPRequest);
System.out.println(&quot;DescribeScalingPolicies result: &quot;);
System.out.println(dspResult);
} catch (Exception e) {
e.printStackTrace();
System.err.println(&quot;Unable to describe scaling policy: &quot;);
System.err.println(e.getMessage());
}
System.out.println();
// Remove the scalable target
DeregisterScalableTargetRequest delSTRequest = new DeregisterScalableTargetRequest()
.withServiceNamespace(ns)
.withScalableDimension(tableWCUs)
.withResourceId(resourceID);
try {
aaClient.deregisterScalableTarget(delSTRequest);
} catch (Exception e) {
System.err.println(&quot;Unable to deregister scalable target: &quot;);
System.err.println(e.getMessage());
}
// Verify that the scalable target was removed
DescribeScalableTargetsRequest dscRequest = new DescribeScalableTargetsRequest()
.withServiceNamespace(ns)
.withScalableDimension(tableWCUs)
.withResourceIds(resourceID);
try {
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DescribeScalableTargetsResult dsaResult =
aaClient.describeScalableTargets(dscRequest);
System.out.println(&quot;DescribeScalableTargets result: &quot;);
System.out.println(dsaResult);
System.out.println();
} catch (Exception e) {
System.err.println(&quot;Unable to describe scalable target: &quot;);
System.err.println(e.getMessage());
}
}
}
Tagging for DynamoDB
You can label DynamoDB resources with tags. Tags allow you to categorize your resources in diﬀerent
ways, for example, by purpose, owner, environment, or other criteria. Tags can help you:
• Quickly identify a resource based on the tags you've assigned to it.
• See AWS bills broken down by tags.
Note
Any Local Secondary Indexes (LSI) and Global Secondary Indexes (GSI) related to tagged
tables are labeled with the same tags automatically. Currently, DynamoDB Streams usage
cannot be tagged.
Tagging is supported by AWS services like Amazon EC2, Amazon S3, DynamoDB, and more. Eﬃcient
tagging can provide cost insights by allowing you to create reports across services that carry a speciﬁc
tag.
To get started with tagging, you should:
1. Understand Tagging Restrictions (p. 314).
2. Create tags by using Tagging Operations (p. 315).
3. Use Cost Allocation Reports (p. 315) to track your AWS costs per active tag.
Finally, it is good practice to follow optimal tagging strategies. For information, see AWS Tagging
Strategies.
Tagging Restrictions
Each tag consists of a key and a value, both of which you deﬁne. The following restrictions apply:
• Each DynamoDB table can have only one tag with the same key. If you try to add an existing tag (same
key), the existing tag value will be updated to the new value.
• Tag keys and values are case sensitive.
• Maximum key length: 128 Unicode characters
• Maximum value length: 256 Unicode characters
• Allowed characters are letters, whitespace, and numbers, plus the following special characters: + - = .
_:/
• Maximum number of tags per resource: 50
• AWS-assigned tag names and values are automatically assigned the aws: preﬁx, which you cannot
assign. AWS-assigned tag names do not count toward the tag limit of 50. User-assigned tag names
have the preﬁx user: in the cost allocation report.
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Tagging for DynamoDB
• You cannot tag a resource at the same time you create it. Tagging is a separate action that can be
performed only after the resource is created.
• You cannot backdate the application of a tag.
Tagging Operations
This section describes how to use the DynamoDB console or CLI to add, list, edit, or delete tags. You can
then activate these user-deﬁned tags so that they appear on the Billing and Cost Management console
for cost allocation tracking. For more information, see Cost Allocation Reports (p. 315).
For bulk editing, you can also use the Tag Editor in the AWS Management Console. For more information,
see Working with Tag Editor.
To use the API instead, see Amazon DynamoDB API Reference.
Topics
• Tagging (console) (p. 315)
• Tagging (CLI) (p. 315)
Tagging (console)
To use the console to add, list, edit, or delete tags:
1. Open the DynamoDB console at https://console.aws.amazon.com/dynamodb/home.
2. Choose a table, and then choose the Settings tab.
You can add, list, edit, or delete tags here. In this example, the Movies tag was created with a value of
moviesProd for the Movies table.
Tagging (CLI)
To add the Owner tag with a value of blueTeam for the Movies table:
aws dynamodb tag-resource \
--resource-arn arn:aws:dynamodb:us-east-1:123456789012:table/Movies \
--tags Key=Owner,Value=blueTeam
To list all of the tags associated with the Movies table:
aws dynamodb list-tags-of-resource \
--resource-arn arn:aws:dynamodb:us-east-1:123456789012:table/Movies
Cost Allocation Reports
AWS uses tags to organize resource costs on your cost allocation report. AWS provides two types of cost
allocation tags:
• An AWS-generated tag. AWS deﬁnes, creates, and applies this tag for you.
• User-deﬁned tags. You deﬁne, create, and apply these tags.
You must activate both types of tags separately before they can appear in Cost Explorer or on a cost
allocation report.
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To activate AWS-generated tags:
1. Sign in to the AWS Management Console and open the Billing and Cost Management console at
https://console.aws.amazon.com/billing/home#/.
2. In the navigation pane, choose Cost Allocation Tags.
3. Under AWS-Generated Cost Allocation Tags, choose Activate.
To activate user-deﬁned tags:
1. Sign in to the AWS Management Console and open the Billing and Cost Management console at
https://console.aws.amazon.com/billing/home#/.
2. In the navigation pane, choose Cost Allocation Tags.
3. Under User-Deﬁned Cost Allocation Tags, choose Activate.
After you create and activate tags, AWS generates a cost allocation report with your usage and costs
grouped by your active tags. The cost allocation report includes all of your AWS costs for each billing
period. The report includes both tagged and untagged resources, so that you can clearly organize the
charges for resources.
Note
Currently, any data transferred out from DynamoDB won't be broken down by tags on cost
allocation reports.
For more information, see Using Cost Allocation Tags.
Working with Tables: Java
Topics
• Creating a Table (p. 316)
• Updating a Table (p. 317)
• Deleting a Table (p. 318)
• Listing Tables (p. 318)
• Example: Create, Update, Delete, and List Tables Using the AWS SDK for Java Document
API (p. 319)
You can use the AWS SDK for Java to create, update, and delete tables, list all the tables in your account,
or get information about a speciﬁc table.
The following are the common steps for table operations using the AWS SDK for Java Document API.
Creating a Table
To create a table, you must provide the table name, its primary key, and the provisioned throughput
values. The following code snippet creates an example table that uses a numeric type attribute Id as its
primary key.
To create a table using the AWS SDK for Java API:
1. Create an instance of the DynamoDB class.
2. Instantiate a CreateTableRequest to provide the request information.
You must provide the table name, attribute deﬁnitions, key schema, and provisioned throughput
values.
3. Execute the createTable method by providing the request object as a parameter.
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The following code snippet demonstrates the preceding steps.
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
DynamoDB dynamoDB = new DynamoDB(client);
List&lt;AttributeDefinition&gt; attributeDefinitions= new ArrayList&lt;AttributeDefinition&gt;();
attributeDefinitions.add(new
AttributeDefinition().withAttributeName(&quot;Id&quot;).withAttributeType(&quot;N&quot;));
List&lt;KeySchemaElement&gt; keySchema = new ArrayList&lt;KeySchemaElement&gt;();
keySchema.add(new KeySchemaElement().withAttributeName(&quot;Id&quot;).withKeyType(KeyType.HASH));
CreateTableRequest request = new CreateTableRequest()
.withTableName(tableName)
.withKeySchema(keySchema)
.withAttributeDefinitions(attributeDefinitions)
.withProvisionedThroughput(new ProvisionedThroughput()
.withReadCapacityUnits(5L)
.withWriteCapacityUnits(6L));
Table table = dynamoDB.createTable(request);
table.waitForActive();
The table will not be ready for use until DynamoDB creates it and sets its status to ACTIVE. The
createTable request returns a Table object that you can use to obtain more information about the table.
Example
TableDescription tableDescription =
dynamoDB.getTable(tableName).describe();
System.out.printf(&quot;%s: %s \t ReadCapacityUnits: %d \t WriteCapacityUnits: %d&quot;,
tableDescription.getTableStatus(),
tableDescription.getTableName(),
tableDescription.getProvisionedThroughput().getReadCapacityUnits(),
tableDescription.getProvisionedThroughput().getWriteCapacityUnits());
You can call the describe method of the client to get table information at any time.
Example
TableDescription tableDescription = dynamoDB.getTable(tableName).describe();
Updating a Table
You can update only the provisioned throughput values of an existing table. Depending on you
application requirements, you might need to update these values.
Note
You can increase throughput capacity as often as needed, and decrease it up to nine times per
table in a single UTC calendar day. For more information, see Limits in DynamoDB (p. 724).
To update a table using the AWS SDK for Java API:
1. Create an instance of the Table class.
2. Create an instance of the ProvisionedThroughput class to provide the new throughput values.
3. Execute the updateTable method by providing the ProvisionedThroughput instance as a parameter.
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The following code snippet demonstrates the preceding steps.
Example
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
DynamoDB dynamoDB = new DynamoDB(client);
Table table = dynamoDB.getTable(&quot;ProductCatalog&quot;);
ProvisionedThroughput provisionedThroughput = new ProvisionedThroughput()
.withReadCapacityUnits(15L)
.withWriteCapacityUnits(12L);
table.updateTable(provisionedThroughput);
table.waitForActive();
Deleting a Table
To delete a table:
1. Create an instance of the Table class.
2. Create an instance of the DeleteTableRequest class and provide the table name that you want to
delete.
3. Execute the deleteTable method by providing the Table instance as a parameter.
The following code snippet demonstrates the preceding steps.
Example
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
DynamoDB dynamoDB = new DynamoDB(client);
Table table = dynamoDB.getTable(&quot;ProductCatalog&quot;);
table.delete();
table.waitForDelete();
Listing Tables
To list tables in your account, create an instance of DynamoDB and execute the listTables method. The
ListTables operation requires no parameters.
Example
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
DynamoDB dynamoDB = new DynamoDB(client);
TableCollection&lt;ListTablesResult&gt; tables = dynamoDB.listTables();
Iterator&lt;Table&gt; iterator = tables.iterator();
while (iterator.hasNext()) {
Table table = iterator.next();
System.out.println(table.getTableName());
}
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Example: Create, Update, Delete, and List Tables Using the AWS
SDK for Java Document API
The following code sample uses the AWS SDK for Java Document API to create, update, and delete a
table (ExampleTable). As part of the table update, it increases the provisioned throughput values. The
example also lists all the tables in your account and gets the description of a speciﬁc table. For step-bystep instructions to run the following example, see Java Code Samples (p. 285).
// Copyright 2012-2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
// Licensed under the Apache License, Version 2.0.
package com.amazonaws.codesamples.document;
import java.util.ArrayList;
import java.util.Iterator;
import
import
import
import
import
import
import
import
import
import
import
import
com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
com.amazonaws.services.dynamodbv2.document.DynamoDB;
com.amazonaws.services.dynamodbv2.document.Table;
com.amazonaws.services.dynamodbv2.document.TableCollection;
com.amazonaws.services.dynamodbv2.model.AttributeDefinition;
com.amazonaws.services.dynamodbv2.model.CreateTableRequest;
com.amazonaws.services.dynamodbv2.model.KeySchemaElement;
com.amazonaws.services.dynamodbv2.model.KeyType;
com.amazonaws.services.dynamodbv2.model.ListTablesResult;
com.amazonaws.services.dynamodbv2.model.ProvisionedThroughput;
com.amazonaws.services.dynamodbv2.model.TableDescription;
public class DocumentAPITableExample {
static AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
static DynamoDB dynamoDB = new DynamoDB(client);
static String tableName = &quot;ExampleTable&quot;;
public static void main(String[] args) throws Exception {
createExampleTable();
listMyTables();
getTableInformation();
updateExampleTable();
}
deleteExampleTable();
static void createExampleTable() {
try {
List&lt;AttributeDefinition&gt; attributeDefinitions = new
ArrayList&lt;AttributeDefinition&gt;();
attributeDefinitions.add(new
AttributeDefinition().withAttributeName(&quot;Id&quot;).withAttributeType(&quot;N&quot;));
List&lt;KeySchemaElement&gt; keySchema = new ArrayList&lt;KeySchemaElement&gt;();
keySchema.add(new
KeySchemaElement().withAttributeName(&quot;Id&quot;).withKeyType(KeyType.HASH)); // Partition
// key
CreateTableRequest request = new
CreateTableRequest().withTableName(tableName).withKeySchema(keySchema)
.withAttributeDefinitions(attributeDefinitions).withProvisionedThroughput(
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new
ProvisionedThroughput().withReadCapacityUnits(5L).withWriteCapacityUnits(6L));
System.out.println(&quot;Issuing CreateTable request for &quot; + tableName);
Table table = dynamoDB.createTable(request);
System.out.println(&quot;Waiting for &quot; + tableName + &quot; to be created...this may take
a while...&quot;);
table.waitForActive();
getTableInformation();
}
catch (Exception e) {
System.err.println(&quot;CreateTable request failed for &quot; + tableName);
System.err.println(e.getMessage());
}
}
static void listMyTables() {
TableCollection&lt;ListTablesResult&gt; tables = dynamoDB.listTables();
Iterator&lt;Table&gt; iterator = tables.iterator();
System.out.println(&quot;Listing table names&quot;);
}
while (iterator.hasNext()) {
Table table = iterator.next();
System.out.println(table.getTableName());
}
static void getTableInformation() {
System.out.println(&quot;Describing &quot; + tableName);
TableDescription tableDescription = dynamoDB.getTable(tableName).describe();
System.out.format(
&quot;Name: %s:\n&quot; + &quot;Status: %s \n&quot; + &quot;Provisioned Throughput (read capacity units/
sec): %d \n&quot;
+ &quot;Provisioned Throughput (write capacity units/sec): %d \n&quot;,
tableDescription.getTableName(), tableDescription.getTableStatus(),
tableDescription.getProvisionedThroughput().getReadCapacityUnits(),
tableDescription.getProvisionedThroughput().getWriteCapacityUnits());
}
static void updateExampleTable() {
Table table = dynamoDB.getTable(tableName);
System.out.println(&quot;Modifying provisioned throughput for &quot; + tableName);
try {
table.updateTable(new
ProvisionedThroughput().withReadCapacityUnits(6L).withWriteCapacityUnits(7L));
}
table.waitForActive();
}
catch (Exception e) {
System.err.println(&quot;UpdateTable request failed for &quot; + tableName);
System.err.println(e.getMessage());
}
static void deleteExampleTable() {
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Table table = dynamoDB.getTable(tableName);
try {
System.out.println(&quot;Issuing DeleteTable request for &quot; + tableName);
table.delete();
System.out.println(&quot;Waiting for &quot; + tableName + &quot; to be deleted...this may take
a while...&quot;);
}
table.waitForDelete();
}
catch (Exception e) {
System.err.println(&quot;DeleteTable request failed for &quot; + tableName);
System.err.println(e.getMessage());
}
}
Working with Tables: .NET
Topics
• Creating a Table (p. 321)
• Updating a Table (p. 323)
• Deleting a Table (p. 323)
• Listing Tables (p. 324)
• Example: Create, Update, Delete, and List Tables Using the AWS SDK for .NET Low-Level
API (p. 324)
You can use the AWS SDK for .NET to create, update, and delete tables, list all the tables in your account,
or get information about a speciﬁc table.
The following are the common steps for table operations using the AWS SDK for .NET.
1. Create an instance of the AmazonDynamoDBClient class (the client).
2. Provide the required and optional parameters for the operation by creating the corresponding request
objects.
For example, create a CreateTableRequest object to create a table and UpdateTableRequest object to
update an existing table.
3. Execute the appropriate method provided by the client that you created in the preceding step.
Note
The examples in this section do not work with .NET core as it does not support synchronous
methods. For more information, see AWS Asynchronous APIs for .NET.
Creating a Table
To create a table, you must provide the table name, its primary key, and the provisioned throughput
values.
The following are the steps to create a table using the .NET low-level API.
1. Create an instance of the AmazonDynamoDBClient class.
2. Create an instance of the CreateTableRequest class to provide the request information.
You must provide the table name, primary key, and the provisioned throughput values.
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3. Execute the AmazonDynamoDBClient.CreateTable method by providing the request object as a
parameter.
The following C# code snippet demonstrates the preceding steps. The sample creates a table
(ProductCatalog) that uses Id as the primary key and set of provisioned throughput values. Depending
on your application requirements, you can update the provisioned throughput values by using the
UpdateTable API.
AmazonDynamoDBClient client = new AmazonDynamoDBClient();
string tableName = &quot;ProductCatalog&quot;;
var request = new CreateTableRequest
{
TableName = tableName,
AttributeDefinitions = new List&lt;AttributeDefinition&gt;()
{
new AttributeDefinition
{
AttributeName = &quot;Id&quot;,
AttributeType = &quot;N&quot;
}
},
KeySchema = new List&lt;KeySchemaElement&gt;()
{
new KeySchemaElement
{
AttributeName = &quot;Id&quot;,
KeyType = &quot;HASH&quot; //Partition key
}
},
ProvisionedThroughput = new ProvisionedThroughput
{
ReadCapacityUnits = 10,
WriteCapacityUnits = 5
}
};
var response = client.CreateTable(request);
You must wait until DynamoDB creates the table and sets the table status to ACTIVE. The CreateTable
response includes the TableDescription property that provides the necessary table information.
Example
var result = response.CreateTableResult;
var tableDescription = result.TableDescription;
Console.WriteLine(&quot;{1}: {0} \t ReadCapacityUnits: {2} \t WriteCapacityUnits: {3}&quot;,
tableDescription.TableStatus,
tableDescription.TableName,
tableDescription.ProvisionedThroughput.ReadCapacityUnits,
tableDescription.ProvisionedThroughput.WriteCapacityUnits);
string status = tableDescription.TableStatus;
Console.WriteLine(tableName + &quot; - &quot; + status);
You can also call the DescribeTable method of the client to get table information at anytime.
Example
var res = client.DescribeTable(new DescribeTableRequest{TableName = &quot;ProductCatalog&quot;});
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Updating a Table
You can update only the provisioned throughput values of an existing table. Depending on you
application requirements, you might need to update these values.
Note
You can increase throughput capacity as often as needed, and decrease it up to nine times per
table in a single UTC calendar day. For more information, see Limits in DynamoDB (p. 724).
The following are the steps to update a table using the .NET low-level API.
1. Create an instance of the AmazonDynamoDBClient class.
2. Create an instance of the UpdateTableRequest class to provide the request information.
You must provide the table name and the new provisioned throughput values.
3. Execute the AmazonDynamoDBClient.UpdateTable method by providing the request object as a
parameter.
The following C# code snippet demonstrates the preceding steps.
Example
AmazonDynamoDBClient client = new AmazonDynamoDBClient();
string tableName = &quot;ExampleTable&quot;;
var request = new UpdateTableRequest()
{
TableName = tableName,
ProvisionedThroughput = new ProvisionedThroughput()
{
// Provide new values.
ReadCapacityUnits = 20,
WriteCapacityUnits = 10
}
};
var response = client.UpdateTable(request);
Deleting a Table
The following are the steps to delete a table using the .NET low-level API.
1. Create an instance of the AmazonDynamoDBClient class.
2. Create an instance of the DeleteTableRequest class and provide the table name that you want to
delete.
3. Execute the AmazonDynamoDBClient.DeleteTable method by providing the request object as a
parameter.
The following C# code snippet demonstrates the preceding steps.
Example
AmazonDynamoDBClient client = new AmazonDynamoDBClient();
string tableName = &quot;ExampleTable&quot;;
var request = new DeleteTableRequest{ TableName = tableName };
var response = client.DeleteTable(request);
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Listing Tables
To list tables in your account using the AWS SDK for .NET low-level API, create an instance of the
AmazonDynamoDBClient and execute the ListTables method. The ListTables operation requires no
parameters. However, you can specify optional parameters. For example, you can set the Limit
parameter if you want to use paging to limit the number of table names per page. This requires you
to create a ListTablesRequest object and provide optional parameters as shown in the following C#
code snippet. Along with the page size, the request sets the ExclusiveStartTableName parameter.
Initially, ExclusiveStartTableName is null, however, after fetching the ﬁrst page of result, to retrieve the
next page of result, you must set this parameter value to the LastEvaluatedTableName property of the
current result.
Example
AmazonDynamoDBClient client = new AmazonDynamoDBClient();
// Initial value for the first page of table names.
string lastEvaluatedTableName = null;
do
{
// Create a request object to specify optional parameters.
var request = new ListTablesRequest
{
Limit = 10, // Page size.
ExclusiveStartTableName = lastEvaluatedTableName
};
var response = client.ListTables(request);
ListTablesResult result = response.ListTablesResult;
foreach (string name in result.TableNames)
Console.WriteLine(name);
lastEvaluatedTableName = result.LastEvaluatedTableName;
} while (lastEvaluatedTableName != null);
Example: Create, Update, Delete, and List Tables Using the AWS
SDK for .NET Low-Level API
The following C# example create,, updates, and deletes a table (ExampleTable). It also lists all the
tables in your account and gets the description of a speciﬁc table. The table update increases the
provisioned throughput values. For step-by-step instructions to test the following sample, see .NET Code
Samples (p. 287).
using
using
using
using
using
System;
System.Collections.Generic;
Amazon.DynamoDBv2;
Amazon.DynamoDBv2.Model;
Amazon.Runtime;
namespace com.amazonaws.codesamples
{
class LowLevelTableExample
{
private static AmazonDynamoDBClient client = new AmazonDynamoDBClient();
private static string tableName = &quot;ExampleTable&quot;;
static void Main(string[] args)
{
try
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{
CreateExampleTable();
ListMyTables();
GetTableInformation();
UpdateExampleTable();
DeleteExampleTable();
Console.WriteLine(&quot;To continue, press Enter&quot;);
Console.ReadLine();
}
}
catch (AmazonDynamoDBException e) { Console.WriteLine(e.Message); }
catch (AmazonServiceException e) { Console.WriteLine(e.Message); }
catch (Exception e) { Console.WriteLine(e.Message); }
private static void CreateExampleTable()
{
Console.WriteLine(&quot;\n*** Creating table ***&quot;);
var request = new CreateTableRequest
{
AttributeDefinitions = new List&lt;AttributeDefinition&gt;()
{
new AttributeDefinition
{
AttributeName = &quot;Id&quot;,
AttributeType = &quot;N&quot;
},
new AttributeDefinition
{
AttributeName = &quot;ReplyDateTime&quot;,
AttributeType = &quot;N&quot;
}
},
KeySchema = new List&lt;KeySchemaElement&gt;
{
new KeySchemaElement
{
AttributeName = &quot;Id&quot;,
KeyType = &quot;HASH&quot; //Partition key
},
new KeySchemaElement
{
AttributeName = &quot;ReplyDateTime&quot;,
KeyType = &quot;RANGE&quot; //Sort key
}
},
ProvisionedThroughput = new ProvisionedThroughput
{
ReadCapacityUnits = 5,
WriteCapacityUnits = 6
},
TableName = tableName
};
var response = client.CreateTable(request);
var tableDescription = response.TableDescription;
Console.WriteLine(&quot;{1}: {0} \t ReadsPerSec: {2} \t WritesPerSec: {3}&quot;,
tableDescription.TableStatus,
tableDescription.TableName,
tableDescription.ProvisionedThroughput.ReadCapacityUnits,
tableDescription.ProvisionedThroughput.WriteCapacityUnits);
string status = tableDescription.TableStatus;
Console.WriteLine(tableName + &quot; - &quot; + status);
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}
WaitUntilTableReady(tableName);
private static void ListMyTables()
{
Console.WriteLine(&quot;\n*** listing tables ***&quot;);
string lastTableNameEvaluated = null;
do
{
var request = new ListTablesRequest
{
Limit = 2,
ExclusiveStartTableName = lastTableNameEvaluated
};
var response = client.ListTables(request);
foreach (string name in response.TableNames)
Console.WriteLine(name);
}
lastTableNameEvaluated = response.LastEvaluatedTableName;
} while (lastTableNameEvaluated != null);
private static void GetTableInformation()
{
Console.WriteLine(&quot;\n*** Retrieving table information ***&quot;);
var request = new DescribeTableRequest
{
TableName = tableName
};
var response = client.DescribeTable(request);
}
TableDescription description = response.Table;
Console.WriteLine(&quot;Name: {0}&quot;, description.TableName);
Console.WriteLine(&quot;# of items: {0}&quot;, description.ItemCount);
Console.WriteLine(&quot;Provision Throughput (reads/sec): {0}&quot;,
description.ProvisionedThroughput.ReadCapacityUnits);
Console.WriteLine(&quot;Provision Throughput (writes/sec): {0}&quot;,
description.ProvisionedThroughput.WriteCapacityUnits);
private static void UpdateExampleTable()
{
Console.WriteLine(&quot;\n*** Updating table ***&quot;);
var request = new UpdateTableRequest()
{
TableName = tableName,
ProvisionedThroughput = new ProvisionedThroughput()
{
ReadCapacityUnits = 6,
WriteCapacityUnits = 7
}
};
var response = client.UpdateTable(request);
}
WaitUntilTableReady(tableName);
private static void DeleteExampleTable()
{
Console.WriteLine(&quot;\n*** Deleting table ***&quot;);
var request = new DeleteTableRequest
{
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};
TableName = tableName
var response = client.DeleteTable(request);
}
Console.WriteLine(&quot;Table is being deleted...&quot;);
private static void WaitUntilTableReady(string tableName)
{
string status = null;
// Let us wait until table is created. Call DescribeTable.
do
{
System.Threading.Thread.Sleep(5000); // Wait 5 seconds.
try
{
var res = client.DescribeTable(new DescribeTableRequest
{
TableName = tableName
});
Console.WriteLine(&quot;Table name: {0}, status: {1}&quot;,
res.Table.TableName,
res.Table.TableStatus);
status = res.Table.TableStatus;
}
}
}
}
catch (ResourceNotFoundException)
{
// DescribeTable is eventually consistent. So you might
// get resource not found. So we handle the potential exception.
}
} while (status != &quot;ACTIVE&quot;);
Working with Items in DynamoDB
Topics
• Reading an Item (p. 328)
• Writing an Item (p. 329)
• Return Values (p. 331)
• Batch Operations (p. 331)
• Atomic Counters (p. 333)
• Conditional Writes (p. 334)
• Using Expressions in DynamoDB (p. 338)
• Time To Live (p. 362)
• Working with Items: Java (p. 368)
• Working with Items: .NET (p. 387)
In DynamoDB, an item is a collection of attributes. Each attribute has a name and a value. An attribute
value can be a scalar, a set, or a document type. For more information, see Amazon DynamoDB: How It
Works (p. 2).
DynamoDB provides four operations for basic create/read/update/delete (CRUD) functionality:
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Reading an Item
• PutItem – create an item.
• GetItem – read an item.
• UpdateItem – update an item.
• DeleteItem – delete an item.
Each of these operations require you to specify the primary key of the item you want to work with. For
example, to read an item using GetItem, you must specify the partition key and sort key (if applicable)
for that item.
In addition to the four basic CRUD operations, DynamoDB also provides the following:
• BatchGetItem – read up to 100 items from one or more tables.
• BatchWriteItem – create or delete up to 25 items in one or more tables.
These batch operations combine multiple CRUD operations into a single request. In addition, the batch
operations read and write items in parallel to minimize response latencies.
This section describes how to use these operations and includes related topics, such as conditional
updates and atomic counters. This section also includes example code that uses the AWS SDKs. For best
practices, see Best Practices for Items (p. 669).
Reading an Item
To read an item from a DynamoDB table, use the GetItem operation. You must provide the name of the
table, along with the primary key of the item you want.
Example
The following AWS CLI example shows how to read an item from the ProductCatalog table.
aws dynamodb get-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;1&quot;}}'
Note
With GetItem, you must specify the entire primary key, not just part of it. For example, if a
table has a composite primary key (partition key and sort key), you must supply a value for the
partition key and a value for the sort key.
GetItem request performs an eventually consistent read, by default. You can use the ConsistentRead
parameter to request a strongly consistent read instead. (This will consume additional read capacity
units, but it will return the most up-to-date version of the item.)
GetItem returns all of the item's attributes. You can use a projection expression to return only some of the
attributes. (For more information, see Projection Expressions (p. 341).)
To return the number of read capacity units consumed by GetItem, set the ReturnConsumedCapacity
parameter to TOTAL.
Example
The following AWS CLI example shows some of the optional GetItem parameters.
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aws dynamodb get-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;1&quot;}}' \
--consistent-read \
--projection-expression &quot;Description, Price, RelatedItems&quot; \
--return-consumed-capacity TOTAL
Writing an Item
To create, update, or delete an item in a DynamoDB table, use one of the following operations:
• PutItem
• UpdateItem
• DeleteItem
For each of these operations, you need to specify the entire primary key, not just part of it. For example,
if a table has a composite primary key (partition key and sort key), you must supply a value for the
partition key and a value for the sort key.
To return the number of write capacity units consumed by any of these operations, set the
ReturnConsumedCapacity parameter to one of the following:
• TOTAL—returns the total number of write capacity units consumed.
• INDEXES—returns the total number of write capacity units consumed, with subtotals for the table and
any secondary indexes that were aﬀected by the operation.
• NONE—no write capacity details are returned. (This is the default.)
PutItem
PutItem creates a new item. If an item with the same key already exists in the table, it is replaced with
the new item.
Example
Write a new item to the Thread table. The primary key for Thread consists of ForumName (partition key)
and Subject (sort key).
aws dynamodb put-item \
--table-name Thread \
--item file://item.json
The arguments for --item are stored in the ﬁle item.json:
{
}
&quot;ForumName&quot;: {&quot;S&quot;: &quot;Amazon DynamoDB&quot;},
&quot;Subject&quot;: {&quot;S&quot;: &quot;New discussion thread&quot;},
&quot;Message&quot;: {&quot;S&quot;: &quot;First post in this thread&quot;},
&quot;LastPostedBy&quot;: {&quot;S&quot;: &quot;[email protected]&quot;},
&quot;LastPostDateTime&quot;: {&quot;S&quot;: &quot;201603190422&quot;}
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UpdateItem
If an item with the speciﬁed key does not exist, UpdateItem creates a new item. Otherwise, it modiﬁes an
existing item's attributes.
You use an update expression to specify the attributes you want to modify and their new values. (For
more information, see Update Expressions (p. 354).) Within the update expression, you use expression
attribute values as placeholders for the actual values. (For more information, see Expression Attribute
Values (p. 345).)
Example
Modify various attributes in the Thread item. The optional ReturnValues parameter shows the item as it
appears after the update. (For more information, see Return Values (p. 331).)
aws dynamodb update-item \
--table-name Thread \
--key file://key.json \
--update-expression &quot;SET Answered = :zero, Replies = :zero, LastPostedBy
= :lastpostedby&quot; \
--expression-attribute-values file://expression-attribute-values.json \
--return-values ALL_NEW
The arguments for --key are stored in the ﬁle key.json:
{
}
&quot;ForumName&quot;: {&quot;S&quot;: &quot;Amazon DynamoDB&quot;},
&quot;Subject&quot;: {&quot;S&quot;: &quot;New discussion thread&quot;}
The arguments for --expression-attribute-values are stored in the ﬁle expression-attributevalues.json:
{
}
&quot;:zero&quot;: {&quot;N&quot;:&quot;0&quot;},
&quot;:lastpostedby&quot;: {&quot;S&quot;:&quot;[email protected]&quot;}
DeleteItem
DeleteItem deletes the item with the speciﬁed key.
Example
This AWS CLI example shows how to delete the Thread item.
aws dynamodb delete-item \
--table-name Thread \
--key file://key.json
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Return Values
In some cases, you might want DynamoDB to return certain attribute values as they appeared before
or after you modiﬁed them. The PutItem, UpdateItem, and DeleteItem operations have a ReturnValues
parameter that you can use to return the attribute values before or after they are modiﬁed.
The default value for ReturnValues is NONE, meaning that DynamoDB will not return any information
about attributes that were modiﬁed.
The following are the other valid settings for ReturnValues, organized by DynamoDB API operation:
PutItem
• ReturnValues: ALL_OLD
• If you overwrite an existing item, ALL_OLD returns the entire item as it appeared before the
overwrite.
• If you write a nonexistent item, ALL_OLD has no eﬀect.
UpdateItem
The most common usage for UpdateItem is to update an existing item. However, UpdateItem actually
performs an upsert, meaning that it will automatically create the item if it does not already exist.
• ReturnValues: ALL_OLD
• If you update an existing item, ALL_OLD returns the entire item as it appeared before the update.
• If you update a nonexistent item (upsert), ALL_OLD has no eﬀect.
• ReturnValues: ALL_NEW
• If you update an existing item, ALL_NEW returns the entire item as it appeared after the update.
• If you update a nonexistent item (upsert), ALL_NEW returns the entire item.
• ReturnValues: UPDATED_OLD
• If you update an existing item, UPDATED_OLD returns only the updated attributes, as they appeared
before the update.
• If you update a nonexistent item (upsert), UPDATED_OLD has no eﬀect.
• ReturnValues: UPDATED_NEW
• If you update an existing item, UPDATED_NEW returns only the aﬀected attributes, as they appeared
after the update.
• If you update a nonexistent item (upsert), UPDATED_NEW returns only the updated attributes, as they
appear after the update.
DeleteItem
• ReturnValues: ALL_OLD
• If you delete an existing item, ALL_OLD returns the entire item as it appeared before you deleted it.
• If you delete a nonexistent item, ALL_OLD does not return any data.
Batch Operations
For applications that need to read or write multiple items, DynamoDB provides the BatchGetItem and
BatchWriteItem operations. Using these operations can reduce the number of network round trips from
your application to DynamoDB. In addition, DynamoDB performs the individual read or write operations
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in parallel. Your applications beneﬁt from this parallelism without having to manage concurrency or
threading.
The batch operations are essentially wrappers around multiple read or write requests. For example, if a
BatchGetItem request contains ﬁve items, DynamoDB performs ﬁve GetItem operations on your behalf.
Similarly, if a BatchWriteItem request contains two put requests and four delete requests, DynamoDB
performs two PutItem and four DeleteItem requests.
In general, a batch operation does not fail unless all of the requests in the batch fail. For example,
suppose you perform a BatchGetItem operation, but one of the individual GetItem requests in the batch
fails. In this case, BatchGetItem returns the keys and data from the GetItem request that failed. The other
GetItem requests in the batch are not aﬀected.
BatchGetItem
A single BatchGetItem operation can contain up to 100 individual GetItem requests and can retrieve up
to 16 MB of data. In addition, a BatchGetItem operation can retrieve items from multiple tables.
Example
Retrieve two items from the Thread table, using a projection expression to return only some of the
attributes.
aws dynamodb batch-get-item \
--request-items file://request-items.json
The arguments for --request-items are stored in the ﬁle request-items.json:
{
}
&quot;Thread&quot;: {
&quot;Keys&quot;: [
{
&quot;ForumName&quot;:{&quot;S&quot;: &quot;Amazon DynamoDB&quot;},
&quot;Subject&quot;:{&quot;S&quot;: &quot;DynamoDB Thread 1&quot;}
},
{
&quot;ForumName&quot;:{&quot;S&quot;: &quot;Amazon S3&quot;},
&quot;Subject&quot;:{&quot;S&quot;: &quot;S3 Thread 1&quot;}
}
],
&quot;ProjectionExpression&quot;:&quot;ForumName, Subject, LastPostedDateTime, Replies&quot;
}
BatchWriteItem
The BatchWriteItem operation can contain up to 25 individual PutItem and DeleteItem requests
and can write up to 16 MB of data. (The maximum size of an individual item is 400 KB.) In addition, a
BatchWriteItem operation can put or delete items in multiple tables.
Note
BatchWriteItem does not support UpdateItem requests.
Example
Write two items to the ProductCatalog table.
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aws dynamodb batch-write-item \
--request-items file://request-items.json
The arguments for --request-items are stored in the ﬁle request-items.json:
{
}
&quot;ProductCatalog&quot;: [
{
&quot;PutRequest&quot;: {
&quot;Item&quot;: {
&quot;Id&quot;: { &quot;N&quot;: &quot;601&quot; },
&quot;Description&quot;: { &quot;S&quot;: &quot;Snowboard&quot; },
&quot;QuantityOnHand&quot;: { &quot;N&quot;: &quot;5&quot; },
&quot;Price&quot;: { &quot;N&quot;: &quot;100&quot; }
}
}
},
{
&quot;PutRequest&quot;: {
&quot;Item&quot;: {
&quot;Id&quot;: { &quot;N&quot;: &quot;602&quot; },
&quot;Description&quot;: { &quot;S&quot;: &quot;Snow shovel&quot; }
}
}
}
]
Atomic Counters
You can use the UpdateItem operation to implement an atomic counter—a numeric attribute that
is incremented, unconditionally, without interfering with other write requests. (All write requests
are applied in the order in which they were received.) With an atomic counter, the updates are not
idempotent. In other words, the numeric value will increment each time you call UpdateItem.
You might use an atomic counter to keep track of the number of visitors to a website. In this case, your
application would increment a numeric value, regardless of its current value. If an UpdateItem operation
should fail, the application could simply retry the operation. This would risk updating the counter twice,
but you could probably tolerate a slight overcounting or undercounting of website visitors.
An atomic counter would not be appropriate where over- or undercounting cannot be tolerated (For
example, in a banking application). In these case, it is safer to use a conditional update instead of an
atomic counter.
For more information, see Incrementing and Decrementing Numeric Attributes (p. 358).
Example
The following AWS CLI example increments the Price of a product by 5. (Because UpdateItem is not
idempotent, the Price will increase every time you run this example.)
aws dynamodb update-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;: { &quot;N&quot;: &quot;601&quot; }}' \
--update-expression &quot;SET Price = Price + :incr&quot; \
--expression-attribute-values '{&quot;:incr&quot;:{&quot;N&quot;:&quot;5&quot;}}' \
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--return-values UPDATED_NEW
Conditional Writes
By default, the DynamoDB write operations (PutItem, UpdateItem, DeleteItem) are unconditional: each of
these operations will overwrite an existing item that has the speciﬁed primary key.
DynamoDB optionally supports conditional writes for these operations. A conditional write will succeed
only if the item attributes meet one or more expected conditions. Otherwise, it returns an error.
Conditional writes are helpful in many situations. For example, you might want a PutItem operation
to succeed only if there is not already an item with the same primary key. Or you could prevent an
UpdateItem operation from modifying an item if one of its attributes has a certain value.
Conditional writes are helpful in cases where multiple users attempt to modify the same item. Consider
the following diagram, in which two users (Alice and Bob) are working with the same item from a
DynamoDB table:
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Suppose that Alice uses the AWS CLI to update the Price attribute to 8:
aws dynamodb update-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;1&quot;}}' \
--update-expression &quot;SET Price = :newval&quot; \
--expression-attribute-values file://expression-attribute-values.json
The arguments for --expression-attribute-values are stored in the ﬁle expression-attributevalues.json:
{
}
&quot;:newval&quot;:{&quot;N&quot;:&quot;8&quot;}
Now suppose that Bob issues a similar UpdateItem request later, but changes the Price to 12. For Bob,
the --expression-attribute-values parameter looks like this:
{
}
&quot;:newval&quot;:{&quot;N&quot;:&quot;12&quot;}
Bob's request succeeds, but Alice's earlier update is lost.
To request a conditional PutItem, DeleteItem, or UpdateItem, you specify a condition expression. A
condition expression is a string containing attribute names, conditional operators, and built-in functions.
The entire expression must evaluate to true. Otherwise, the operation will fail.
Now consider the following diagram, showing how conditional writes would prevent Alice's update from
being overwritten:
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Alice ﬁrst attempts to update Price to 8, but only if the current Price is 10:
aws dynamodb update-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;1&quot;}}' \
--update-expression &quot;SET Price = :newval&quot; \
--condition-expression &quot;Price = :currval&quot; \
--expression-attribute-values file://expression-attribute-values.json
The arguments for --expression-attribute-values are stored in the ﬁle expression-attributevalues.json:
{
&quot;:newval&quot;:{&quot;N&quot;:&quot;8&quot;},
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}
&quot;:currval&quot;:{&quot;N&quot;:&quot;10&quot;}
Alice's update succeeds because the condition evaluates to true.
Next, Bob attempts to update the Price to 12, but only if the current Price is 10. For Bob, the -expression-attribute-values parameter looks like this:
{
}
&quot;:newval&quot;:{&quot;N&quot;:&quot;12&quot;},
&quot;:currval&quot;:{&quot;N&quot;:&quot;10&quot;}
Because Alice has previously changed the Price to 8, the condition expression evaluates to false and
Bob's update fails.
For more information, see Condition Expressions (p. 346).
Conditional Write Idempotence
Conditional writes are idempotent. This means that you can send the same conditional write request to
DynamoDB multiple times, but the request will have no further eﬀect on the item after the ﬁrst time
DynamoDB performs the update.
For example, suppose you issue an UpdateItem request to increase the Price of an item by 3, but only
if the Price is currently 20. After you send the request, but before you get the results back, a network
error occurs and you don't know whether the request was successful. Because conditional writes are
idempotent, you can retry the same UpdateItem request, and DynamoDB will update the item only if the
Price is currently 20.
Capacity Units Consumed by Conditional Writes
If a ConditionExpression evaluates to false during a conditional write, DynamoDB will still consume
write capacity from the table:
• If the item does not currently exist in the table, DynamoDB will consume one write capacity unit.
• If the item does exist, then the number of write capacity units consumed depends on the size of the
item. For example, a failed conditional write of a 1 KB item would consume one write capacity unit. If
the item were twice that size, the failed conditional write would consume two write capacity units.
Note
Write operations consume write capacity units only. They never consume read capacity units.
A failed conditional write will return a ConditionalCheckFailedException. When this occurs, you will not
receive any information in the response about the write capacity that was consumed. However, you
can view the ConsumedWriteCapacityUnits metric for the table in Amazon CloudWatch. (For more
information, see DynamoDB Metrics (p. 637) in Monitoring DynamoDB (p. 635).)
To return the number of write capacity units consumed during a conditional write, you use the
ReturnConsumedCapacity parameter:
• TOTAL—returns the total number of write capacity units consumed.
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• INDEXES—returns the total number of write capacity units consumed, with subtotals for the table and
any secondary indexes that were aﬀected by the operation.
• NONE—no write capacity details are returned. (This is the default.)
Note
Unlike a global secondary index, a local secondary index shares its provisioned throughput
capacity with its table. Read and write activity on a local secondary index consumes provisioned
throughput capacity from the table.
Using Expressions in DynamoDB
In Amazon DynamoDB, you use expressions to denote the attributes that you want to read from an item.
You also use expressions when writing an item, to indicate any conditions that must be met (also known
as a conditional update), and to indicate how the attributes are to be updated. This section describes the
basic expression grammar and the available kinds of expressions.
Note
For backward compatibility, DynamoDB also supports conditional parameters that do not use
expressions. For more information, see Legacy Conditional Parameters (p. 782).
New applications should use expressions rather than the legacy parameters.
Topics
• Specifying Item Attributes (p. 338)
• Projection Expressions (p. 341)
• Expression Attribute Names (p. 342)
• Expression Attribute Values (p. 345)
• Condition Expressions (p. 346)
• Update Expressions (p. 354)
Specifying Item Attributes
This section describes how to refer to item attributes in an expression. You can work with any attribute,
even if it is deeply nested within multiple lists and maps.
Topics
• Top-Level Attributes (p. 340)
• Nested Attributes (p. 340)
• Document Paths (p. 341)
A Sample Item: ProductCatalog
In this section, we will consider an item in the ProductCatalog table. (This table is described in Example
Tables and Data (p. 732).) Here is a representation of the item:
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Note the following:
• The partition key value (Id) is 123. There is no sort key.
• Most of the attributes have scalar data types, such as String, Number, Boolean, and Null.
• One attribute (Color) is a String Set.
• The following attributes are document data types:
• A list of RelatedItems. Each element is an Id for a related product.
• A map of Pictures. Each element is a short description of a picture, along with a URL for the
corresponding image ﬁle.
• A map of ProductReviews. Each element represents a rating and a list of reviews corresponding to
that rating. Initially, this map will be populated with ﬁve-star and one-star reviews.
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Top-Level Attributes
An attribute is said to be top-level if it is not embedded within another attribute. For the ProductCatalog
item, the top-level attributes are:
• Id
• Title
• Description
• BicycleType
• Brand
• Price
• Color
• ProductCategory
• InStock
• QuantityOnHand
• RelatedItems
• Pictures
• ProductReviews
• Comment
• Safety.Warning
All of these top-level attributes are scalars, except for Color (list), RelatedItems (list), Pictures (map)
and ProductReviews (map).
Nested Attributes
An attribute is said to be nested if it is embedded within another attribute. To access a nested attribute,
you use dereference operators:
• [n]—for list elements
• . (dot)—for map elements
Accessing List Elements
The dereference operator for a list element is [n], where n is the element number. List elements are zerobased, so [0] represents the ﬁrst element in the list, [1] represents the second, and so on. Here are some
examples:
• MyList[0]
• AnotherList[12]
• ThisList[5][11]
The element ThisList[5] is itself a nested list. Therefore, ThisList[5][11] refers to the twelfth element
in that list.
The number within the square brackets must be a non-negative integer. Therefore, the following
expressions are invalid:
• MyList[-1]
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• MyList[0.4]
Accessing Map Elements
The dereference operator for a map element is . (a dot). Use a dot as a separator between elements in a
map:
• MyMap.nestedField
• MyMap.nestedField.deeplyNestedField
Document Paths
In an expression, you use a document path to tell DynamoDB where to ﬁnd an attribute. For a top-level
attribute, the document path is simply the attribute name. For a nested attribute, you construct the
document path using dereference operators.
The following are some examples of document paths. (Refer to the item shown in Specifying Item
Attributes (p. 338).)
• A top-level scalar attribute:
ProductDescription
• A top-level list attribute. (This will return the entire list, not just some of the elements.)
RelatedItems
• The third element from the RelatedItems list. (Remember that list elements are zero-based.)
RelatedItems[2]
• The front-view picture of the product.
Pictures.FrontView
• All of the ﬁve-star reviews.
ProductReviews.FiveStar
• The ﬁrst of the ﬁve-star reviews.
ProductReviews.FiveStar[0]
Note
The maximum depth for a document path is 32. Therefore, the number of dereferences
operators in a path cannot exceed this limit.
You can use any attribute name in a document path, provided that the ﬁrst character is a-z or A-Z and
the second character (if present) is a-z, A-Z, or 0-9. If an attribute name does not meet this requirement,
you will need to deﬁne an expression attribute name as a placeholder. For more information, see
Expression Attribute Names (p. 342).
Projection Expressions
To read data from a table, you use operations such as GetItem, Query, or Scan. DynamoDB returns all
of the item attributes by default. To get just some, rather than all of the attributes, use a projection
expression.
A projection expression is a string that identiﬁes the attributes you want. To retrieve a single attribute,
specify its name. For multiple attributes, the names must be comma-separated.
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The following are some examples of projection expressions, based on the ProductCatalog item from
Specifying Item Attributes (p. 338):
• A single top-level attribute.
Title
• Three top-level attributes. DynamoDB will retrieve the entire Color set.
Title, Price, Color
• Four top-level attributes. DynamoDB will return the entire contents of RelatedItems and
ProductReviews.
Title, Description, RelatedItems, ProductReviews
You can use any attribute name in a projection expression, provided that the ﬁrst character is a-z
or A-Z and the second character (if present) is a-z, A-Z, or 0-9. If an attribute name does not meet
this requirement, you will need to deﬁne an expression attribute name as a placeholder. For more
information, see Expression Attribute Names (p. 342).
The following AWS CLI example shows how to use a projection expression with a GetItem operation.
This projection expression retrieves a top-level scalar attribute (Description), the ﬁrst element in a list
(RelatedItems[0]), and a list nested within a map (ProductReviews.FiveStar).
aws dynamodb get-item \
--table-name ProductCatalog \
--key file://key.json \
--projection-expression &quot;Description, RelatedItems[0], ProductReviews.FiveStar&quot;
The arguments for --key are stored in the ﬁle key.json:
{
}
&quot;Id&quot;: { &quot;N&quot;: &quot;123&quot; }
For programming language-speciﬁc code samples, see Getting Started with DynamoDB (p. 52).
Expression Attribute Names
An expression attribute name is a placeholder that you use in an expression, as an alternative to an actual
attribute name. An expression attribute name must begin with a #, and be followed by one or more
alphanumeric characters.
This section describes several situations in which you will need to use expression attribute names.
Note
The examples in this section use the AWS CLI. For programming language-speciﬁc code samples,
see Getting Started with DynamoDB (p. 52).
Topics
• Reserved Words (p. 343)
• Attribute Names Containing Dots (p. 343)
• Nested Attributes (p. 344)
• Repeating Attribute Names (p. 344)
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Reserved Words
On some occasions, you might need to write an expression containing an attribute name that conﬂicts
with a DynamoDB reserved word. (For a complete list of reserved words, see Reserved Words in
DynamoDB (p. 773).)
For example, the following AWS CLI example would fail because COMMENT is a reserved word:
aws dynamodb get-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;123&quot;}}' \
--projection-expression &quot;Comment&quot;
To work around this, you can replace Comment with an expression attribute name such as #c. The # (pound
sign) is required and indicates that this is a placeholder for an attribute name. The AWS CLI example
would now look like this:
aws dynamodb get-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;123&quot;}}' \
--projection-expression &quot;#c&quot; \
--expression-attribute-names '{&quot;#c&quot;:&quot;Comment&quot;}'
Note
If an attribute name begins with a number or contains a space, a special character, or a reserved
word, then you must use an expression attribute name to replace that attribute's name in the
expression.
Attribute Names Containing Dots
In an expression, a dot (&quot;.&quot;) is interpreted as a separator character in a document path. However,
DynamoDB also allows you to use a dot character as part of an attribute name. This can be ambiguous
in some cases. To illustrate, suppose that you wanted to retrieve the Safety.Warning attribute from a
ProductCatalog item (see Specifying Item Attributes (p. 338)):
Suppose that you wanted to access Safety.Warning using a projection expression:
aws dynamodb get-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;123&quot;}}' \
--projection-expression &quot;Safety.Warning&quot;
DynamoDB would return an empty result, rather than the expected string (&quot;Always wear a helmet&quot;).
This is because DynamoDB interprets a dot in an expression as a document path separator. In this case,
you would need to deﬁne an expression attribute name (such as #sw) as a substitute for Safety.Warning.
You could then use the following projection expression:
aws dynamodb get-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;123&quot;}}' \
--projection-expression &quot;#sw&quot; \
--expression-attribute-names '{&quot;#sw&quot;:&quot;Safety.Warning&quot;}'
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DynamoDB would then return the correct result.
Nested Attributes
Suppose that you wanted to access the nested attribute ProductReviews.OneStar, using the following
projection expression:
aws dynamodb get-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;123&quot;}}' \
--projection-expression &quot;ProductReviews.OneStar&quot;
The result would contain all of the one-star product reviews, which is expected.
But what if you decided to use an expression attribute name instead? For example, what would happen if
you were to deﬁne #pr1star as a substitute for ProductReviews.OneStar?
aws dynamodb get-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;123&quot;}}' \
--projection-expression &quot;#pr1star&quot; \
--expression-attribute-names '{&quot;#pr1star&quot;:&quot;ProductReviews.OneStar&quot;}'
DynamoDB would return an empty result, instead of the expected map of one-star reviews. This is
because DynamoDB interprets a dot in an expression attribute value as a character within an attribute's
name. When DynamoDB evaluates the expression attribute name #pr1star, it determines that
ProductReviews.OneStar refers to a scalar attribute—which is not what was intended.
The correct approach would be to deﬁne an expression attribute name for each element in the document
path:
• #pr — ProductReviews
• #1star — OneStar
You could then use #pr.#1s for the projection expression:
aws dynamodb get-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;123&quot;}}' \
--projection-expression &quot;#pr.#1star&quot; \
--expression-attribute-names '{&quot;#pr&quot;:&quot;ProductReviews&quot;, &quot;#1star&quot;:&quot;OneStar&quot;}'
DynamoDB would then return the correct result.
Repeating Attribute Names
Expression attribute names are helpful when you need to refer to the same attribute name repeatedly.
For example, consider the following expression for retrieving some of the reviews from a ProductCatalog
item:
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aws dynamodb get-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;123&quot;}}' \
--projection-expression &quot;ProductReviews.FiveStar, ProductReviews.ThreeStar,
ProductReviews.OneStar&quot;
To make this more concise, you can replace ProductReviews with an expression attribute name such as
#pr. The revised expression would now look like this:
• #pr.FiveStar, #pr.ThreeStar, #pr.OneStar
aws dynamodb get-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;123&quot;}}' \
--projection-expression &quot;#pr.FiveStar, #pr.ThreeStar, #pr.OneStar&quot; \
--expression-attribute-names '{&quot;#pr&quot;:&quot;ProductReviews&quot;}'
If you deﬁne an expression attribute name, you must use it consistently throughout the entire
expression. Also, you cannot omit the # symbol.
Expression Attribute Values
If you need to compare an attribute with a value, deﬁne an expression attribute value as a placeholder.
Expression attribute values are substitutes for the actual values that you want to compare — values that
you might not know until runtime. An expression attribute value must begin with a :, and be followed by
one or more alphanumeric characters.
For example, suppose you wanted to return all of the ProductCatalog items that are available in Black
and cost 500 or less. You could use a Scan operation with a ﬁlter expression, as in this AWS CLI example:
aws dynamodb scan \
--table-name ProductCatalog \
--filter-expression &quot;contains(Color, :c) and Price &lt;= :p&quot; \
--expression-attribute-values file://values.json
The arguments for --expression-attribute-values are stored in the ﬁle values.json:
{
}
&quot;:c&quot;: { &quot;S&quot;: &quot;Black&quot; },
&quot;:p&quot;: { &quot;N&quot;: &quot;500&quot; }
Note
A Scan operation reads every item in a table; therefore, you should avoid using Scan with large
tables.
The ﬁlter expression is applied to the Scan results, and items that do not match the ﬁlter
expression are discarded.
If you deﬁne an expression attribute value, you must use it consistently throughout the entire expression.
Also, you cannot omit the : symbol.
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Expression attribute values are used with condition expressions, update expressions, and ﬁlter
expressions.
Note
For programming language-speciﬁc code samples, see Getting Started with DynamoDB (p. 52).
Condition Expressions
To manipulate data in a DynamoDB table, you use the PutItem, UpdateItem and DeleteItem operations.
(You can also use BatchWriteItem to perform multiple PutItem or DeleteItem operations in a single call.)
For these data manipulation operations, you can specify a condition expression to determine which items
should be modiﬁed. If the condition expression evaluates to true, the operation succeeds; otherwise, the
operation fails.
The following are some AWS CLI examples of using condition expressions. These examples are based on
the ProductCatalog table, which was introduced in Specifying Item Attributes (p. 338). The partition key
for this table is Id; there is no sort key. The following PutItem operation creates a sample ProductCatalog
item that we will refer to in the examples:
aws dynamodb put-item \
--table-name ProductCatalog \
--item file://item.json
The arguments for --item are stored in the ﬁle item.json. (For simplicity, only a few item attributes are
used.)
{
}
&quot;Id&quot;: {&quot;N&quot;: &quot;456&quot; },
&quot;ProductCategory&quot;: {&quot;S&quot;: &quot;Sporting Goods&quot; },
&quot;Price&quot;: {&quot;N&quot;: &quot;650&quot; }
Topics
• Preventing Overwrites of an Existing Item (p. 346)
• Checking for Attributes in an Item (p. 347)
• Conditional Deletes (p. 347)
• Conditional Updates (p. 348)
• Comparison Operator and Function Reference (p. 349)
Preventing Overwrites of an Existing Item
The PutItem operation will overwrite an item with the same key (if it exists). If you want to avoid this, use
a condition expression. This will allows the write to proceed only if the item in question does not already
have the same key:
aws dynamodb put-item \
--table-name ProductCatalog \
--item file://item.json \
--condition-expression &quot;attribute_not_exists(Id)&quot;
If the condition expression evaluates to false, DynamoDB returns the following error message: The
conditional request failed
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Note
For more information about attribute_not_exists and other functions, see Comparison
Operator and Function Reference (p. 349).
Checking for Attributes in an Item
You can check for the existence (or nonexistence) of any attribute. If the condition expression evaluates
to true, the operation will succeed; otherwise, it will fail.
The following example uses attribute_not_exists to delete a product only if it does not have a Price
attribute:
aws dynamodb delete-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;: {&quot;N&quot;: &quot;456&quot;}}' \
--condition-expression &quot;attribute_not_exists(Price)&quot;
DynamoDB also provides an attribute_exists function. The following example will delete a product
only if it has received poor reviews:
aws dynamodb delete-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;: {&quot;N&quot;: &quot;456&quot;}}' \
--condition-expression &quot;attribute_exists(ProductReviews.OneStar)&quot;
Note
For more information about attribute_not_exists, attribute_exists, and other functions, see
Comparison Operator and Function Reference (p. 349).
Conditional Deletes
To perform a conditional delete, you use a DeleteItem operation with a condition expression. The
condition expression must evaluate to true in order for the operation to succeed; otherwise, the
operation fails.
Let us revisit the item from Condition Expressions (p. 346):
{
}
&quot;Id&quot;: {
&quot;N&quot;: &quot;456&quot;
},
&quot;Price&quot;: {
&quot;N&quot;: &quot;650&quot;
},
&quot;ProductCategory&quot;: {
&quot;S&quot;: &quot;Sporting Goods&quot;
}
Now suppose that you wanted to delete the item, but only under the following conditions:
• The ProductCategory is either &quot;Sporting Goods&quot; or &quot;Gardening Supplies&quot;
• The Price is between 500 and 600.
The following example will attempt to delete the item:
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aws dynamodb delete-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;456&quot;}}' \
--condition-expression &quot;(ProductCategory IN (:cat1, :cat2)) and (Price between :lo
and :hi)&quot; \
--expression-attribute-values file://values.json
The arguments for --expression-attribute-values are stored in the ﬁle values.json:
{
}
&quot;:cat1&quot;: {&quot;S&quot;: &quot;Sporting Goods&quot;},
&quot;:cat2&quot;: {&quot;S&quot;: &quot;Gardening Supplies&quot;},
&quot;:lo&quot;: {&quot;N&quot;: &quot;500&quot;},
&quot;:hi&quot;: {&quot;N&quot;: &quot;600&quot;}
Note
In the condition expression, the : (colon character) indicates an expression attribute value—
placeholder for an actual value. For more information, see Expression Attribute Values (p. 345).
For more information about IN, AND, and other keywords, , see Comparison Operator and
Function Reference (p. 349).
In this example, the ProductCategory comparison evaluates to true, but the Price comparison evaluates
to false. This causes the condition expression to evaluate to false, and the DeleteItem operation to fail.
Conditional Updates
To perform a conditional update, you use an UpdateItem operation with a condition expression. The
condition expression must evaluate to true in order for the operation to succeed; otherwise, the
operation fails.
Note
UpdateItem also supports update expressions, where you specify the modiﬁcations you
specify the changes you want to make to an item. For more information, see Update
Expressions (p. 354).
Suppose that you started with the item shown in Condition Expressions (p. 346):
{
}
&quot;Id&quot;: { &quot;N&quot;: &quot;456&quot;},
&quot;Price&quot;: {&quot;N&quot;: &quot;650&quot;},
&quot;ProductCategory&quot;: {&quot;S&quot;: &quot;Sporting Goods&quot;}
The following example performs an UpdateItem operation. It attempts to reduce the Price of a product
by 75—but the condition expression prevents the update if the current Price is below 500:
aws dynamodb update-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;: {&quot;N&quot;: &quot;456&quot;}}' \
--update-expression &quot;SET Price = Price - :discount&quot; \
--condition-expression &quot;Price &gt; :limit&quot; \
--expression-attribute-values file://values.json
The arguments for --item are stored in the ﬁle values.json:
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{
}
&quot;:discount&quot;: { &quot;N&quot;: &quot;75&quot;},
&quot;:limit&quot;: {&quot;N&quot;: &quot;500&quot;}
If the starting Price is 650, then the UpdateItem operation reduces the Price to 575. If you run the
UpdateItem operation again, the Price is reduced to 500. If you run it a third time, the condition
expression evaluates to false, and the update fails.
Note
In the condition expression, the : (colon character) indicates an expression attribute value—
placeholder for an actual value. For more information, see Expression Attribute Values (p. 345).
For more information about &quot;&gt;&quot; and other operators, see Comparison Operator and Function
Reference (p. 349).
Comparison Operator and Function Reference
This section covers the built-in functions and keywords for writing condition expressions in DynamoDB.
Topics
• Syntax for Condition Expressions (p. 349)
• Making Comparisons (p. 350)
• Functions (p. 350)
• Logical Evaluations (p. 353)
• Parentheses (p. 354)
• Precedence in Conditions (p. 354)
Syntax for Condition Expressions
In the following syntax summary, an operand can be the following:
• A top-level attribute name, such as Id, Title, Description or ProductCategory
• A document path that references a nested attribute
condition-expression ::=
operand comparator operand
| operand BETWEEN operand AND operand
| operand IN ( operand (',' operand (, ...) ))
| function
| condition AND condition
| condition OR condition
| NOT condition
| ( condition )
comparator ::=
=
| &lt;&gt;
| &lt;
| &lt;=
| &gt;
| &gt;=
function ::=
attribute_exists (path)
| attribute_not_exists (path)
| attribute_type (path, type)
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| begins_with (path, substr)
| contains (path, operand)
| size (path)
Making Comparisons
Use these comparators to compare an operand against a range of values, or an enumerated list of values:
• a = b — true if a is equal to b
• a &lt;&gt; b — true if a is not equal to b
• a &lt; b — true if a is less than b
• a &lt;= b — true if a is less than or equal to b
• a &gt; b — true if a is greater than b
• a &gt;= b — true if a is greater than or equal to b
Use the BETWEEN and IN keywords to compare an operand against a range of values, or an enumerated
list of values:
• a BETWEEN b AND c - true if a is greater than or equal to b, and less than or equal to c.
• a IN (b, c, d) — true if a is equal to any value in the list — for example, any of b, c or d. The list can
contain up to 100 values, separated by commas.
Functions
Use the following functions to determine whether an attribute exists in an item, or to evaluate the value
of an attribute. These function names are case-sensitive. For a nested attribute, you must provide its full
document path.
Function
Description
attribute_exists (path)
True if the item contains the attribute speciﬁed by
path.
Example: Check whether an item in the Product
table has a side view picture.
• attribute_exists (Pictures.SideView)
attribute_not_exists (path)
True if the attribute speciﬁed by path does not
exist in the item.
Example: Check whether an item has a
Manufacturer attribute
• attribute_not_exists (Manufacturer)
attribute_type (path, type)
True if the attribute at the speciﬁed path is of a
particular data type. The type parameter must be
one of the following:
• S — String
• SS — String Set
• N — Number
• NS — Number Set
• B — Binary
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Function
Description
• BS — Binary Set
• BOOL — Boolean
• NULL — Null
• L — List
• M — Map
You must use an expression attribute value for the
type parameter.
Example: Check whether the QuantityOnHand
attribute is of type List. In this example, :v_sub is
a placeholder for the string L.
• attribute_type
(ProductReviews.FiveStar, :v_sub)
You must use an expression attribute value for the
second parameter.
begins_with (path, substr)
True if the attribute speciﬁed by path begins with
a particular substring.
Example: Check whether the ﬁrst few characters
of the front view picture URL are http://.
• begins_with (Pictures.FrontView, :v_sub)
The expression attribute value :v_sub is a
placeholder for http://.
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Function
Description
contains (path, operand)
True if the attribute speciﬁed by path is:
• a String that contains a particular substring.
• a Set that contains a particular element within
the set.
In either case, operand must be a String.
The path and the operand must be distinct; that
is, contains (a, a) will return an error.
Example: Check whether the Brand attribute
contains the substring Company.
• contains (Brand, :v_sub)
The expression attribute value :v_sub is a
placeholder for Company.
Example: Check whether the product is available
in red.
• contains (Color, :v_sub)
The expression attribute value :v_sub is a
placeholder for Red.
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Function
Description
size (path)
Returns a number representing an attribute's size.
The following are valid data types for use with
size.
If the attribute is of type String, size returns the
length of the string.
Example: Check whether the string Brand is less
than or equal to 20 characters. The expression
attribute value :v_sub is a placeholder for 20.
• size (Brand) &lt;= :v_sub
If the attribute is of type Binary, size returns the
number of bytes in the attribute value.
Example: Suppose that the ProductCatalog item
has a Binary attribute named VideoClip, which
contains a short video of the product in use. The
following expression checks whether VideoClip
exceeds 64,000 bytes. The expression attribute
value :v_sub is a placeholder for 64000.
• size(VideoClip) &gt; :v_sub
If the attribute is a Set data type, size returns the
number of elements in the set.
Example: Check whether the product is available
in more than one color. The expression attribute
value :v_sub is a placeholder for 1.
• size (Color) &lt; :v_sub
If the attribute is of type List or Map, size returns
the number of child elements.
Example: Check whether the number of OneStar
reviews has exceeded a certain threshold. The
expression attribute value :v_sub is a placeholder
for 3.
• size(ProductReviews.OneStar) &gt; :v_sub
Logical Evaluations
Use the AND, OR and NOT keywords to perform logical evaluations. In the list following, a and b represent
conditions to be evaluated.
• a AND b — true if a and b are both true.
• a OR b — true if either a or b (or both) are true.
• NOT a — true if a is false; false if a is true.
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Parentheses
Use parentheses to change the precedence of a logical evaluation. For example, suppose that conditions
a and b are true, and that condition c is false. The following expression evaluates to true:
• a OR b AND c
However, if you enclose a condition in parentheses, it is evaluated ﬁrst. For example, the following
evaluates to false:
• (a OR b) AND c
Note
You can nest parentheses in an expression. The innermost ones are evaluated ﬁrst.
Precedence in Conditions
DynamoDB evaluates conditions from left to right using the following precedence rules:
• = &lt;&gt; &lt; &lt;= &gt; &gt;=
• IN
• BETWEEN
• attribute_exists attribute_not_exists begins_with contains
• Parentheses
• NOT
• AND
• OR
Update Expressions
To update an existing item in a table, you use the UpdateItem operation. You must provide the key of the
item you want to update. You must also provide an update expression, indicating the attributes you want
to modify and the values you want to assign to them.
An update expression speciﬁes how UpdateItem will modify the attributes of an item—for example,
setting a scalar value, or removing elements from a list or a map.
The following is a syntax summary for update expressions:
update-expression ::=
[ SET action [, action] ... ]
[ REMOVE action [, action] ...]
[ ADD action [, action] ... ]
[ DELETE action [, action] ...]
An update expression consists of one or more clauses. Each clause begins with a SET, REMOVE, ADD or
DELETE keyword. You can include any of these clauses in an update expression, in any order. However,
each action keyword can appear only once.
Within each clause are one or more actions, separated by commas. Each action represents a data
modiﬁcation.
The examples in this section are based on the ProductCatalog item shown in Projection
Expressions (p. 341).
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Topics
• SET—Modifying or Adding Item Attributes (p. 355)
• REMOVE—Deleting Attributes From An Item (p. 359)
• ADD—Updating Numbers and Sets (p. 360)
• DELETE—Removing Elements From A Set (p. 362)
SET—Modifying or Adding Item Attributes
Use the SET action in an update expression to add one or more attributes to an item. If any of these
attribute already exist, they are overwritten by the new values.
You can also use SET to add or subtract from an attribute that is of type Number. To perform multiple
SET actions, separate them by commas.
In the following syntax summary:
• The path element is the document path to the item.
• An operand element can be either a document path to an item, or a function.
set-action ::=
path = value
value ::=
operand
| operand '+' operand
| operand '-' operand
operand ::=
path | function
The following PutItem operation creates a sample item that we will refer to in the examples:
aws dynamodb put-item \
--table-name ProductCatalog \
--item file://item.json
The arguments for --item are stored in the ﬁle item.json. (For simplicity, only a few item attributes are
used.)
{
}
&quot;Id&quot;: {&quot;N&quot;: &quot;789&quot;},
&quot;ProductCategory&quot;: {&quot;S&quot;: &quot;Home Improvement&quot;},
&quot;Price&quot;: {&quot;N&quot;: &quot;52&quot;},
&quot;InStock&quot;: {&quot;BOOL&quot;: true},
&quot;Brand&quot;: {&quot;S&quot;: &quot;Acme&quot;}
Topics
• Modifying Attributes (p. 356)
• Adding Lists and Maps (p. 356)
• Adding Elements To a List (p. 357)
• Adding Nested Map Attributes (p. 357)
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• Incrementing and Decrementing Numeric Attributes (p. 358)
• Appending Elements To a List (p. 358)
• Preventing Overwrites of an Existing Attribute (p. 359)
Modifying Attributes
Example
Update the ProductCategory and Price attributes:
aws dynamodb update-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;789&quot;}}' \
--update-expression &quot;SET ProductCategory = :c, Price = :p&quot; \
--expression-attribute-values file://values.json \
--return-values ALL_NEW
The arguments for --expression-attribute-values are stored in the ﬁle values.json:
{
}
&quot;:c&quot;: { &quot;S&quot;: &quot;Hardware&quot; },
&quot;:p&quot;: { &quot;N&quot;: &quot;60&quot; }
Note
In the UpdateItem operation, --return-values ALL_NEW causes DynamoDB to return the item as
it appears after the update.
Adding Lists and Maps
Example
Add a new list and a new map.
aws dynamodb update-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;789&quot;}}' \
--update-expression &quot;SET RelatedItems = :ri, ProductReviews = :pr&quot; \
--expression-attribute-values file://values.json \
--return-values ALL_NEW
The arguments for --expression-attribute-values are stored in the ﬁle values.json:
{
&quot;:ri&quot;: {
&quot;L&quot;: [
{ &quot;S&quot;: &quot;Hammer&quot; }
]
},
&quot;:pr&quot;: {
&quot;M&quot;: {
&quot;FiveStar&quot;: {
&quot;L&quot;: [
{ &quot;S&quot;: &quot;Best product ever!&quot; }
]
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}
}
}
}
Adding Elements To a List
Example
Add a new attribute to the RelatedItems list. (Remember that list elements are zero-based, so [0]
represents the ﬁrst element in the list, [1] represents the second, and so on.)
aws dynamodb update-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;789&quot;}}' \
--update-expression &quot;SET RelatedItems[1] = :ri&quot; \
--expression-attribute-values file://values.json \
--return-values ALL_NEW
The arguments for --expression-attribute-values are stored in the ﬁle values.json:
{
}
&quot;:ri&quot;: { &quot;S&quot;: &quot;Nails&quot; }
Note
When you use SET to update a list element, the contents of that element are replaced with
the new data that you specify. If the element does not already exist, SET will append the new
element at the end of the list.
If you add multiple elements in a single SET operation, the elements are sorted in order by
element number.
Adding Nested Map Attributes
Example
Add some nested map attributes:
aws dynamodb update-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;789&quot;}}' \
--update-expression &quot;SET #pr.#5star[1] = :r5, #pr.#3star = :r3&quot; \
--expression-attribute-names file://names.json \
--expression-attribute-values file://values.json \
--return-values ALL_NEW
The arguments for --expression-attribute-names are stored in the ﬁle names.json:
{
}
&quot;#pr&quot;: &quot;ProductReviews&quot;,
&quot;#5star&quot;: &quot;FiveStar&quot;,
&quot;#3star&quot;: &quot;ThreeStar&quot;
The arguments for --expression-attribute-values are stored in the ﬁle values.json:
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{
}
&quot;:r5&quot;: { &quot;S&quot;: &quot;Very happy with my purchase&quot; },
&quot;:r3&quot;: {
&quot;L&quot;: [
{ &quot;S&quot;: &quot;Just OK - not that great&quot; }
]
}
Incrementing and Decrementing Numeric Attributes
You can add to or subtract from an existing numeric attribute. To do this, use the + (plus) and - (minus)
operators.
Example
Decrease the Price of an item:
aws dynamodb update-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;789&quot;}}' \
--update-expression &quot;SET Price = Price - :p&quot; \
--expression-attribute-values '{&quot;:p&quot;: {&quot;N&quot;:&quot;15&quot;}}' \
--return-values ALL_NEW
To increase the Price, you would use the + operator in the update expression.
Appending Elements To a List
You can add elements to the end of a list,. To do this, use SET with the list_append function. (The
function name is case-sensitive.) The list_append function is speciﬁc to the SET action, and can only be
used in an update expression. The syntax is:
• list_append (list1, list2)
The function takes two lists as input, and appends list2 to list1.
Example
In Adding Elements To a List (p. 357), we created the RelatedItems list and populated it with two
elements: Hammer and Nails. Now we will append two more elements to the end of RelatedItems:
aws dynamodb update-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;789&quot;}}' \
--update-expression &quot;SET #ri = list_append(#ri, :vals)&quot; \
--expression-attribute-names '{&quot;#ri&quot;: &quot;RelatedItems&quot;}' \
--expression-attribute-values file://values.json \
--return-values ALL_NEW
The arguments for --expression-attribute-values are stored in the ﬁle values.json:
{
&quot;:vals&quot;: {
&quot;L&quot;: [
{ &quot;S&quot;: &quot;Screwdriver&quot; },
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}
}
]
{&quot;S&quot;: &quot;Hacksaw&quot; }
Finally, we will append one more element to the beginning of RelatedItems. To do this, we will swap the
order of the list_append elements. (Remember that list_append takes two lists as input, and appends
the second list to the ﬁrst.)
aws dynamodb update-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;789&quot;}}' \
--update-expression &quot;SET #ri = list_append(:vals, #ri)&quot; \
--expression-attribute-names '{&quot;#ri&quot;: &quot;RelatedItems&quot;}' \
--expression-attribute-values '{&quot;:vals&quot;: {&quot;L&quot;: [ { &quot;S&quot;: &quot;Chisel&quot; }]}}' \
--return-values ALL_NEW
The resulting RelatedItems attribute now contains ﬁve elements, in the following order: Chisel, Hammer,
Nails, Screwdriver, Hacksaw.
Preventing Overwrites of an Existing Attribute
If you want to avoid overwriting an existing attribute, you can use SET with the if_not_exists function.
(The function name is case-sensitive.) The if_not_exists function is speciﬁc to the SET action, and can
only be used in an update expression. The syntax is:
• if_not_exists (path, value)
If the item does not contain an attribute at the speciﬁed path, then if_not_exists evaluates to value;
otherwise, it evaluates to path.
Example
Set the Price of an item, but only if the item does not already have a Price attribute. (If Price already
exists, nothing happens.)
aws dynamodb update-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;789&quot;}}' \
--update-expression &quot;SET Price = if_not_exists(Price, :p)&quot; \
--expression-attribute-values '{&quot;:p&quot;: {&quot;N&quot;: &quot;100&quot;}}' \
--return-values ALL_NEW
REMOVE—Deleting Attributes From An Item
Use the REMOVE action in an update expression to remove one or more attributes from an item. To
perform multiple REMOVE actions, separate them by commas.
The following is a syntax summary for REMOVE in an update expression. The only operand is the
document path for the attribute you want to remove:
remove-action ::=
path
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Example
Remove some attributes from an item. (If the attributes do not exist, nothing happens.)
aws dynamodb update-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;789&quot;}}' \
--update-expression &quot;REMOVE Brand, InStock, QuantityOnHand&quot; \
--return-values ALL_NEW
Removing Elements From a List
You can use REMOVE to delete individual elements from a list.
Example
In Appending Elements To a List (p. 358), we modiﬁed a list attribute (RelatedItems) so that it
contained ﬁve elements:
• [0]—Chisel
• [1]—Hammer
• [2]—Nails
• [3]—Screwdriver
• [4]—Hacksaw
The following AWS CLI example deletes Hammer and Nails from the list.
aws dynamodb update-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;789&quot;}}' \
--update-expression &quot;REMOVE RelatedItems[1], RelatedItems[2]&quot; \
--return-values ALL_NEW
After removing Hammer and Nails, the remaining elements are shifted. The list now contains the
following:
• [0]—Chisel
• [1]—Screwdriver
• [2]—Hacksaw
ADD—Updating Numbers and Sets
Note
In general, we recommend using SET rather than ADD.
Use the ADD action in an update expression to add a new attribute and its value(s) to an item.
If the attribute already exists, then the behavior of ADD depends on the attribute's data type:
• If the attribute is a number, and the value you are adding is also a number, then the value is
mathematically added to the existing attribute. (If the value is a negative number, then it is subtracted
from the existing attribute.)
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• If the attribute is a set, and the value you are adding is also a set, then the value is appended to the
existing set.
Note
The ADD action only supports number and set data types.
To perform multiple ADD actions, separate them by commas.
In the following syntax summary:
• The path element is the document path to an attribute. The attribute must be either a Number or a set
data type.
• The value element is a number that you want to add to the attribute (for Number data types), or a set
to append to the attribute (for set types).
add-action ::=
path value
Adding a Number
Assume that the QuantityOnHand attribute does not exist. The following AWS CLI example sets
QuantityOnHand to 5:
aws dynamodb update-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;789&quot;}}' \
--update-expression &quot;ADD QuantityOnHand :q&quot; \
--expression-attribute-values '{&quot;:q&quot;: {&quot;N&quot;: &quot;5&quot;}}' \
--return-values ALL_NEW
Now that QuantityOnHand exists, you can re-run the example to increment QuantityOnHand by 5 each
time.
Adding Elements To A Set
Assume that the Color attribute does not exist. The following AWS CLI example sets Color to a string set
with two elements:
aws dynamodb update-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;789&quot;}}' \
--update-expression &quot;ADD Color :c&quot; \
--expression-attribute-values '{&quot;:c&quot;: {&quot;SS&quot;:[&quot;Orange&quot;, &quot;Purple&quot;]}}' \
--return-values ALL_NEW
Now that Color exists, we can add more elements to it:
aws dynamodb update-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;789&quot;}}' \
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--update-expression &quot;ADD Color :c&quot; \
--expression-attribute-values '{&quot;:c&quot;: {&quot;SS&quot;:[&quot;Yellow&quot;, &quot;Green&quot;, &quot;Blue&quot;]}}' \
--return-values ALL_NEW
DELETE—Removing Elements From A Set
Important
The DELETE action only supports Set data types.
Use the DELETE action in an update expression to remove one or more elements from a set. To perform
multiple DELETE actions, separate them by commas.
In the following syntax summary:
• The path element is the document path to an attribute. The attribute must be a set data type.
• The subset is one or more elements that you want to delete from path. that you want to delete. You
must specify subset as a set type.
delete-action ::=
path value
Example
In Adding Elements To A Set (p. 361), we created the Colors string set. This example removes some of
the elements from that set:
aws dynamodb update-item \
--table-name ProductCatalog \
--key '{&quot;Id&quot;:{&quot;N&quot;:&quot;789&quot;}}' \
--update-expression &quot;DELETE Color :p&quot; \
--expression-attribute-values '{&quot;:p&quot;: {&quot;SS&quot;: [&quot;Yellow&quot;, &quot;Purple&quot;]}}' \
--return-values ALL_NEW
Time To Live
Time To Live (TTL) for DynamoDB allows you to deﬁne when items in a table expire so that they can be
automatically deleted from the database.
TTL is provided at no extra cost as a way to reduce storage usage and reduce the cost of storing
irrelevant data without using provisioned throughput. With TTL enabled on a table, you can set a
timestamp for deletion on a per-item basis, allowing you to limit storage usage to only those records
that are relevant.
TTL is useful if you have continuously accumulating data that loses relevance after a speciﬁc time period.
For example: session data, event logs, usage patterns, and other temporary data. If you have sensitive
data that must be retained only for a certain amount of time according to contractual or regulatory
obligations, TTL helps you ensure that it is removed promptly and as scheduled.
To get started with TTL:
1. Understand Time To Live: How It Works (p. 363).
2. Read the Before You Begin Using Time To Live (p. 364) section.
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3. Enable TTL on a speciﬁc table and choose the name of an attribute to hold the expiration timestamp.
Then, you can add or update items in the table with timestamps in the attribute you chose. For more
information, see Enabling Time To Live (p. 364).
Time To Live: How It Works
When Time To Live is enabled on a table, a background job checks the TTL attribute of items to see if
they are expired.
TTL compares the current time in epoch time format to the time stored in the Time To Live attribute of
an item. If the epoch time value stored in the attribute is less than the current time, the item is marked
as expired and subsequently deleted.
Note
The epoch time format is the number of seconds elapsed since 12:00:00 AM January 1st, 1970
UTC.
DynamoDB deletes expired items on a best-eﬀort basis to ensure availability of throughput for other
data operations.
Important
DynamoDB typically deletes expired items within 48 hours of expiration. The exact duration
within which an item truly gets deleted after expiration is speciﬁc to the nature of the workload
and the size of the table. Items that have expired and not been deleted will still show up in
reads, queries, and scans.
As items are deleted, they are removed from any Local Secondary Index and Global Secondary Index
immediately in the same eventually consistent way as a standard delete operation.
For example, consider a table named SessionData that tracks the session history of users. Each item in
SessionData is identiﬁed by a partition key (UserName) and a sort key (SessionId). Additional attributes
like UserName,SessionId, CreationTime and ExpirationTime track the session information.
The following diagram shows how the items in the table would be organized. The ExpirationTime
attribute is set as the Time To Live (TTL) attribute. (Not all of the attributes are shown)
SessionData
UserName
SessionId
SessionInfo
…
user1
746865726527731461931200
1461938400
{JSON
Document}
...
user2
6e6f7468696e671461920400
1461927600
{JSON
Document}
...
user3
746f20736565201461922200
1461929400
{JSON
Document}
...
user4
686572652121211461925380
1461932580
{JSON
Document}
…
user5
6e6572642e2e2e1461920400
1461927600
{JSON
Document}
...
...
...
CreationTime ExpirationTime
(TTL)
...
...
...
…
In this example each item has an ExpirationTime attribute value set when it is created. Consider the ﬁrst
record:
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SessionData
UserName
SessionId
CreationTime ExpirationTime
(TTL)
user1
746865726527731461931200
1461938400
SessionInfo
…
{JSON
Document}
...
In this example, the item CreationTime is set to Friday, April 29 12:00 PM UTC 2016 and the
ExpirationTime is set 2 hours later at Friday, April 29 2:00 PM UTC 2016. The item will expire when the
current time, in epoch format, is greater than the time in the ExpirationTime attribute. In this case,
the item with the key { Username: user1, SessionId: 74686572652773 } will expire after 2:00 PM
(1461938400).
Note
Due to the potential delay between expiration and deletion time, you might get expired items
when you query for items. If you don’t need to view expired items when you issue a read
request, you should ﬁlter out the expired items using the expiration attribute that you have
deﬁned
You can do this by using a ﬁlter expression that returns only items where the Time To Live
expiration value is greater than the current time in epoch format. For more information, see
Filter Expressions for Query (p. 412) and Filter Expressions for Scan (p. 427).
Before You Begin Using Time To Live
Before you enable Time To Live on a table, consider the following:
• Ensure that any existing timestamp values in the speciﬁed Time To Live attribute are correct and in the
right format.
• Items with an expiration time greater than 5 years in the past are not deleted.
• If data recovery is a concern, we recommend that you back up your table.
• For a 24-hour recovery window, you can use Amazon DynamoDB Streams. For more information, see
DynamoDB Streams and Time To Live (p. 523).
• For a full backup, you can use AWS Data Pipeline. For more information, see Exporting and
Importing DynamoDB Data Using AWS Data Pipeline (p. 715).
• You can use IAM policies to prevent unauthorized updates to the TTL attribute or conﬁguration of the
Time To Live feature. If you only allow access to speciﬁed actions in your existing IAM policies, ensure
that your policies are updated to allow dynamodb:UpdateTimeToLive for roles that need to enable or
disable Time To Live on tables. For more information, see Using Identity-Based Policies (IAM Policies)
for Amazon DynamoDB (p. 607).
• Consider whether you need to do any post-processing of deleted items. The Streams records of TTL
deletes are marked and you can monitor them using an AWS Lambda function. For more information
on the additions to the Streams record, see DynamoDB Streams and Time To Live (p. 523).
Enabling Time To Live
This section describes how to use the DynamoDB console or CLI to enable Time To Live. To use the API
instead, see Amazon DynamoDB API Reference.
Topics
• Enable Time To Live (console) (p. 365)
• Enable Time To Live (CLI) (p. 367)
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Enable Time To Live (console)
To enable Time To Live using the DynamoDB console:
1.
Open the DynamoDB console at https://console.aws.amazon.com/dynamodb/home.
2.
Choose Tables and then choose the table that you want to modify.
3.
In Table details, next to TTL attribute, choose Manage TTL.
4.
In the Manage TTL dialog box, choose Enable TTL and then type the TTL attribute name.
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There are three settings in Manage TTL:
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5.
• Enable TTL – Choose this to either enable or disable TTL on the table. It may take up to one hour
for the change to fully process.
• TTL Attribute – The name of the DynamoDB attribute to store the TTL timestamp for items.
• 24-hour backup streams – Choose this to enable Amazon DynamoDB Streams on the table. For
more information about how you can use DynamoDB Streams for backup, see DynamoDB Streams
and Time To Live (p. 523).
(Optional) To preview some of the items that will be deleted when TTL is enabled, choose Run
preview.
Warning
This provides you with a sample list of items. It does not provide you with a complete list of
items that will be deleted by TTL.
6.
Choose Continue to save the settings and enable TTL.
Now that TTL is enabled, the TTL attribute is marked TTL when you view items in the DynamoDB
console.
You can view the date and time that an item will expire by hovering your mouse over the attribute.
Enable Time To Live (CLI)
To enable TTL on the &quot;TTLExample&quot; table:
aws dynamodb update-time-to-live --table-name TTLExample --time-to-live-specification
&quot;Enabled=true, AttributeName=ttl&quot;
To describe TTL on the &quot;TTLExample&quot; table:
aws dynamodb describe-time-to-live --table-name TTLExample
{
&quot;TimeToLiveDescription&quot;: {
&quot;AttributeName&quot;: &quot;ttl&quot;,
&quot;TimeToLiveStatus&quot;: &quot;ENABLED&quot;
}
}
To add an item to the &quot;TTLExample&quot; table with the Time To Live attribute set using the BASH shell and
CLI:
EXP=`date -d '+5 days' +%s`
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aws dynamodb put-item --table-name &quot;TTLExample&quot; --item '{&quot;id&quot;: {&quot;N&quot;: &quot;1&quot;}, &quot;ttl&quot;: {&quot;N&quot;:
&quot;'$EXP'&quot;}}'
This example started with the current date and added ﬁve days to it to create an expiration time. Then, it
converts the expiration time to epoch time format to ﬁnally add an item to the &quot;TTLExample&quot; table.
Note
One way to set expiration values for Time To Live is to calculate the number of seconds to add
to the expiration time. For example, ﬁve days is 432000 seconds. However, it is often preferable
to start with a date and work from there.
It is fairly simple to get the current time in epoch time format. For example:
• Linux Terminal: date +%s
• Python: import time; long(time.time())
• Java: System.currentTimeMillis() / 1000L
• JavaScript: Math.floor(Date.now() / 1000)
Working with Items: Java
Topics
• Putting an Item (p. 368)
• Getting an Item (p. 371)
• Batch Write: Putting and Deleting Multiple Items (p. 373)
• Batch Get: Getting Multiple Items (p. 374)
• Updating an Item (p. 375)
• Deleting an Item (p. 377)
• Example: CRUD Operations Using the AWS SDK for Java Document API (p. 377)
• Example: Batch Operations Using AWS SDK for Java Document API (p. 381)
• Example: Handling Binary Type Attributes Using the AWS SDK for Java Document API (p. 385)
You can use the AWS SDK for Java Document API to perform typical create, read, update, and delete
(CRUD) operations on items in a table.
Note
The SDK for Java also provides an object persistence model, allowing you to map your clientside classes to DynamoDB tables. This approach can reduce the amount of code you have to
write. For more information, see Java: DynamoDBMapper (p. 195).
The following sections describe Java snippets to perform several Java Document API item actions. To run
complete working examples instead, see:
• Example: CRUD Operations Using the AWS SDK for Java Document API (p. 377)
• Example: Batch Operations Using AWS SDK for Java Document API (p. 381)
• Example: Handling Binary Type Attributes Using the AWS SDK for Java Document API (p. 385)
Putting an Item
The putItem method stores an item in a table. If the item exists, it replaces the entire item. Instead of
replacing the entire item, if you want to update only speciﬁc attributes, you can use the updateItem
method. For more information, see Updating an Item (p. 375).
Follow these steps:
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1. Create an instance of the DynamoDB class.
2. Create an instance of the Table class to represent the table you want to work with.
3. Create an instance of the Item class to represent the new item. You must specify the new item's
primary key and its attributes.
4. Call the putItem method of the Table object, using the Item that you created in the preceding step.
The following Java code snippet demonstrates the preceding tasks. The snippet writes a new item to the
ProductCatalog table.
Example
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
DynamoDB dynamoDB = new DynamoDB(client);
Table table = dynamoDB.getTable(&quot;ProductCatalog&quot;);
// Build a list of related items
List&lt;Number&gt; relatedItems = new ArrayList&lt;Number&gt;();
relatedItems.add(341);
relatedItems.add(472);
relatedItems.add(649);
//Build a map of product pictures
Map&lt;String, String&gt; pictures = new HashMap&lt;String, String&gt;();
pictures.put(&quot;FrontView&quot;, &quot;http://example.com/products/123_front.jpg&quot;);
pictures.put(&quot;RearView&quot;, &quot;http://example.com/products/123_rear.jpg&quot;);
pictures.put(&quot;SideView&quot;, &quot;http://example.com/products/123_left_side.jpg&quot;);
//Build a map of product reviews
Map&lt;String, List&lt;String&gt;&gt; reviews = new HashMap&lt;String, List&lt;String&gt;&gt;();
List&lt;String&gt; fiveStarReviews = new ArrayList&lt;String&gt;();
fiveStarReviews.add(&quot;Excellent! Can't recommend it highly enough!
fiveStarReviews.add(&quot;Do yourself a favor and buy this&quot;);
reviews.put(&quot;FiveStar&quot;, fiveStarReviews);
Buy it!&quot;);
List&lt;String&gt; oneStarReviews = new ArrayList&lt;String&gt;();
oneStarReviews.add(&quot;Terrible product! Do not buy this.&quot;);
reviews.put(&quot;OneStar&quot;, oneStarReviews);
// Build the item
Item item = new Item()
.withPrimaryKey(&quot;Id&quot;, 123)
.withString(&quot;Title&quot;, &quot;Bicycle 123&quot;)
.withString(&quot;Description&quot;, &quot;123 description&quot;)
.withString(&quot;BicycleType&quot;, &quot;Hybrid&quot;)
.withString(&quot;Brand&quot;, &quot;Brand-Company C&quot;)
.withNumber(&quot;Price&quot;, 500)
.withStringSet(&quot;Color&quot;, new HashSet&lt;String&gt;(Arrays.asList(&quot;Red&quot;, &quot;Black&quot;)))
.withString(&quot;ProductCategory&quot;, &quot;Bicycle&quot;)
.withBoolean(&quot;InStock&quot;, true)
.withNull(&quot;QuantityOnHand&quot;)
.withList(&quot;RelatedItems&quot;, relatedItems)
.withMap(&quot;Pictures&quot;, pictures)
.withMap(&quot;Reviews&quot;, reviews);
// Write the item to the table
PutItemOutcome outcome = table.putItem(item);
In the preceding example, the item has attributes that are scalars (String, Number, Boolean, Null), sets
(String Set), and document types (List, Map).
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Specifying Optional Parameters
Along with the required parameters, you can also specify optional parameters to the putItem method.
For example, the following Java code snippet uses an optional parameter to specify a condition
for uploading the item. If the condition you specify is not met, then the AWS Java SDK throws a
ConditionalCheckFailedException. The code snippet speciﬁes the following optional parameters in the
putItem method:
• A ConditionExpression that deﬁnes the conditions for the request. The snippet deﬁnes the condition
that the existing item that has the same primary key is replaced only if it has an ISBN attribute that
equals a speciﬁc value.
• A map for ExpressionAttributeValues that will be used in the condition. In this case, there is only
one substitution required: The placeholder :val in the condition expression will be replaced at runtime
with the actual ISBN value to be checked.
The following example adds a new book item using these optional parameters.
Example
Item item = new Item()
.withPrimaryKey(&quot;Id&quot;, 104)
.withString(&quot;Title&quot;, &quot;Book 104 Title&quot;)
.withString(&quot;ISBN&quot;, &quot;444-4444444444&quot;)
.withNumber(&quot;Price&quot;, 20)
.withStringSet(&quot;Authors&quot;,
new HashSet&lt;String&gt;(Arrays.asList(&quot;Author1&quot;, &quot;Author2&quot;)));
Map&lt;String, Object&gt; expressionAttributeValues = new HashMap&lt;String, Object&gt;();
expressionAttributeValues.put(&quot;:val&quot;, &quot;444-4444444444&quot;);
PutItemOutcome outcome = table.putItem(
item,
&quot;ISBN = :val&quot;, // ConditionExpression parameter
null,
// ExpressionAttributeNames parameter - we're not using it for this
example
expressionAttributeValues);
PutItem and JSON Documents
You can store a JSON document as an attribute in a DynamoDB table. To do this, use the withJSON
method of Item. This method will parse the JSON document and map each element to a native
DynamoDB data type.
Suppose that you wanted to store the following JSON document, containing vendors that can fulﬁll
orders for a particular product:
Example
{
&quot;V01&quot;: {
&quot;Name&quot;: &quot;Acme Books&quot;,
&quot;Offices&quot;: [ &quot;Seattle&quot; ]
},
&quot;V02&quot;: {
&quot;Name&quot;: &quot;New Publishers, Inc.&quot;,
&quot;Offices&quot;: [&quot;London&quot;, &quot;New York&quot;
]
},
&quot;V03&quot;: {
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}
}
&quot;Name&quot;: &quot;Better Buy Books&quot;,
&quot;Offices&quot;: [ &quot;Tokyo&quot;, &quot;Los Angeles&quot;, &quot;Sydney&quot;
]
You can use the withJSON method to store this in the ProductCatalog table, in a Map attribute named
VendorInfo. The following Java code snippet demonstrates how to do this.
// Convert the document into a String. Must escape all double-quotes.
String vendorDocument = &quot;{&quot;
+ &quot;
\&quot;V01\&quot;: {&quot;
+ &quot;
\&quot;Name\&quot;: \&quot;Acme Books\&quot;,&quot;
+ &quot;
\&quot;Offices\&quot;: [ \&quot;Seattle\&quot; ]&quot;
+ &quot;
},&quot;
+ &quot;
\&quot;V02\&quot;: {&quot;
+ &quot;
\&quot;Name\&quot;: \&quot;New Publishers, Inc.\&quot;,&quot;
+ &quot;
\&quot;Offices\&quot;: [ \&quot;London\&quot;, \&quot;New York\&quot;&quot; + &quot;]&quot; + &quot;},&quot;
+ &quot;
\&quot;V03\&quot;: {&quot;
+ &quot;
\&quot;Name\&quot;: \&quot;Better Buy Books\&quot;,&quot;
+
&quot;\&quot;Offices\&quot;: [ \&quot;Tokyo\&quot;, \&quot;Los Angeles\&quot;, \&quot;Sydney\&quot;&quot;
+ &quot;
]&quot;
+ &quot;
}&quot;
+ &quot;
}&quot;;
Item item = new Item()
.withPrimaryKey(&quot;Id&quot;, 210)
.withString(&quot;Title&quot;, &quot;Book 210 Title&quot;)
.withString(&quot;ISBN&quot;, &quot;210-2102102102&quot;)
.withNumber(&quot;Price&quot;, 30)
.withJSON(&quot;VendorInfo&quot;, vendorDocument);
PutItemOutcome outcome = table.putItem(item);
Getting an Item
To retrieve a single item, use the getItem method of a Table object. Follow these steps:
1. Create an instance of the DynamoDB class.
2. Create an instance of the Table class to represent the table you want to work with.
3. Call the getItem method of the Table instance. You must specify the primary key of the item that you
want to retrieve.
The following Java code snippet demonstrates the preceding steps. The code snippet gets the item that
has the speciﬁed partition key.
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
DynamoDB dynamoDB = new DynamoDB(client);
Table table = dynamoDB.getTable(&quot;ProductCatalog&quot;);
Item item = table.getItem(&quot;Id&quot;, 101);
Specifying Optional Parameters
Along with the required parameters, you can also specify optional parameters for the getItem method.
For example, the following Java code snippet uses an optional method to retrieve only a speciﬁc list of
attributes, and to specify strongly consistent reads. (To learn more about read consistency, see Read
Consistency (p. 15).)
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You can use a ProjectionExpression to retrieve only speciﬁc attributes or elements, rather than an
entire item. A ProjectionExpression can specify top-level or nested attributes, using document paths.
For more information, see Projection Expressions (p. 341).
The parameters of the getItem method do not let you specify read consistency; however, you can create
a GetItemSpec, which provides full access to all of the inputs to the low-level GetItem operation. The
code example below creates a GetItemSpec, and uses that spec as input to the getItem method.
Example
GetItemSpec spec = new GetItemSpec()
.withPrimaryKey(&quot;Id&quot;, 206)
.withProjectionExpression(&quot;Id, Title, RelatedItems[0], Reviews.FiveStar&quot;)
.withConsistentRead(true);
Item item = table.getItem(spec);
System.out.println(item.toJSONPretty());
To print an Item in a human-readable format, use the toJSONPretty method. The output from the
example above looks like this:
{
&quot;RelatedItems&quot; : [ 341 ],
&quot;Reviews&quot; : {
&quot;FiveStar&quot; : [ &quot;Excellent! Can't recommend it highly enough!
favor and buy this&quot; ]
},
&quot;Id&quot; : 123,
&quot;Title&quot; : &quot;20-Bicycle 123&quot;
Buy it!&quot;, &quot;Do yourself a
}
GetItem and JSON Documents
In the PutItem and JSON Documents (p. 370) section, we stored a JSON document in a Map attribute
named VendorInfo. You can use the getItem method to retrieve the entire document in JSON format, or
use document path notation to retrieve only some of the elements in the document. The following Java
code snippet demonstrates these techniques.
GetItemSpec spec = new GetItemSpec()
.withPrimaryKey(&quot;Id&quot;, 210);
System.out.println(&quot;All vendor info:&quot;);
spec.withProjectionExpression(&quot;VendorInfo&quot;);
System.out.println(table.getItem(spec).toJSON());
System.out.println(&quot;A single vendor:&quot;);
spec.withProjectionExpression(&quot;VendorInfo.V03&quot;);
System.out.println(table.getItem(spec).toJSON());
System.out.println(&quot;First office location for this vendor:&quot;);
spec.withProjectionExpression(&quot;VendorInfo.V03.Offices[0]&quot;);
System.out.println(table.getItem(spec).toJSON());
The output from the example above looks like this:
All vendor info:
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{&quot;VendorInfo&quot;:{&quot;V03&quot;:{&quot;Name&quot;:&quot;Better Buy Books&quot;,&quot;Offices&quot;:[&quot;Tokyo&quot;,&quot;Los
Angeles&quot;,&quot;Sydney&quot;]},&quot;V02&quot;:{&quot;Name&quot;:&quot;New Publishers, Inc.&quot;,&quot;Offices&quot;:[&quot;London&quot;,&quot;New
York&quot;]},&quot;V01&quot;:{&quot;Name&quot;:&quot;Acme Books&quot;,&quot;Offices&quot;:[&quot;Seattle&quot;]}}}
A single vendor:
{&quot;VendorInfo&quot;:{&quot;V03&quot;:{&quot;Name&quot;:&quot;Better Buy Books&quot;,&quot;Offices&quot;:[&quot;Tokyo&quot;,&quot;Los
Angeles&quot;,&quot;Sydney&quot;]}}}
First office location for a single vendor:
{&quot;VendorInfo&quot;:{&quot;V03&quot;:{&quot;Offices&quot;:[&quot;Tokyo&quot;]}}}
Note
You can use the toJSON method to convert any item (or its attributes) to a JSON-formatted
string. The following code snippet retrieves several top-level and nested attributes, and prints
the results as JSON:
GetItemSpec spec = new GetItemSpec()
.withPrimaryKey(&quot;Id&quot;, 210)
.withProjectionExpression(&quot;VendorInfo.V01, Title, Price&quot;);
Item item = table.getItem(spec);
System.out.println(item.toJSON());
The output looks like this:
{&quot;VendorInfo&quot;:{&quot;V01&quot;:{&quot;Name&quot;:&quot;Acme Books&quot;,&quot;Offices&quot;:
[&quot;Seattle&quot;]}},&quot;Price&quot;:30,&quot;Title&quot;:&quot;Book 210 Title&quot;}
Batch Write: Putting and Deleting Multiple Items
Batch write refers to putting and deleting multiple items in a batch. The batchWriteItem method
enables you to put and delete multiple items from one or more tables in a single call. The following are
the steps to put or delete multiple items using the AWS SDK for Java Document API.
1. Create an instance of the DynamoDB class.
2. Create an instance of the TableWriteItems class that describes all the put and delete operations for a
table. If you want to write to multiple tables in a single batch write operation, you will need to create
one TableWriteItems instance per table.
3. Call the batchWriteItem method by providing the TableWriteItems object(s) that you created in the
preceding step.
4. Process the response. You should check if there were any unprocessed request items returned in the
response. This could happen if you reach the provisioned throughput limit or some other transient
error. Also, DynamoDB limits the request size and the number of operations you can specify in a
request. If you exceed these limits, DynamoDB rejects the request. For more information, see Limits in
DynamoDB (p. 724).
The following Java code snippet demonstrates the preceding steps. The example performs a
batchWriteItem operation on two tables - Forum and Thread. The corresponding TableWriteItems
objects deﬁne the following actions:
• Put an item in the Forum table
• Put and delete an item in the Thread table
The code then calls batchWriteItem to perform the operation.
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
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DynamoDB dynamoDB = new DynamoDB(client);
TableWriteItems forumTableWriteItems = new TableWriteItems(&quot;Forum&quot;)
.withItemsToPut(
new Item()
.withPrimaryKey(&quot;Name&quot;, &quot;Amazon RDS&quot;)
.withNumber(&quot;Threads&quot;, 0));
TableWriteItems threadTableWriteItems = new TableWriteItems(Thread)
.withItemsToPut(
new Item()
.withPrimaryKey(&quot;ForumName&quot;,&quot;Amazon RDS&quot;,&quot;Subject&quot;,&quot;Amazon RDS Thread 1&quot;)
.withHashAndRangeKeysToDelete(&quot;ForumName&quot;,&quot;Some partition key value&quot;, &quot;Amazon S3&quot;,
&quot;Some sort key value&quot;);
BatchWriteItemOutcome outcome = dynamoDB.batchWriteItem(forumTableWriteItems,
threadTableWriteItems);
// Code for checking unprocessed items is omitted in this example
For a working example, see Example: Batch Write Operation Using the AWS SDK for Java Document
API (p. 381).
Batch Get: Getting Multiple Items
The batchGetItem method enables you to retrieve multiple items from one or more tables. To retrieve a
single item, you can use the getItem method.
Follow these steps:
1. Create an instance of the DynamoDB class.
2. Create an instance of the TableKeysAndAttributes class that describes a list of primary key values to
retrieve from a table. If you want to read from multiple tables in a single batch get operation, you will
need to create one TableKeysAndAttributes instance per table.
3. Call the batchGetItem method by providing the TableKeysAndAttributes object(s) that you created in
the preceding step.
The following Java code snippet demonstrates the preceding steps. The example retrieves two items
from the Forum table and three items from the Thread table.
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
DynamoDB dynamoDB = new DynamoDB(client);
TableKeysAndAttributes forumTableKeysAndAttributes = new
TableKeysAndAttributes(forumTableName);
forumTableKeysAndAttributes.addHashOnlyPrimaryKeys(&quot;Name&quot;,
&quot;Amazon S3&quot;,
&quot;Amazon DynamoDB&quot;);
TableKeysAndAttributes threadTableKeysAndAttributes = new
TableKeysAndAttributes(threadTableName);
threadTableKeysAndAttributes.addHashAndRangePrimaryKeys(&quot;ForumName&quot;, &quot;Subject&quot;,
&quot;Amazon DynamoDB&quot;,&quot;DynamoDB Thread 1&quot;,
&quot;Amazon DynamoDB&quot;,&quot;DynamoDB Thread 2&quot;,
&quot;Amazon S3&quot;,&quot;S3 Thread 1&quot;);
BatchGetItemOutcome outcome = dynamoDB.batchGetItem(
forumTableKeysAndAttributes, threadTableKeysAndAttributes);
for (String tableName : outcome.getTableItems().keySet()) {
System.out.println(&quot;Items in table &quot; + tableName);
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}
List&lt;Item&gt; items = outcome.getTableItems().get(tableName);
for (Item item : items) {
System.out.println(item);
}
Specifying Optional Parameters
Along with the required parameters, you can also specify optional parameters when using batchGetItem.
For example, you can provide a ProjectionExpression with each TableKeysAndAttributes you deﬁne.
This allows you to specify the attributes that you want to retrieve from the table.
The following code snippet retrieves two items from the Forum table. The withProjectionExpression
parameter speciﬁes that only the Threads attribute is to be retrieved.
Example
TableKeysAndAttributes forumTableKeysAndAttributes = new TableKeysAndAttributes(&quot;Forum&quot;)
.withProjectionExpression(&quot;Threads&quot;);
forumTableKeysAndAttributes.addHashOnlyPrimaryKeys(&quot;Name&quot;,
&quot;Amazon S3&quot;,
&quot;Amazon DynamoDB&quot;);
BatchGetItemOutcome outcome = dynamoDB.batchGetItem(forumTableKeysAndAttributes);
Updating an Item
The updateItem method of a Table object can update existing attribute values, add new attributes, or
delete attributes from an existing item.
The updateItem method behaves as follows:
• If an item does not exist (no item in the table with the speciﬁed primary key), updateItem adds a new
item to the table
• If an item exists, updateItem performs the update as speciﬁed by the UpdateExpression parameter:
Note
It is also possible to &quot;update&quot; an item using putItem. For example, if you call putItem to add
an item to the table, but there is already an item with the speciﬁed primary key, putItem will
replace the entire item. If there are attributes in the existing item that are not speciﬁed in the
input, putItem will remove those attributes from the item.
In general, we recommend that you use updateItem whenever you want to modify any item
attributes. The updateItem method will only modify the item attributes that you specify in the
input, and the other attributes in the item will remain unchanged.
Follow these steps:
1. Create an instance of the Table class to represent the table you want to work with.
2. Call the updateTable method of the Table instance. You must specify the primary key of the item that
you want to retrieve, along with an UpdateExpression that describes the attributes to modify and how
to modify them.
The following Java code snippet demonstrates the preceding tasks. The snippet updates a book item
in the ProductCatalog table. It adds a new author to the set of Authors and deletes the existing ISBN
attribute. It also reduces the price by one.
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An ExpressionAttributeValues map is used in the UpdateExpression. The placeholders :val1 and :val2
will be replaced at runtime with the actual values for Authors and Price.
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
DynamoDB dynamoDB = new DynamoDB(client);
Table table = dynamoDB.getTable(&quot;ProductCatalog&quot;);
Map&lt;String, String&gt; expressionAttributeNames = new HashMap&lt;String, String&gt;();
expressionAttributeNames.put(&quot;#A&quot;, &quot;Authors&quot;);
expressionAttributeNames.put(&quot;#P&quot;, &quot;Price&quot;);
expressionAttributeNames.put(&quot;#I&quot;, &quot;ISBN&quot;);
Map&lt;String, Object&gt; expressionAttributeValues = new HashMap&lt;String, Object&gt;();
expressionAttributeValues.put(&quot;:val1&quot;,
new HashSet&lt;String&gt;(Arrays.asList(&quot;Author YY&quot;,&quot;Author ZZ&quot;)));
expressionAttributeValues.put(&quot;:val2&quot;, 1);
//Price
UpdateItemOutcome outcome = table.updateItem(
&quot;Id&quot;,
// key attribute name
101,
// key attribute value
&quot;add #A :val1 set #P = #P - :val2 remove #I&quot;, // UpdateExpression
expressionAttributeNames,
expressionAttributeValues);
Specifying Optional Parameters
Along with the required parameters, you can also specify optional parameters for the updateItem
method including a condition that must be met in order for the update is to occur. If the condition
you specify is not met, then the AWS Java SDK throws a ConditionalCheckFailedException. For
example, the following Java code snippet conditionally updates a book item price to 25. It speciﬁes a
ConditionExpression stating that the price should be updated only if the existing price is 20.
Example
Table table = dynamoDB.getTable(&quot;ProductCatalog&quot;);
Map&lt;String, String&gt; expressionAttributeNames = new HashMap&lt;String, String&gt;();
expressionAttributeNames.put(&quot;#P&quot;, &quot;Price&quot;);
Map&lt;String, Object&gt; expressionAttributeValues = new HashMap&lt;String, Object&gt;();
expressionAttributeValues.put(&quot;:val1&quot;, 25); // update Price to 25...
expressionAttributeValues.put(&quot;:val2&quot;, 20); //...but only if existing Price is 20
UpdateItemOutcome outcome = table.updateItem(
new PrimaryKey(&quot;Id&quot;,101),
&quot;set #P = :val1&quot;, // UpdateExpression
&quot;#P = :val2&quot;,
// ConditionExpression
expressionAttributeNames,
expressionAttributeValues);
Atomic Counter
You can use updateItem to implement an atomic counter, where you increment or decrement the value
of an existing attribute without interfering with other write requests. To increment an atomic counter,
use an UpdateExpression with a set action to add a numeric value to an existing attribute of type
Number.
The following code snippet demonstrates this, incrementing the Quantity attribute by one. It also
demonstrates the use of the ExpressionAttributeNames parameter in an UpdateExpression.
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Table table = dynamoDB.getTable(&quot;ProductCatalog&quot;);
Map&lt;String,String&gt; expressionAttributeNames = new HashMap&lt;String,String&gt;();
expressionAttributeNames.put(&quot;#p&quot;, &quot;PageCount&quot;);
Map&lt;String,Object&gt; expressionAttributeValues = new HashMap&lt;String,Object&gt;();
expressionAttributeValues.put(&quot;:val&quot;, 1);
UpdateItemOutcome outcome = table.updateItem(
&quot;Id&quot;, 121,
&quot;set #p = #p + :val&quot;,
expressionAttributeNames,
expressionAttributeValues);
Deleting an Item
The deleteItem method deletes an item from a table. You must provide the primary key of the item you
want to delete.
Follow these steps:
1. Create an instance of the DynamoDB client.
2. Call the deleteItem method by providing the key of the item you want to delete.
The following Java code snippet demonstrates these tasks.
Example
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
DynamoDB dynamoDB = new DynamoDB(client);
Table table = dynamoDB.getTable(&quot;ProductCatalog&quot;);
DeleteItemOutcome outcome = table.deleteItem(&quot;Id&quot;, 101);
Specifying Optional Parameters
You can specify optional parameters for deleteItem. For example, the following Java code snippet
speciﬁes includes a ConditionExpression, stating that a book item in ProductCatalog can only be
deleted if the book is no longer in publication (the InPublication attribute is false).
Example
Map&lt;String,Object&gt; expressionAttributeValues = new HashMap&lt;String,Object&gt;();
expressionAttributeValues.put(&quot;:val&quot;, false);
DeleteItemOutcome outcome = table.deleteItem(&quot;Id&quot;,103,
&quot;InPublication = :val&quot;,
null, // ExpressionAttributeNames - not used in this example
expressionAttributeValues);
Example: CRUD Operations Using the AWS SDK for Java
Document API
The following code sample illustrates CRUD operations on an item. The example creates an item,
retrieves it, performs various updates, and ﬁnally deletes the item.
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Note
The SDK for Java also provides an object persistence model, allowing you to map your clientside classes to DynamoDB tables. This approach can reduce the amount of code you have to
write. For more information, see Java: DynamoDBMapper (p. 195).
Note
This code sample assumes that you have already loaded data into DynamoDB for your account
by following the instructions in the Creating Tables and Loading Sample Data (p. 280) section.
For step-by-step instructions to run the following example, see Java Code Samples (p. 285).
// Copyright 2012-2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
// Licensed under the Apache License, Version 2.0.
package com.amazonaws.codesamples.document;
import
import
import
import
import
java.io.IOException;
java.util.Arrays;
java.util.HashMap;
java.util.HashSet;
java.util.Map;
import
import
import
import
import
import
import
import
import
import
import
import
com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
com.amazonaws.services.dynamodbv2.document.DeleteItemOutcome;
com.amazonaws.services.dynamodbv2.document.DynamoDB;
com.amazonaws.services.dynamodbv2.document.Item;
com.amazonaws.services.dynamodbv2.document.Table;
com.amazonaws.services.dynamodbv2.document.UpdateItemOutcome;
com.amazonaws.services.dynamodbv2.document.spec.DeleteItemSpec;
com.amazonaws.services.dynamodbv2.document.spec.UpdateItemSpec;
com.amazonaws.services.dynamodbv2.document.utils.NameMap;
com.amazonaws.services.dynamodbv2.document.utils.ValueMap;
com.amazonaws.services.dynamodbv2.model.ReturnValue;
public class DocumentAPIItemCRUDExample {
static AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
static DynamoDB dynamoDB = new DynamoDB(client);
static String tableName = &quot;ProductCatalog&quot;;
public static void main(String[] args) throws IOException {
createItems();
retrieveItem();
// Perform various updates.
updateMultipleAttributes();
updateAddNewAttribute();
updateExistingAttributeConditionally();
// Delete the item.
deleteItem();
}
private static void createItems() {
Table table = dynamoDB.getTable(tableName);
try {
Title&quot;)
Item item = new Item().withPrimaryKey(&quot;Id&quot;, 120).withString(&quot;Title&quot;, &quot;Book 120
.withString(&quot;ISBN&quot;, &quot;120-1111111111&quot;)
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&quot;Author22&quot;)))
.withStringSet(&quot;Authors&quot;, new HashSet&lt;String&gt;(Arrays.asList(&quot;Author12&quot;,
.withNumber(&quot;Price&quot;, 20).withString(&quot;Dimensions&quot;,
&quot;8.5x11.0x.75&quot;).withNumber(&quot;PageCount&quot;, 500)
.withBoolean(&quot;InPublication&quot;, false).withString(&quot;ProductCategory&quot;, &quot;Book&quot;);
table.putItem(item);
item = new Item().withPrimaryKey(&quot;Id&quot;, 121).withString(&quot;Title&quot;, &quot;Book 121
Title&quot;)
&quot;Author 22&quot;)))
.withString(&quot;ISBN&quot;, &quot;121-1111111111&quot;)
.withStringSet(&quot;Authors&quot;, new HashSet&lt;String&gt;(Arrays.asList(&quot;Author21&quot;,
.withNumber(&quot;Price&quot;, 20).withString(&quot;Dimensions&quot;,
&quot;8.5x11.0x.75&quot;).withNumber(&quot;PageCount&quot;, 500)
.withBoolean(&quot;InPublication&quot;, true).withString(&quot;ProductCategory&quot;, &quot;Book&quot;);
table.putItem(item);
}
catch (Exception e) {
System.err.println(&quot;Create items failed.&quot;);
System.err.println(e.getMessage());
}
}
private static void retrieveItem() {
Table table = dynamoDB.getTable(tableName);
try {
Item item = table.getItem(&quot;Id&quot;, 120, &quot;Id, ISBN, Title, Authors&quot;, null);
System.out.println(&quot;Printing item after retrieving it....&quot;);
System.out.println(item.toJSONPretty());
}
catch (Exception e) {
System.err.println(&quot;GetItem failed.&quot;);
System.err.println(e.getMessage());
}
}
private static void updateAddNewAttribute() {
Table table = dynamoDB.getTable(tableName);
try {
UpdateItemSpec updateItemSpec = new UpdateItemSpec().withPrimaryKey(&quot;Id&quot;, 121)
.withUpdateExpression(&quot;set #na = :val1&quot;).withNameMap(new
NameMap().with(&quot;#na&quot;, &quot;NewAttribute&quot;))
.withValueMap(new ValueMap().withString(&quot;:val1&quot;, &quot;Some
value&quot;)).withReturnValues(ReturnValue.ALL_NEW);
UpdateItemOutcome outcome = table.updateItem(updateItemSpec);
// Check the response.
System.out.println(&quot;Printing item after adding new attribute...&quot;);
System.out.println(outcome.getItem().toJSONPretty());
}
}
catch (Exception e) {
System.err.println(&quot;Failed to add new attribute in &quot; + tableName);
System.err.println(e.getMessage());
}
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private static void updateMultipleAttributes() {
Table table = dynamoDB.getTable(tableName);
try {
UpdateItemSpec updateItemSpec = new UpdateItemSpec().withPrimaryKey(&quot;Id&quot;, 120)
.withUpdateExpression(&quot;add #a :val1 set #na=:val2&quot;)
.withNameMap(new NameMap().with(&quot;#a&quot;, &quot;Authors&quot;).with(&quot;#na&quot;,
&quot;NewAttribute&quot;))
.withValueMap(
new ValueMap().withStringSet(&quot;:val1&quot;, &quot;Author YY&quot;, &quot;Author
ZZ&quot;).withString(&quot;:val2&quot;, &quot;someValue&quot;))
.withReturnValues(ReturnValue.ALL_NEW);
UpdateItemOutcome outcome = table.updateItem(updateItemSpec);
// Check the response.
System.out.println(&quot;Printing item after multiple attribute update...&quot;);
System.out.println(outcome.getItem().toJSONPretty());
}
catch (Exception e) {
System.err.println(&quot;Failed to update multiple attributes in &quot; + tableName);
System.err.println(e.getMessage());
}
}
private static void updateExistingAttributeConditionally() {
Table table = dynamoDB.getTable(tableName);
try {
// Specify the desired price (25.00) and also the condition (price =
// 20.00)
= :val1&quot;)
UpdateItemSpec updateItemSpec = new UpdateItemSpec().withPrimaryKey(&quot;Id&quot;, 120)
.withReturnValues(ReturnValue.ALL_NEW).withUpdateExpression(&quot;set #p
.withConditionExpression(&quot;#p = :val2&quot;).withNameMap(new NameMap().with(&quot;#p&quot;,
&quot;Price&quot;))
.withValueMap(new ValueMap().withNumber(&quot;:val1&quot;, 25).withNumber(&quot;:val2&quot;,
20));
UpdateItemOutcome outcome = table.updateItem(updateItemSpec);
// Check the response.
System.out.println(&quot;Printing item after conditional update to new
attribute...&quot;);
System.out.println(outcome.getItem().toJSONPretty());
}
}
catch (Exception e) {
System.err.println(&quot;Error updating item in &quot; + tableName);
System.err.println(e.getMessage());
}
private static void deleteItem() {
Table table = dynamoDB.getTable(tableName);
try {
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DeleteItemSpec deleteItemSpec = new DeleteItemSpec().withPrimaryKey(&quot;Id&quot;, 120)
.withConditionExpression(&quot;#ip = :val&quot;).withNameMap(new
NameMap().with(&quot;#ip&quot;, &quot;InPublication&quot;))
.withValueMap(new ValueMap().withBoolean(&quot;:val&quot;,
false)).withReturnValues(ReturnValue.ALL_OLD);
DeleteItemOutcome outcome = table.deleteItem(deleteItemSpec);
// Check the response.
System.out.println(&quot;Printing item that was deleted...&quot;);
System.out.println(outcome.getItem().toJSONPretty());
}
}
}
catch (Exception e) {
System.err.println(&quot;Error deleting item in &quot; + tableName);
System.err.println(e.getMessage());
}
Example: Batch Operations Using AWS SDK for Java Document
API
Topics
• Example: Batch Write Operation Using the AWS SDK for Java Document API (p. 381)
• Example: Batch Get Operation Using the AWS SDK for Java Document API (p. 383)
This section provides examples of batch write and batch get operations using the AWS SDK for Java
Document API.
Note
The SDK for Java also provides an object persistence model, allowing you to map your clientside classes to DynamoDB tables. This approach can reduce the amount of code you have to
write. For more information, see Java: DynamoDBMapper (p. 195).
Example: Batch Write Operation Using the AWS SDK for Java Document API
The following Java code example uses the batchWriteItem method to perform the following put and
delete operations:
• Put one item in the Forum table
• Put one item and delete one item from the Thread table.
You can specify any number of put and delete requests against one or more tables when creating your
batch write request. However, batchWriteItem limits the size of a batch write request and the number
of put and delete operations in a single batch write operation. If your request exceeds these limits, your
request is rejected. If your table does not have suﬃcient provisioned throughput to serve this request,
the unprocessed request items are returned in the response.
The following example checks the response to see if it has any unprocessed request items. If it does,
it loops back and resends the batchWriteItem request with unprocessed items in the request. If you
followed the Creating Tables and Loading Sample Data (p. 280) section, you should already have
created the Forum and Thread tables. You can also create these tables and upload sample data
programmatically. For more information, see Creating Example Tables and Uploading Data Using the
AWS SDK for Java (p. 742).
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For step-by-step instructions to test the following sample, see Java Code Samples (p. 285).
Example
// Copyright 2012-2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
// Licensed under the Apache License, Version 2.0.
package com.amazonaws.codesamples.document;
import
import
import
import
import
java.io.IOException;
java.util.Arrays;
java.util.HashSet;
java.util.List;
java.util.Map;
import
import
import
import
import
import
import
com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
com.amazonaws.services.dynamodbv2.document.BatchWriteItemOutcome;
com.amazonaws.services.dynamodbv2.document.DynamoDB;
com.amazonaws.services.dynamodbv2.document.Item;
com.amazonaws.services.dynamodbv2.document.TableWriteItems;
com.amazonaws.services.dynamodbv2.model.WriteRequest;
public class DocumentAPIBatchWrite {
static AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
static DynamoDB dynamoDB = new DynamoDB(client);
static String forumTableName = &quot;Forum&quot;;
static String threadTableName = &quot;Thread&quot;;
public static void main(String[] args) throws IOException {
writeMultipleItemsBatchWrite();
}
private static void writeMultipleItemsBatchWrite() {
try {
Forum
// Add a new item to Forum
TableWriteItems forumTableWriteItems = new TableWriteItems(forumTableName) //
.withItemsToPut(new Item().withPrimaryKey(&quot;Name&quot;, &quot;Amazon
RDS&quot;).withNumber(&quot;Threads&quot;, 0));
// Add a new item, and delete an existing item, from Thread
// This table has a partition key and range key, so need to specify
// both of them
TableWriteItems threadTableWriteItems = new TableWriteItems(threadTableName)
.withItemsToPut(new Item().withPrimaryKey(&quot;ForumName&quot;, &quot;Amazon RDS&quot;,
&quot;Subject&quot;, &quot;Amazon RDS Thread 1&quot;)
.withString(&quot;Message&quot;, &quot;ElastiCache Thread 1 message&quot;)
.withStringSet(&quot;Tags&quot;, new HashSet&lt;String&gt;(Arrays.asList(&quot;cache&quot;, &quot;inmemory&quot;))))
.withHashAndRangeKeysToDelete(&quot;ForumName&quot;, &quot;Subject&quot;, &quot;Amazon S3&quot;, &quot;S3
Thread 100&quot;);
System.out.println(&quot;Making the request.&quot;);
BatchWriteItemOutcome outcome = dynamoDB.batchWriteItem(forumTableWriteItems,
threadTableWriteItems);
do {
// Check for unprocessed keys which could happen if you exceed
// provisioned throughput
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Map&lt;String, List&lt;WriteRequest&gt;&gt; unprocessedItems =
outcome.getUnprocessedItems();
if (outcome.getUnprocessedItems().size() == 0) {
System.out.println(&quot;No unprocessed items found&quot;);
}
else {
System.out.println(&quot;Retrieving the unprocessed items&quot;);
outcome = dynamoDB.batchWriteItemUnprocessed(unprocessedItems);
}
} while (outcome.getUnprocessedItems().size() &gt; 0);
}
catch (Exception e) {
System.err.println(&quot;Failed to retrieve items: &quot;);
e.printStackTrace(System.err);
}
}
}
Example: Batch Get Operation Using the AWS SDK for Java Document API
The following Java code example uses the batchGetItem method to retrieve multiple items from the
Forum and the Thread tables. The BatchGetItemRequest speciﬁes the table names and a list of keys for
each item to get. The example processes the response by printing the items retrieved.
Note
This code sample assumes that you have already loaded data into DynamoDB for your account
by following the instructions in the Creating Tables and Loading Sample Data (p. 280) section.
For step-by-step instructions to run the following example, see Java Code Samples (p. 285).
Example
// Copyright 2012-2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
// Licensed under the Apache License, Version 2.0.
package com.amazonaws.codesamples.document;
import java.io.IOException;
import java.util.List;
import java.util.Map;
import
import
import
import
import
import
import
com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
com.amazonaws.services.dynamodbv2.document.BatchGetItemOutcome;
com.amazonaws.services.dynamodbv2.document.DynamoDB;
com.amazonaws.services.dynamodbv2.document.Item;
com.amazonaws.services.dynamodbv2.document.TableKeysAndAttributes;
com.amazonaws.services.dynamodbv2.model.KeysAndAttributes;
public class DocumentAPIBatchGet {
static AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
static DynamoDB dynamoDB = new DynamoDB(client);
static String forumTableName = &quot;Forum&quot;;
static String threadTableName = &quot;Thread&quot;;
public static void main(String[] args) throws IOException {
retrieveMultipleItemsBatchGet();
}
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private static void retrieveMultipleItemsBatchGet() {
try {
TableKeysAndAttributes forumTableKeysAndAttributes = new
TableKeysAndAttributes(forumTableName);
// Add a partition key
forumTableKeysAndAttributes.addHashOnlyPrimaryKeys(&quot;Name&quot;, &quot;Amazon S3&quot;, &quot;Amazon
DynamoDB&quot;);
TableKeysAndAttributes threadTableKeysAndAttributes = new
TableKeysAndAttributes(threadTableName);
// Add a partition key and a sort key
threadTableKeysAndAttributes.addHashAndRangePrimaryKeys(&quot;ForumName&quot;, &quot;Subject&quot;,
&quot;Amazon DynamoDB&quot;,
&quot;DynamoDB Thread 1&quot;, &quot;Amazon DynamoDB&quot;, &quot;DynamoDB Thread 2&quot;, &quot;Amazon S3&quot;,
&quot;S3 Thread 1&quot;);
System.out.println(&quot;Making the request.&quot;);
BatchGetItemOutcome outcome =
dynamoDB.batchGetItem(forumTableKeysAndAttributes,
threadTableKeysAndAttributes);
Map&lt;String, KeysAndAttributes&gt; unprocessed = null;
do {
for (String tableName : outcome.getTableItems().keySet()) {
System.out.println(&quot;Items in table &quot; + tableName);
List&lt;Item&gt; items = outcome.getTableItems().get(tableName);
for (Item item : items) {
System.out.println(item.toJSONPretty());
}
}
// Check for unprocessed keys which could happen if you exceed
// provisioned
// throughput or reach the limit on response size.
unprocessed = outcome.getUnprocessedKeys();
if (unprocessed.isEmpty()) {
System.out.println(&quot;No unprocessed keys found&quot;);
}
else {
System.out.println(&quot;Retrieving the unprocessed keys&quot;);
outcome = dynamoDB.batchGetItemUnprocessed(unprocessed);
}
} while (!unprocessed.isEmpty());
}
catch (Exception e) {
System.err.println(&quot;Failed to retrieve items.&quot;);
System.err.println(e.getMessage());
}
}
}
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Example: Handling Binary Type Attributes Using the AWS SDK
for Java Document API
The following Java code example illustrates handling binary type attributes. The example adds an item
to the Reply table. The item includes a binary type attribute (ExtendedMessage) that stores compressed
data. The example then retrieves the item and prints all the attribute values. For illustration, the example
uses the GZIPOutputStream class to compress a sample stream and assign it to the ExtendedMessage
attribute. When the binary attribute is retrieved, it is decompressed using the GZIPInputStream class.
Note
The SDK for Java also provides an object persistence model, allowing you to map your clientside classes to DynamoDB tables. This approach can reduce the amount of code you have to
write. For more information, see Java: DynamoDBMapper (p. 195).
If you followed the Creating Tables and Loading Sample Data (p. 280) section, you should already have
created the Reply table. You can also create this tables programmatically. For more information, see
Creating Example Tables and Uploading Data Using the AWS SDK for Java (p. 742).
For step-by-step instructions to test the following sample, see Java Code Samples (p. 285).
Example
// Copyright 2012-2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
// Licensed under the Apache License, Version 2.0.
package com.amazonaws.codesamples.document;
import
import
import
import
import
import
import
import
import
java.io.ByteArrayInputStream;
java.io.ByteArrayOutputStream;
java.io.IOException;
java.nio.ByteBuffer;
java.text.SimpleDateFormat;
java.util.Date;
java.util.TimeZone;
java.util.zip.GZIPInputStream;
java.util.zip.GZIPOutputStream;
import
import
import
import
import
import
com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
com.amazonaws.services.dynamodbv2.document.DynamoDB;
com.amazonaws.services.dynamodbv2.document.Item;
com.amazonaws.services.dynamodbv2.document.Table;
com.amazonaws.services.dynamodbv2.document.spec.GetItemSpec;
public class DocumentAPIItemBinaryExample {
static AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
static DynamoDB dynamoDB = new DynamoDB(client);
static String tableName = &quot;Reply&quot;;
static SimpleDateFormat dateFormatter = new SimpleDateFormat(&quot;yyyy-MMdd'T'HH:mm:ss.SSS'Z'&quot;);
public static void main(String[] args) throws IOException {
try {
// Format the primary key values
String threadId = &quot;Amazon DynamoDB#DynamoDB Thread 2&quot;;
dateFormatter.setTimeZone(TimeZone.getTimeZone(&quot;UTC&quot;));
String replyDateTime = dateFormatter.format(new Date());
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// Add a new reply with a binary attribute type
createItem(threadId, replyDateTime);
// Retrieve the reply with a binary attribute type
retrieveItem(threadId, replyDateTime);
// clean up by deleting the item
deleteItem(threadId, replyDateTime);
}
{
}
catch (Exception e) {
System.err.println(&quot;Error running the binary attribute type example: &quot; + e);
e.printStackTrace(System.err);
}
public static void createItem(String threadId, String replyDateTime) throws IOException
Table table = dynamoDB.getTable(tableName);
// Craft a long message
String messageInput = &quot;Long message to be compressed in a lengthy forum reply&quot;;
// Compress the long message
ByteBuffer compressedMessage = compressString(messageInput.toString());
table.putItem(new Item().withPrimaryKey(&quot;Id&quot;, threadId).withString(&quot;ReplyDateTime&quot;,
replyDateTime)
.withString(&quot;Message&quot;, &quot;Long message follows&quot;).withBinary(&quot;ExtendedMessage&quot;,
compressedMessage)
.withString(&quot;PostedBy&quot;, &quot;User A&quot;));
}
public static void retrieveItem(String threadId, String replyDateTime) throws
IOException {
Table table = dynamoDB.getTable(tableName);
GetItemSpec spec = new GetItemSpec().withPrimaryKey(&quot;Id&quot;, threadId,
&quot;ReplyDateTime&quot;, replyDateTime)
.withConsistentRead(true);
Item item = table.getItem(spec);
// Uncompress the reply message and print
String uncompressed =
uncompressString(ByteBuffer.wrap(item.getBinary(&quot;ExtendedMessage&quot;)));
System.out.println(&quot;Reply message:\n&quot; + &quot; Id: &quot; + item.getString(&quot;Id&quot;) + &quot;\n&quot; + &quot;
ReplyDateTime: &quot;
+ item.getString(&quot;ReplyDateTime&quot;) + &quot;\n&quot; + &quot; PostedBy: &quot; +
item.getString(&quot;PostedBy&quot;) + &quot;\n&quot; + &quot; Message: &quot;
+ item.getString(&quot;Message&quot;) + &quot;\n&quot; + &quot; ExtendedMessage (uncompressed): &quot; +
uncompressed + &quot;\n&quot;);
}
public static void deleteItem(String threadId, String replyDateTime) {
}
Table table = dynamoDB.getTable(tableName);
table.deleteItem(&quot;Id&quot;, threadId, &quot;ReplyDateTime&quot;, replyDateTime);
private static ByteBuffer
// Compress the UTF-8
ByteArrayOutputStream
GZIPOutputStream os =
compressString(String input) throws IOException {
encoded String into a byte[]
baos = new ByteArrayOutputStream();
new GZIPOutputStream(baos);
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os.write(input.getBytes(&quot;UTF-8&quot;));
os.close();
baos.close();
byte[] compressedBytes = baos.toByteArray();
}
// The following code writes the compressed bytes to a ByteBuffer.
// A simpler way to do this is by simply calling
// ByteBuffer.wrap(compressedBytes);
// However, the longer form below shows the importance of resetting the
// position of the buffer
// back to the beginning of the buffer if you are writing bytes directly
// to it, since the SDK
// will consider only the bytes after the current position when sending
// data to DynamoDB.
// Using the &quot;wrap&quot; method automatically resets the position to zero.
ByteBuffer buffer = ByteBuffer.allocate(compressedBytes.length);
buffer.put(compressedBytes, 0, compressedBytes.length);
buffer.position(0); // Important: reset the position of the ByteBuffer
// to the beginning
return buffer;
private static String uncompressString(ByteBuffer input) throws IOException {
byte[] bytes = input.array();
ByteArrayInputStream bais = new ByteArrayInputStream(bytes);
ByteArrayOutputStream baos = new ByteArrayOutputStream();
GZIPInputStream is = new GZIPInputStream(bais);
int chunkSize = 1024;
byte[] buffer = new byte[chunkSize];
int length = 0;
while ((length = is.read(buffer, 0, chunkSize)) != -1) {
baos.write(buffer, 0, length);
}
String result = new String(baos.toByteArray(), &quot;UTF-8&quot;);
is.close();
baos.close();
bais.close();
}
}
return result;
Working with Items: .NET
Topics
• Putting an Item (p. 388)
• Getting an Item (p. 389)
• Updating an Item (p. 390)
• Atomic Counter (p. 392)
• Deleting an Item (p. 393)
• Batch Write: Putting and Deleting Multiple Items (p. 394)
• Batch Get: Getting Multiple Items (p. 395)
• Example: CRUD Operations Using the AWS SDK for .NET Low-Level API (p. 398)
• Example: Batch Operations Using AWS SDK for .NET Low-Level API (p. 401)
• Example: Handling Binary Type Attributes Using the AWS SDK for .NET Low-Level API (p. 407)
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You can use the AWS SDK for .NET low-level API to perform typical create, read, update, and delete
(CRUD) operations on an item in a table.
The following are the common steps you follow to perform data CRUD operations using the .NET lowlevel API.
1. Create an instance of the AmazonDynamoDBClient class (the client).
2. Provide the operation speciﬁc required parameters in a corresponding request object.
For example, use the PutItemRequest request object when uploading an item and use the
GetItemRequest request object when retrieving an existing item.
You can use the request object to provide both the required and optional parameters.
3. Execute the appropriate method provided by the client by passing in the request object that you
created in the preceding step.
The AmazonDynamoDBClient client provides PutItem, GetItem, UpdateItem, and DeleteItem methods
for the CRUD operations.
Putting an Item
The PutItem method uploads an item to a table. If the item exists, it replaces the entire item.
Note
Instead of replacing the entire item, if you want to update only speciﬁc attributes, you can use
the UpdateItem method. For more information, see Updating an Item (p. 390).
The following are the steps to upload an item using the low-level .NET SDK API.
1. Create an instance of the AmazonDynamoDBClient class.
2. Provide the required parameters by creating an instance of the PutItemRequest class.
To put an item, you must provide the table name and the item.
3. Execute the PutItem method by providing the PutItemRequest object that you created in the
preceding step.
The following C# code snippet demonstrates the preceding steps. The example uploads an item to the
ProductCatalog table.
Example
AmazonDynamoDBClient client = new AmazonDynamoDBClient();
string tableName = &quot;ProductCatalog&quot;;
var request = new PutItemRequest
{
TableName = tableName,
Item = new Dictionary&lt;string, AttributeValue&gt;()
{
{ &quot;Id&quot;, new AttributeValue { N = &quot;201&quot; }},
{ &quot;Title&quot;, new AttributeValue { S = &quot;Book 201 Title&quot; }},
{ &quot;ISBN&quot;, new AttributeValue { S = &quot;11-11-11-11&quot; }},
{ &quot;Price&quot;, new AttributeValue { S = &quot;20.00&quot; }},
{
&quot;Authors&quot;,
new AttributeValue
{ SS = new List&lt;string&gt;{&quot;Author1&quot;, &quot;Author2&quot;}
}
}
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}
};
client.PutItem(request);
In the preceding example, you upload a book item that has the Id, Title, ISBN, and Authors attributes.
Note that Id is a numeric type attribute and all other attributes are of the string type. Authors is a String
set.
Specifying Optional Parameters
You can also provide optional parameters using the PutItemRequest object as shown in the following C#
code snippet. The sample speciﬁes the following optional parameters:
• ExpressionAttributeNames, ExpressionAttributeValues, and ConditionExpression specify that the
item can be replaced only if the existing item has the ISBN attribute with a speciﬁc value.
• ReturnValues parameter to request the old item in the response.
Example
var request = new PutItemRequest
{
TableName = tableName,
Item = new Dictionary&lt;string, AttributeValue&gt;()
{
{ &quot;Id&quot;, new AttributeValue { N = &quot;104&quot; }},
{ &quot;Title&quot;, new AttributeValue { S = &quot;Book 104 Title&quot; }},
{ &quot;ISBN&quot;, new AttributeValue { S = &quot;444-4444444444&quot; }},
{ &quot;Authors&quot;,
new AttributeValue { SS = new List&lt;string&gt;{&quot;Author3&quot;}}}
},
// Optional parameters.
ExpressionAttributeNames = new Dictionary&lt;string,string&gt;()
{
{&quot;#I&quot;, &quot;ISBN&quot;}
},
ExpressionAttributeValues = new Dictionary&lt;string, AttributeValue&gt;()
{
{&quot;:isbn&quot;,new AttributeValue {S = &quot;444-4444444444&quot;}}
},
ConditionExpression = &quot;#I = :isbn&quot;
};
var response = client.PutItem(request);
For more information, see PutItem.
Getting an Item
The GetItem method retrieves an item.
Note
To retrieve multiple items you can use the BatchGetItem method. For more information, see
Batch Get: Getting Multiple Items (p. 395).
The following are the steps to retrieve an existing item using the low-level .NET SDK API.
1. Create an instance of the AmazonDynamoDBClient class.
2. Provide the required parameters by creating an instance of the GetItemRequest class.
To get an item, you must provide the table name and primary key of the item.
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3. Execute the GetItem method by providing the GetItemRequest object that you created in the
preceding step.
The following C# code snippet demonstrates the preceding steps. The example retrieves an item from
the ProductCatalog table.
AmazonDynamoDBClient client = new AmazonDynamoDBClient();
string tableName = &quot;ProductCatalog&quot;;
var request = new GetItemRequest
{
TableName = tableName,
Key = new Dictionary&lt;string,AttributeValue&gt;() { { &quot;Id&quot;, new AttributeValue { N =
&quot;202&quot; } } },
};
var response = client.GetItem(request);
// Check the response.
var result = response.GetItemResult;
var attributeMap = result.Item; // Attribute list in the response.
Specifying Optional Parameters
You can also provide optional parameters using the GetItemRequest object as shown in the following C#
code snippet. The sample speciﬁes the following optional parameters:
• ProjectionExpression parameter to specify the attributes to retrieve.
• ConsistentRead parameter to perform a strongly consistent read. To learn more read consistency, see
Read Consistency (p. 15).
Example
AmazonDynamoDBClient client = new AmazonDynamoDBClient();
string tableName = &quot;ProductCatalog&quot;;
var request = new GetItemRequest
{
TableName = tableName,
Key = new Dictionary&lt;string,AttributeValue&gt;() { { &quot;Id&quot;, new AttributeValue { N =
&quot;202&quot; } } },
// Optional parameters.
ProjectionExpression = &quot;Id, ISBN, Title, Authors&quot;,
ConsistentRead = true
};
var response = client.GetItem(request);
// Check the response.
var result = response.GetItemResult;
var attributeMap = result.Item;
For more information, see GetItem.
Updating an Item
The UpdateItem method updates an existing item if it is present. You can use the UpdateItem operation
to update existing attribute values, add new attributes, or delete attributes from the existing collection.
If the item that has the speciﬁed primary key is not found, it adds a new item.
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The UpdateItem operation uses the following guidelines:
• If the item does not exist, UpdateItem adds a new item using the primary key that is speciﬁed in the
input.
• If the item exists, UpdateItem applies the updates as follows:
• Replaces the existing attribute values by the values in the update
• If the attribute that you provide in the input does not exist, it adds a new attribute to the item.
• If the input attribute is null, it deletes the attribute, if it is present.
• If you use ADD for the Action, you can add values to an existing set (string or number set), or
mathematically add (use a positive number) or subtract (use a negative number) from the existing
numeric attribute value.
Note
The PutItem operation also can perform an update. For more information, see Putting an
Item (p. 388). For example, if you call PutItem to upload an item and the primary key exists,
the PutItem operation replaces the entire item. Note that, if there are attributes in the existing
item and those attributes are not speciﬁed in the input, the PutItem operation deletes those
attributes. However, UpdateItem only updates the speciﬁed input attributes, any other existing
attributes of that item remain unchanged.
The following are the steps to update an existing item using the low-level .NET SDK API.
1. Create an instance of the AmazonDynamoDBClient class.
2. Provide the required parameters by creating an instance of the UpdateItemRequest class.
This is the request object in which you describe all the updates, such as add attributes, update existing
attributes, or delete attributes. To delete an existing attribute, specify the attribute name with null
value.
3. Execute the UpdateItem method by providing the UpdateItemRequest object that you created in the
preceding step.
The following C# code snippet demonstrates the preceding steps. The example updates a book item in
the ProductCatalog table. It adds a new author to the Authors collection, and deletes the existing ISBN
attribute. It also reduces the price by one.
AmazonDynamoDBClient client = new AmazonDynamoDBClient();
string tableName = &quot;ProductCatalog&quot;;
var request = new UpdateItemRequest
{
TableName = tableName,
Key = new Dictionary&lt;string,AttributeValue&gt;() { { &quot;Id&quot;, new AttributeValue { N =
&quot;202&quot; } } },
ExpressionAttributeNames = new Dictionary&lt;string,string&gt;()
{
{&quot;#A&quot;, &quot;Authors&quot;},
{&quot;#P&quot;, &quot;Price&quot;},
{&quot;#NA&quot;, &quot;NewAttribute&quot;},
{&quot;#I&quot;, &quot;ISBN&quot;}
},
ExpressionAttributeValues = new Dictionary&lt;string, AttributeValue&gt;()
{
{&quot;:auth&quot;,new AttributeValue { SS = {&quot;Author YY&quot;,&quot;Author ZZ&quot;}}},
{&quot;:p&quot;,new AttributeValue {N = &quot;1&quot;}},
{&quot;:newattr&quot;,new AttributeValue {S = &quot;someValue&quot;}},
},
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// This expression does the following:
// 1) Adds two new authors to the list
// 2) Reduces the price
// 3) Adds a new attribute to the item
// 4) Removes the ISBN attribute from the item
UpdateExpression = &quot;ADD #A :auth SET #P = #P - :p, #NA = :newattr REMOVE #I&quot;
};
var response = client.UpdateItem(request);
Specifying Optional Parameters
You can also provide optional parameters using the UpdateItemRequest object as shown in the following
C# code snippet. It speciﬁes the following optional parameters:
• ExpressionAttributeValues and ConditionExpression to specify that the price can be updated only if
the existing price is 20.00.
• ReturnValues parameter to request the updated item in the response.
Example
AmazonDynamoDBClient client = new AmazonDynamoDBClient();
string tableName = &quot;ProductCatalog&quot;;
var request = new UpdateItemRequest
{
Key = new Dictionary&lt;string,AttributeValue&gt;() { { &quot;Id&quot;, new AttributeValue { N =
&quot;202&quot; } } },
};
// Update price only if the current price is 20.00.
ExpressionAttributeNames = new Dictionary&lt;string,string&gt;()
{
{&quot;#P&quot;, &quot;Price&quot;}
},
ExpressionAttributeValues = new Dictionary&lt;string, AttributeValue&gt;()
{
{&quot;:newprice&quot;,new AttributeValue {N = &quot;22&quot;}},
{&quot;:currprice&quot;,new AttributeValue {N = &quot;20&quot;}}
},
UpdateExpression = &quot;SET #P = :newprice&quot;,
ConditionExpression = &quot;#P = :currprice&quot;,
TableName = tableName,
ReturnValues = &quot;ALL_NEW&quot; // Return all the attributes of the updated item.
var response = client.UpdateItem(request);
For more information, see UpdateItem.
Atomic Counter
You can use updateItem to implement an atomic counter, where you increment or decrement the value
of an existing attribute without interfering with other write requests. To update an atomic counter, use
updateItem with an attribute of type Number in the UpdateExpression parameter, and ADD as the Action.
The following code snippet demonstrates this, incrementing the Quantity attribute by one.
AmazonDynamoDBClient client = new AmazonDynamoDBClient();
string tableName = &quot;ProductCatalog&quot;;
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var request = new UpdateItemRequest
{
Key = new Dictionary&lt;string, AttributeValue&gt;() { { &quot;Id&quot;, new AttributeValue { N =
&quot;121&quot; } } },
ExpressionAttributeNames = new Dictionary&lt;string, string&gt;()
{
{&quot;#Q&quot;, &quot;Quantity&quot;}
},
ExpressionAttributeValues = new Dictionary&lt;string, AttributeValue&gt;()
{
{&quot;:incr&quot;,new AttributeValue {N = &quot;1&quot;}}
},
UpdateExpression = &quot;SET #Q = #Q + :incr&quot;,
TableName = tableName
};
var response = client.UpdateItem(request);
Deleting an Item
The DeleteItem method deletes an item from a table.
The following are the steps to delete an item using the low-level .NET SDK API.
1. Create an instance of the AmazonDynamoDBClient class.
2. Provide the required parameters by creating an instance of the DeleteItemRequest class.
To delete an item, the table name and item's primary key are required.
3. Execute the DeleteItem method by providing the DeleteItemRequest object that you created in the
preceding step.
Example
AmazonDynamoDBClient client = new AmazonDynamoDBClient();
string tableName = &quot;ProductCatalog&quot;;
var request = new DeleteItemRequest
{
TableName = tableName,
Key = new Dictionary&lt;string,AttributeValue&gt;() { { &quot;Id&quot;, new AttributeValue { N =
&quot;201&quot; } } },
};
var response = client.DeleteItem(request);
Specifying Optional Parameters
You can also provide optional parameters using the DeleteItemRequest object as shown in the following
C# code snippet. It speciﬁes the following optional parameters:
• ExpressionAttributeValues and ConditionExpression to specify that the book item can be deleted
only if it is no longer in publication (the InPublication attribute value is false).
• ReturnValues parameter to request the deleted item in the response.
Example
var request = new DeleteItemRequest
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{
TableName = tableName,
Key = new Dictionary&lt;string,AttributeValue&gt;() { { &quot;Id&quot;, new AttributeValue { N =
&quot;201&quot; } } },
};
// Optional parameters.
ReturnValues = &quot;ALL_OLD&quot;,
ExpressionAttributeNames = new Dictionary&lt;string, string&gt;()
{
{&quot;#IP&quot;, &quot;InPublication&quot;}
},
ExpressionAttributeValues = new Dictionary&lt;string, AttributeValue&gt;()
{
{&quot;:inpub&quot;,new AttributeValue {BOOL = false}}
},
ConditionExpression = &quot;#IP = :inpub&quot;
var response = client.DeleteItem(request);
For more information, see DeleteItem.
Batch Write: Putting and Deleting Multiple Items
Batch write refers to putting and deleting multiple items in a batch. The BatchWriteItem method
enables you to put and delete multiple items from one or more tables in a single call. The following are
the steps to retrieve multiple items using the low-level .NET SDK API.
1. Create an instance of the AmazonDynamoDBClient class.
2. Describe all the put and delete operations by creating an instance of the BatchWriteItemRequest
class.
3. Execute the BatchWriteItem method by providing the BatchWriteItemRequest object that you created
in the preceding step.
4. Process the response. You should check if there were any unprocessed request items returned in the
response. This could happen if you reach the provisioned throughput limit or some other transient
error. Also, DynamoDB limits the request size and the number of operations you can specify in
a request. If you exceed these limits, DynamoDB rejects the request. For more information, see
BatchWriteItem.
The following C# code snippet demonstrates the preceding steps. The example creates a
BatchWriteItemRequest to perform the following write operations:
• Put an item in Forum table
• Put and delete an item from Thread table
The code then executes BatchWriteItem to perform a batch operation.
AmazonDynamoDBClient client = new AmazonDynamoDBClient();
string table1Name = &quot;Forum&quot;;
string table2Name = &quot;Thread&quot;;
var request = new BatchWriteItemRequest
{
RequestItems = new Dictionary&lt;string, List&lt;WriteRequest&gt;&gt;
{
{
table1Name, new List&lt;WriteRequest&gt;
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{
new WriteRequest
{
PutRequest = new PutRequest
{
Item = new Dictionary&lt;string,AttributeValue&gt;
{
{ &quot;Name&quot;, new AttributeValue { S = &quot;Amazon S3 forum&quot; } },
{ &quot;Threads&quot;, new AttributeValue { N = &quot;0&quot; }}
}
}
}
}
} ,
{
table2Name, new List&lt;WriteRequest&gt;
{
new WriteRequest
{
PutRequest = new PutRequest
{
Item = new Dictionary&lt;string,AttributeValue&gt;
{
{ &quot;ForumName&quot;, new AttributeValue { S = &quot;Amazon S3 forum&quot; } },
{ &quot;Subject&quot;, new AttributeValue { S = &quot;My sample question&quot; } },
{ &quot;Message&quot;, new AttributeValue { S = &quot;Message Text.&quot; } },
{ &quot;KeywordTags&quot;, new AttributeValue { SS = new List&lt;string&gt; { &quot;Amazon S3&quot;,
&quot;Bucket&quot; } } }
}
}
},
new WriteRequest
{
DeleteRequest = new DeleteRequest
{
Key = new Dictionary&lt;string,AttributeValue&gt;()
{
{ &quot;ForumName&quot;, new AttributeValue { S = &quot;Some forum name&quot; } },
{ &quot;Subject&quot;, new AttributeValue { S = &quot;Some subject&quot; } }
}
}
}
}
}
}
};
response = client.BatchWriteItem(request);
For a working example, see Example: Batch Operations Using AWS SDK for .NET Low-Level API (p. 401).
Batch Get: Getting Multiple Items
The BatchGetItem method enables you to retrieve multiple items from one or more tables.
Note
To retrieve a single item you can use the GetItem method.
The following are the steps to retrieve multiple items using the low-level .NET SDK API.
1. Create an instance of the AmazonDynamoDBClient class.
2. Provide the required parameters by creating an instance of the BatchGetItemRequest class.
To retrieve multiple items, the table name and a list of primary key values are required.
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3. Execute the BatchGetItem method by providing the BatchGetItemRequest object that you created in
the preceding step.
4. Process the response. You should check if there were any unprocessed keys, which could happen if you
reach the provisioned throughput limit or some other transient error.
The following C# code snippet demonstrates the preceding steps. The example retrieves items from two
tables, Forum and Thread. The request speciﬁes two items in the Forum and three items in the Thread
table. The response includes items from both of the tables. The code shows how you can process the
response.
AmazonDynamoDBClient client = new AmazonDynamoDBClient();
string table1Name = &quot;Forum&quot;;
string table2Name = &quot;Thread&quot;;
var request = new BatchGetItemRequest
{
RequestItems = new Dictionary&lt;string, KeysAndAttributes&gt;()
{
{ table1Name,
new KeysAndAttributes
{
Keys = new List&lt;Dictionary&lt;string, AttributeValue&gt;&gt;()
{
new Dictionary&lt;string, AttributeValue&gt;()
{
{ &quot;Name&quot;, new AttributeValue { S = &quot;DynamoDB&quot; } }
},
new Dictionary&lt;string, AttributeValue&gt;()
{
{ &quot;Name&quot;, new AttributeValue { S = &quot;Amazon S3&quot; } }
}
}
}
},
{
table2Name,
new KeysAndAttributes
{
Keys = new List&lt;Dictionary&lt;string, AttributeValue&gt;&gt;()
{
new Dictionary&lt;string, AttributeValue&gt;()
{
{ &quot;ForumName&quot;, new AttributeValue { S = &quot;DynamoDB&quot; } },
{ &quot;Subject&quot;, new AttributeValue { S = &quot;DynamoDB Thread 1&quot; } }
},
new Dictionary&lt;string, AttributeValue&gt;()
{
{ &quot;ForumName&quot;, new AttributeValue { S = &quot;DynamoDB&quot; } },
{ &quot;Subject&quot;, new AttributeValue { S = &quot;DynamoDB Thread 2&quot; } }
},
new Dictionary&lt;string, AttributeValue&gt;()
{
{ &quot;ForumName&quot;, new AttributeValue { S = &quot;Amazon S3&quot; } },
{ &quot;Subject&quot;, new AttributeValue { S = &quot;Amazon S3 Thread 1&quot; } }
}
}
}
}
}
};
var response = client.BatchGetItem(request);
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// Check the response.
var result = response.BatchGetItemResult;
var responses = result.Responses; // The attribute list in the response.
var table1Results = responses[table1Name];
Console.WriteLine(&quot;Items in table {0}&quot; + table1Name);
foreach (var item1 in table1Results.Items)
{
PrintItem(item1);
}
var table2Results = responses[table2Name];
Console.WriteLine(&quot;Items in table {1}&quot; + table2Name);
foreach (var item2 in table2Results.Items)
{
PrintItem(item2);
}
// Any unprocessed keys? could happen if you exceed ProvisionedThroughput or some other
error.
Dictionary&lt;string, KeysAndAttributes&gt; unprocessedKeys = result.UnprocessedKeys;
foreach (KeyValuePair&lt;string, KeysAndAttributes&gt; pair in unprocessedKeys)
{
Console.WriteLine(pair.Key, pair.Value);
}
Specifying Optional Parameters
You can also provide optional parameters using the BatchGetItemRequest object as shown in the
following C# code snippet. The code samples retrieves two items from the Forum table. It speciﬁes the
following optional parameter:
• ProjectionExpression parameter to specify the attributes to retrieve.
Example
AmazonDynamoDBClient client = new AmazonDynamoDBClient();
string table1Name = &quot;Forum&quot;;
var request = new BatchGetItemRequest
{
RequestItems = new Dictionary&lt;string, KeysAndAttributes&gt;()
{
{ table1Name,
new KeysAndAttributes
{
Keys = new List&lt;Dictionary&lt;string, AttributeValue&gt;&gt;()
{
new Dictionary&lt;string, AttributeValue&gt;()
{
{ &quot;Name&quot;, new AttributeValue { S = &quot;DynamoDB&quot; } }
},
new Dictionary&lt;string, AttributeValue&gt;()
{
{ &quot;Name&quot;, new AttributeValue { S = &quot;Amazon S3&quot; } }
}
}
},
// Optional - name of an attribute to retrieve.
ProjectionExpression = &quot;Title&quot;
}
}
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};
var response = client.BatchGetItem(request);
For more information, see BatchGetItem.
Example: CRUD Operations Using the AWS SDK for .NET LowLevel API
The following C# code example illustrates CRUD operations on an item. The example adds an item to the
ProductCatalog table, retrieves it, performs various updates, and ﬁnally deletes the item. If you followed
the steps in Creating Tables and Loading Sample Data (p. 280), you already have the ProductCatalog
table created. You can also create these sample tables programmatically. For more information, see
Creating Example Tables and Uploading Data Using the AWS SDK for .NET (p. 749).
For step-by-step instructions to test the following sample, see .NET Code Samples (p. 287).
Example
using
using
using
using
using
using
System;
System.Collections.Generic;
Amazon.DynamoDBv2;
Amazon.DynamoDBv2.Model;
Amazon.Runtime;
Amazon.SecurityToken;
namespace com.amazonaws.codesamples
{
class LowLevelItemCRUDExample
{
private static string tableName = &quot;ProductCatalog&quot;;
private static AmazonDynamoDBClient client = new AmazonDynamoDBClient();
static void Main(string[] args)
{
try
{
CreateItem();
RetrieveItem();
// Perform various updates.
UpdateMultipleAttributes();
UpdateExistingAttributeConditionally();
// Delete item.
DeleteItem();
Console.WriteLine(&quot;To continue, press Enter&quot;);
Console.ReadLine();
}
}
catch (Exception e)
{
Console.WriteLine(e.Message);
Console.WriteLine(&quot;To continue, press Enter&quot;);
Console.ReadLine();
}
private static void CreateItem()
{
var request = new PutItemRequest
{
TableName = tableName,
Item = new Dictionary&lt;string, AttributeValue&gt;()
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{
}
{ &quot;Id&quot;, new AttributeValue {
N = &quot;1000&quot;
}},
{ &quot;Title&quot;, new AttributeValue {
S = &quot;Book 201 Title&quot;
}},
{ &quot;ISBN&quot;, new AttributeValue {
S = &quot;11-11-11-11&quot;
}},
{ &quot;Authors&quot;, new AttributeValue {
SS = new List&lt;string&gt;{&quot;Author1&quot;, &quot;Author2&quot; }
}},
{ &quot;Price&quot;, new AttributeValue {
N = &quot;20.00&quot;
}},
{ &quot;Dimensions&quot;, new AttributeValue {
S = &quot;8.5x11.0x.75&quot;
}},
{ &quot;InPublication&quot;, new AttributeValue {
BOOL = false
} }
}
};
client.PutItem(request);
private static void RetrieveItem()
{
var request = new GetItemRequest
{
TableName = tableName,
Key = new Dictionary&lt;string, AttributeValue&gt;()
{
{ &quot;Id&quot;, new AttributeValue {
N = &quot;1000&quot;
} }
},
ProjectionExpression = &quot;Id, ISBN, Title, Authors&quot;,
ConsistentRead = true
};
var response = client.GetItem(request);
}
// Check the response.
var attributeList = response.Item; // attribute list in the response.
Console.WriteLine(&quot;\nPrinting item after retrieving it ............&quot;);
PrintItem(attributeList);
private static void UpdateMultipleAttributes()
{
var request = new UpdateItemRequest
{
Key = new Dictionary&lt;string, AttributeValue&gt;()
{
{ &quot;Id&quot;, new AttributeValue {
N = &quot;1000&quot;
} }
},
// Perform the following updates:
// 1) Add two new authors to the list
// 1) Set a new attribute
// 2) Remove the ISBN attribute
ExpressionAttributeNames = new Dictionary&lt;string, string&gt;()
{
{&quot;#A&quot;,&quot;Authors&quot;},
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},
{
},
{&quot;#NA&quot;,&quot;NewAttribute&quot;},
{&quot;#I&quot;,&quot;ISBN&quot;}
ExpressionAttributeValues = new Dictionary&lt;string, AttributeValue&gt;()
{&quot;:auth&quot;,new AttributeValue {
SS = {&quot;Author YY&quot;, &quot;Author ZZ&quot;}
}},
{&quot;:new&quot;,new AttributeValue {
S = &quot;New Value&quot;
}}
UpdateExpression = &quot;ADD #A :auth SET #NA = :new REMOVE #I&quot;,
TableName = tableName,
ReturnValues = &quot;ALL_NEW&quot; // Give me all attributes of the updated item.
};
var response = client.UpdateItem(request);
// Check the response.
var attributeList = response.Attributes; // attribute list in the response.
// print attributeList.
Console.WriteLine(&quot;\nPrinting item after multiple attribute
update ............&quot;);
PrintItem(attributeList);
}
private static void UpdateExistingAttributeConditionally()
{
var request = new UpdateItemRequest
{
Key = new Dictionary&lt;string, AttributeValue&gt;()
{
{ &quot;Id&quot;, new AttributeValue {
N = &quot;1000&quot;
} }
},
ExpressionAttributeNames = new Dictionary&lt;string, string&gt;()
{
{&quot;#P&quot;, &quot;Price&quot;}
},
ExpressionAttributeValues = new Dictionary&lt;string, AttributeValue&gt;()
{
{&quot;:newprice&quot;,new AttributeValue {
N = &quot;22.00&quot;
}},
{&quot;:currprice&quot;,new AttributeValue {
N = &quot;20.00&quot;
}}
},
// This updates price only if current price is 20.00.
UpdateExpression = &quot;SET #P = :newprice&quot;,
ConditionExpression = &quot;#P = :currprice&quot;,
TableName = tableName,
ReturnValues = &quot;ALL_NEW&quot; // Give me all attributes of the updated item.
};
var response = client.UpdateItem(request);
// Check the response.
var attributeList = response.Attributes; // attribute list in the response.
Console.WriteLine(&quot;\nPrinting item after updating price value
conditionally ............&quot;);
PrintItem(attributeList);
}
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private static void DeleteItem()
{
var request = new DeleteItemRequest
{
TableName = tableName,
Key = new Dictionary&lt;string, AttributeValue&gt;()
{
{ &quot;Id&quot;, new AttributeValue {
N = &quot;1000&quot;
} }
},
{
},
{
},
};
// Return the entire item as it appeared before the update.
ReturnValues = &quot;ALL_OLD&quot;,
ExpressionAttributeNames = new Dictionary&lt;string, string&gt;()
{&quot;#IP&quot;, &quot;InPublication&quot;}
ExpressionAttributeValues = new Dictionary&lt;string, AttributeValue&gt;()
{&quot;:inpub&quot;,new AttributeValue {
BOOL = false
}}
ConditionExpression = &quot;#IP = :inpub&quot;
var response = client.DeleteItem(request);
}
// Check the response.
var attributeList = response.Attributes; // Attribute list in the response.
// Print item.
Console.WriteLine(&quot;\nPrinting item that was just deleted ............&quot;);
PrintItem(attributeList);
private static void PrintItem(Dictionary&lt;string, AttributeValue&gt; attributeList)
{
foreach (KeyValuePair&lt;string, AttributeValue&gt; kvp in attributeList)
{
string attributeName = kvp.Key;
AttributeValue value = kvp.Value;
+ &quot;]&quot;) +
+ &quot;]&quot;)
}
}
}
Console.WriteLine(
attributeName + &quot; &quot; +
(value.S == null ? &quot;&quot; : &quot;S=[&quot; + value.S + &quot;]&quot;) +
(value.N == null ? &quot;&quot; : &quot;N=[&quot; + value.N + &quot;]&quot;) +
(value.SS == null ? &quot;&quot; : &quot;SS=[&quot; + string.Join(&quot;,&quot;, value.SS.ToArray())
(value.NS == null ? &quot;&quot; : &quot;NS=[&quot; + string.Join(&quot;,&quot;, value.NS.ToArray())
);
}
Console.WriteLine(&quot;************************************************&quot;);
Example: Batch Operations Using AWS SDK for .NET Low-Level
API
Topics
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• Example: Batch Write Operation Using the AWS SDK for .NET Low-Level API (p. 402)
• Example: Batch Get Operation Using the AWS SDK for .NET Low-Level API (p. 404)
This section provides examples of batch operations, batch write and batch get, that DynamoDB supports.
Example: Batch Write Operation Using the AWS SDK for .NET Low-Level API
The following C# code example uses the BatchWriteItem method to perform the following put and
delete operations:
• Put one item in the Forum table
• Put one item and delete one item from the Thread table.
You can specify any number of put and delete requests against one or more tables when creating your
batch write request. However, DynamoDB BatchWriteItem limits the size of a batch write request and
the number of put and delete operations in a single batch write operation. For more information, see
BatchWriteItem. If your request exceeds these limits, your request is rejected. If your table does not have
suﬃcient provisioned throughput to serve this request, the unprocessed request items are returned in
the response.
The following example checks the response to see if it has any unprocessed request items. If it does,
it loops back and resends the BatchWriteItem request with unprocessed items in the request. If
you followed the steps in Creating Tables and Loading Sample Data (p. 280), you already have the
Forum and Thread tables created. You can also create these sample tables and upload sample data
programmatically. For more information, see Creating Example Tables and Uploading Data Using the
AWS SDK for .NET (p. 749).
For step-by-step instructions to test the following sample, see .NET Code Samples (p. 287).
Example
using
using
using
using
using
System;
System.Collections.Generic;
Amazon.DynamoDBv2;
Amazon.DynamoDBv2.Model;
Amazon.Runtime;
namespace com.amazonaws.codesamples
{
class LowLevelBatchWrite
{
private static string table1Name = &quot;Forum&quot;;
private static string table2Name = &quot;Thread&quot;;
private static AmazonDynamoDBClient client = new AmazonDynamoDBClient();
static void Main(string[] args)
{
try
{
TestBatchWrite();
}
catch (AmazonServiceException e) { Console.WriteLine(e.Message); }
catch (Exception e) { Console.WriteLine(e.Message); }
}
Console.WriteLine(&quot;To continue, press Enter&quot;);
Console.ReadLine();
private static void TestBatchWrite()
{
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var request = new BatchWriteItemRequest
{
ReturnConsumedCapacity = &quot;TOTAL&quot;,
RequestItems = new Dictionary&lt;string, List&lt;WriteRequest&gt;&gt;
{
{
table1Name, new List&lt;WriteRequest&gt;
{
new WriteRequest
{
PutRequest = new PutRequest
{
Item = new Dictionary&lt;string, AttributeValue&gt;
{
{ &quot;Name&quot;, new AttributeValue {
S = &quot;S3 forum&quot;
} },
{ &quot;Threads&quot;, new AttributeValue {
N = &quot;0&quot;
}}
}
}
}
}
},
{
table2Name, new List&lt;WriteRequest&gt;
{
new WriteRequest
{
PutRequest = new PutRequest
{
Item = new Dictionary&lt;string, AttributeValue&gt;
{
{ &quot;ForumName&quot;, new AttributeValue {
S = &quot;S3 forum&quot;
} },
{ &quot;Subject&quot;, new AttributeValue {
S = &quot;My sample question&quot;
} },
{ &quot;Message&quot;, new AttributeValue {
S = &quot;Message Text.&quot;
} },
{ &quot;KeywordTags&quot;, new AttributeValue {
SS = new List&lt;string&gt; { &quot;S3&quot;, &quot;Bucket&quot; }
} }
}
}
},
new WriteRequest
{
// For the operation to delete an item, if you provide a
primary key value
// that does not exist in the table, there is no error, it is
just a no-op.
DeleteRequest = new DeleteRequest
{
Key = new Dictionary&lt;string, AttributeValue&gt;()
{
{ &quot;ForumName&quot;, new AttributeValue {
S = &quot;Some partition key value&quot;
} },
{ &quot;Subject&quot;, new AttributeValue {
S = &quot;Some sort key value&quot;
} }
}
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}
};
}
}
}
}
}
CallBatchWriteTillCompletion(request);
private static void CallBatchWriteTillCompletion(BatchWriteItemRequest request)
{
BatchWriteItemResponse response;
int callCount = 0;
do
{
Console.WriteLine(&quot;Making request&quot;);
response = client.BatchWriteItem(request);
callCount++;
// Check the response.
var tableConsumedCapacities = response.ConsumedCapacity;
var unprocessed = response.UnprocessedItems;
Console.WriteLine(&quot;Per-table consumed capacity&quot;);
foreach (var tableConsumedCapacity in tableConsumedCapacities)
{
Console.WriteLine(&quot;{0} - {1}&quot;, tableConsumedCapacity.TableName,
tableConsumedCapacity.CapacityUnits);
}
Console.WriteLine(&quot;Unprocessed&quot;);
foreach (var unp in unprocessed)
{
Console.WriteLine(&quot;{0} - {1}&quot;, unp.Key, unp.Value.Count);
}
Console.WriteLine();
// For the next iteration, the request will have unprocessed items.
request.RequestItems = unprocessed;
} while (response.UnprocessedItems.Count &gt; 0);
}
}
}
Console.WriteLine(&quot;Total # of batch write API calls made: {0}&quot;, callCount);
Example: Batch Get Operation Using the AWS SDK for .NET Low-Level API
The following C# code example uses the BatchGetItem method to retrieve multiple items from the
Forum and the Thread tables. The BatchGetItemRequest speciﬁes the table names and a list of primary
keys for each table. The example processes the response by printing the items retrieved.
If you followed the steps in Creating Tables and Loading Sample Data (p. 280), you already have these
tables created with sample data. You can also create these sample tables and upload sample data
programmatically. For more information, see Creating Example Tables and Uploading Data Using the
AWS SDK for .NET (p. 749).
For step-by-step instructions to test the following sample, see .NET Code Samples (p. 287).
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Example
using
using
using
using
using
System;
System.Collections.Generic;
Amazon.DynamoDBv2;
Amazon.DynamoDBv2.Model;
Amazon.Runtime;
namespace com.amazonaws.codesamples
{
class LowLevelBatchGet
{
private static string table1Name = &quot;Forum&quot;;
private static string table2Name = &quot;Thread&quot;;
private static AmazonDynamoDBClient client = new AmazonDynamoDBClient();
static void Main(string[] args)
{
try
{
RetrieveMultipleItemsBatchGet();
Console.WriteLine(&quot;To continue, press Enter&quot;);
Console.ReadLine();
}
}
catch (AmazonServiceException e) { Console.WriteLine(e.Message); }
catch (Exception e) { Console.WriteLine(e.Message); }
private static void RetrieveMultipleItemsBatchGet()
{
var request = new BatchGetItemRequest
{
RequestItems = new Dictionary&lt;string, KeysAndAttributes&gt;()
{
{ table1Name,
new KeysAndAttributes
{
Keys = new List&lt;Dictionary&lt;string, AttributeValue&gt; &gt;()
{
new Dictionary&lt;string, AttributeValue&gt;()
{
{ &quot;Name&quot;, new AttributeValue {
S = &quot;Amazon DynamoDB&quot;
} }
},
new Dictionary&lt;string, AttributeValue&gt;()
{
{ &quot;Name&quot;, new AttributeValue {
S = &quot;Amazon S3&quot;
} }
}
}
}},
{
table2Name,
new KeysAndAttributes
{
Keys = new List&lt;Dictionary&lt;string, AttributeValue&gt; &gt;()
{
new Dictionary&lt;string, AttributeValue&gt;()
{
{ &quot;ForumName&quot;, new AttributeValue {
S = &quot;Amazon DynamoDB&quot;
} },
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{ &quot;Subject&quot;, new AttributeValue {
S = &quot;DynamoDB Thread 1&quot;
} }
}
};
}
}
}
},
new Dictionary&lt;string, AttributeValue&gt;()
{
{ &quot;ForumName&quot;, new AttributeValue {
S = &quot;Amazon DynamoDB&quot;
} },
{ &quot;Subject&quot;, new AttributeValue {
S = &quot;DynamoDB Thread 2&quot;
} }
},
new Dictionary&lt;string, AttributeValue&gt;()
{
{ &quot;ForumName&quot;, new AttributeValue {
S = &quot;Amazon S3&quot;
} },
{ &quot;Subject&quot;, new AttributeValue {
S = &quot;S3 Thread 1&quot;
} }
}
BatchGetItemResponse response;
do
{
Console.WriteLine(&quot;Making request&quot;);
response = client.BatchGetItem(request);
// Check the response.
var responses = response.Responses; // Attribute list in the response.
foreach (var tableResponse in responses)
{
var tableResults = tableResponse.Value;
Console.WriteLine(&quot;Items retrieved from table {0}&quot;,
tableResponse.Key);
foreach (var item1 in tableResults)
{
PrintItem(item1);
}
}
// Any unprocessed keys? could happen if you exceed ProvisionedThroughput
or some other error.
Dictionary&lt;string, KeysAndAttributes&gt; unprocessedKeys =
response.UnprocessedKeys;
foreach (var unprocessedTableKeys in unprocessedKeys)
{
// Print table name.
Console.WriteLine(unprocessedTableKeys.Key);
// Print unprocessed primary keys.
foreach (var key in unprocessedTableKeys.Value.Keys)
{
PrintItem(key);
}
}
}
request.RequestItems = unprocessedKeys;
} while (response.UnprocessedKeys.Count &gt; 0);
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private static void PrintItem(Dictionary&lt;string, AttributeValue&gt; attributeList)
{
foreach (KeyValuePair&lt;string, AttributeValue&gt; kvp in attributeList)
{
string attributeName = kvp.Key;
AttributeValue value = kvp.Value;
Console.WriteLine(
attributeName + &quot; &quot; +
(value.S == null ? &quot;&quot; : &quot;S=[&quot; + value.S + &quot;]&quot;) +
(value.N == null ? &quot;&quot; : &quot;N=[&quot; + value.N + &quot;]&quot;) +
(value.SS == null ? &quot;&quot; : &quot;SS=[&quot; + string.Join(&quot;,&quot;, value.SS.ToArray())
+ &quot;]&quot;) +
+ &quot;]&quot;)
}
}
}
(value.NS == null ? &quot;&quot; : &quot;NS=[&quot; + string.Join(&quot;,&quot;, value.NS.ToArray())
);
}
Console.WriteLine(&quot;************************************************&quot;);
Example: Handling Binary Type Attributes Using the AWS SDK
for .NET Low-Level API
The following C# code example illustrates the handling of binary type attributes. The example
adds an item to the Reply table. The item includes a binary type attribute (ExtendedMessage) that
stores compressed data. The example then retrieves the item and prints all the attribute values. For
illustration, the example uses the GZipStream class to compress a sample stream and assigns it to the
ExtendedMessage attribute, and decompresses it when printing the attribute value.
If you followed the steps in Creating Tables and Loading Sample Data (p. 280), you already have the
Reply table created. You can also create these sample tables programmatically. For more information,
see Creating Example Tables and Uploading Data Using the AWS SDK for .NET (p. 749).
For step-by-step instructions to test the following sample, see .NET Code Samples (p. 287).
Example
using
using
using
using
using
using
using
System;
System.Collections.Generic;
System.IO;
System.IO.Compression;
Amazon.DynamoDBv2;
Amazon.DynamoDBv2.Model;
Amazon.Runtime;
namespace com.amazonaws.codesamples
{
class LowLevelItemBinaryExample
{
private static string tableName = &quot;Reply&quot;;
private static AmazonDynamoDBClient client = new AmazonDynamoDBClient();
static void Main(string[] args)
{
// Reply table primary key.
string replyIdPartitionKey = &quot;Amazon DynamoDB#DynamoDB Thread 1&quot;;
string replyDateTimeSortKey = Convert.ToString(DateTime.UtcNow);
try
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{
}
CreateItem(replyIdPartitionKey, replyDateTimeSortKey);
RetrieveItem(replyIdPartitionKey, replyDateTimeSortKey);
// Delete item.
DeleteItem(replyIdPartitionKey, replyDateTimeSortKey);
Console.WriteLine(&quot;To continue, press Enter&quot;);
Console.ReadLine();
}
catch (AmazonDynamoDBException e) { Console.WriteLine(e.Message); }
catch (AmazonServiceException e) { Console.WriteLine(e.Message); }
catch (Exception e) { Console.WriteLine(e.Message); }
private static void CreateItem(string partitionKey, string sortKey)
{
MemoryStream compressedMessage = ToGzipMemoryStream(&quot;Some long extended message
to compress.&quot;);
var request = new PutItemRequest
{
TableName = tableName,
Item = new Dictionary&lt;string, AttributeValue&gt;()
{
{ &quot;Id&quot;, new AttributeValue {
S = partitionKey
}},
{ &quot;ReplyDateTime&quot;, new AttributeValue {
S = sortKey
}},
{ &quot;Subject&quot;, new AttributeValue {
S = &quot;Binary type &quot;
}},
{ &quot;Message&quot;, new AttributeValue {
S = &quot;Some message about the binary type&quot;
}},
{ &quot;ExtendedMessage&quot;, new AttributeValue {
B = compressedMessage
}}
}
};
client.PutItem(request);
}
private static void RetrieveItem(string partitionKey, string sortKey)
{
var request = new GetItemRequest
{
TableName = tableName,
Key = new Dictionary&lt;string, AttributeValue&gt;()
{
{ &quot;Id&quot;, new AttributeValue {
S = partitionKey
} },
{ &quot;ReplyDateTime&quot;, new AttributeValue {
S = sortKey
} }
},
ConsistentRead = true
};
var response = client.GetItem(request);
// Check the response.
var attributeList = response.Item; // attribute list in the response.
Console.WriteLine(&quot;\nPrinting item after retrieving it ............&quot;);
}
PrintItem(attributeList);
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private static void DeleteItem(string partitionKey, string sortKey)
{
var request = new DeleteItemRequest
{
TableName = tableName,
Key = new Dictionary&lt;string, AttributeValue&gt;()
{
{ &quot;Id&quot;, new AttributeValue {
S = partitionKey
} },
{ &quot;ReplyDateTime&quot;, new AttributeValue {
S = sortKey
} }
}
};
var response = client.DeleteItem(request);
}
private static void PrintItem(Dictionary&lt;string, AttributeValue&gt; attributeList)
{
foreach (KeyValuePair&lt;string, AttributeValue&gt; kvp in attributeList)
{
string attributeName = kvp.Key;
AttributeValue value = kvp.Value;
+ &quot;]&quot;) +
+ &quot;]&quot;) +
}
true))
Console.WriteLine(
attributeName + &quot; &quot; +
(value.S == null ? &quot;&quot; : &quot;S=[&quot; + value.S + &quot;]&quot;) +
(value.N == null ? &quot;&quot; : &quot;N=[&quot; + value.N + &quot;]&quot;) +
(value.SS == null ? &quot;&quot; : &quot;SS=[&quot; + string.Join(&quot;,&quot;, value.SS.ToArray())
(value.NS == null ? &quot;&quot; : &quot;NS=[&quot; + string.Join(&quot;,&quot;, value.NS.ToArray())
(value.B == null ? &quot;&quot; : &quot;B=[&quot; + FromGzipMemoryStream(value.B) + &quot;]&quot;)
);
}
Console.WriteLine(&quot;************************************************&quot;);
private static MemoryStream ToGzipMemoryStream(string value)
{
MemoryStream output = new MemoryStream();
using (GZipStream zipStream = new GZipStream(output, CompressionMode.Compress,
}
using (StreamWriter writer = new StreamWriter(zipStream))
{
writer.Write(value);
}
return output;
private static string FromGzipMemoryStream(MemoryStream stream)
{
using (GZipStream zipStream = new GZipStream(stream,
CompressionMode.Decompress))
using (StreamReader reader = new StreamReader(zipStream))
{
return reader.ReadToEnd();
}
}
}
}
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Working with Queries
Working with Queries
Topics
• Key Condition Expression (p. 410)
• Filter Expressions for Query (p. 412)
• Limiting the Number of Items in the Result Set (p. 413)
• Paginating the Results (p. 413)
• Counting the Items in the Results (p. 414)
• Capacity Units Consumed by Query (p. 414)
• Read Consistency for Query (p. 415)
• Querying Tables and Indexes: Java (p. 415)
• Querying Tables and Indexes: .NET (p. 420)
The Query operation ﬁnds items based on primary key values. You can query any table or secondary
index that has a composite primary key (a partition key and a sort key).
You must provide the name of the partition key attribute, and a single value for that attribute.Query will
return all of the items with that partition key value. You can optionally provide a sort key attribute, and
use a comparison operator to reﬁne the search results.
Key Condition Expression
To specify the search criteria, you use a key condition expression—a string that determines the items
to be read from the table or index. You must specify the partition key name and value as an equality
condition. You can optionally provide a second condition for the sort key (if present). The sort key
condition must use one of the following comparison operators:
• a = b — true if the attribute a is equal to the value b
• a &lt; b — true if a is less than b
• a &lt;= b — true if a is less than or equal to b
• a &gt; b — true if a is greater than b
• a &gt;= b — true if a is greater than or equal to b
• a BETWEEN b AND c — true if a is greater than or equal to b, and less than or equal to c.
The following function is also supported:
• begins_with (a, substr)— true if the value of attribute a begins with a particular substring.
The following AWS CLI examples demonstrate the use of key condition expressions. Note that these
expressions use placeholders (such as :name and :sub) instead of actual values. For more information,
see Expression Attribute Names (p. 342) and Expression Attribute Values (p. 345).
Example
Query the Thread table for a particular ForumName (partition key). All of the items with that
ForumName value will be read by the query, because the sort key (Subject) is not included in
KeyConditionExpression.
aws dynamodb query \
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--table-name Thread \
--key-condition-expression &quot;ForumName = :name&quot; \
--expression-attribute-values '{&quot;:name&quot;:{&quot;S&quot;:&quot;Amazon DynamoDB&quot;}}'
Example
Query the Thread table for a particular ForumName (partition key), but this time return only the items
with a given Subject (sort key).
aws dynamodb query \
--table-name Thread \
--key-condition-expression &quot;ForumName = :name and Subject = :sub&quot; \
--expression-attribute-values file://values.json
The arguments for --expression-attribute-values are stored in the ﬁle values.json:
{
}
&quot;:name&quot;:{&quot;S&quot;:&quot;Amazon DynamoDB&quot;},
&quot;:sub&quot;:{&quot;S&quot;:&quot;DynamoDB Thread 1&quot;}
Example
Query the Reply table for a particular Id (partition key), but return only those items whose ReplyDateTime
(sort key) begins with certain characters.
aws dynamodb query \
--table-name Reply \
--key-condition-expression &quot;Id = :id and begins_with(ReplyDateTime, :dt)&quot; \
--expression-attribute-values file://values.json
The arguments for --expression-attribute-values are stored in the ﬁle values.json:
{
}
&quot;:id&quot;:{&quot;S&quot;:&quot;Amazon DynamoDB#DynamoDB Thread 1&quot;},
&quot;:dt&quot;:{&quot;S&quot;:&quot;2015-09&quot;}
You can use any attribute name in a key condition expression, provided that the ﬁrst character is a-z or
A-Z and the second character (if present) is a-z, A-Z, or 0-9. In addition, the attribute name must not be
a DynamoDB reserved word. (For a complete list of these, see Reserved Words in DynamoDB (p. 773).)
If an attribute name does not meet these requirements, you will need to deﬁne an expression attribute
name as a placeholder. For more information, see Expression Attribute Names (p. 342).
For items with a given partition key value, DynamoDB stores these items close together, in sorted
order by sort key value. In a Query operation, DynamoDB retrieves the items in sorted order, and then
processes the items using KeyConditionExpression and any FilterExpression that might be present.
Only then are the Query results sent back to the client.
A Query operation always returns a result set. If no matching items are found, the result set will be
empty.
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Filter Expressions for Query
Query results are always sorted by the sort key value. If the data type of the sort key is Number, the
results are returned in numeric order; otherwise, the results are returned in order of UTF-8 bytes. By
default, the sort order is ascending. To reverse the order, set the ScanIndexForward parameter to false.
A single Query operation can retrieve a maximum of 1 MB of data. This limit applies before any
FilterExpression is applied to the results. If LastEvaluatedKey is present in the response and is nonnull, you will need to paginate the result set (see Paginating the Results (p. 413)).
Filter Expressions for Query
If you need to further reﬁne the Query results, you can optionally provide a ﬁlter expression. A ﬁlter
expression determines which items within the Query results should be returned to you. All of the other
results are discarded.
A ﬁlter expression is applied after a Query ﬁnishes, but before the results are returned. Therefore, a Query
will consume the same amount of read capacity, regardless of whether a ﬁlter expression is present.
A Query operation can retrieve a maximum of 1 MB of data. This limit applies before the ﬁlter expression
is evaluated.
A ﬁlter expression cannot contain partition key or sort key attributes. You need to specify those
attributes in the key condition expression, not the ﬁlter expression.
The syntax for a ﬁlter expression is identical to that of a condition expression. Filter expressions can use
the same comparators, functions, and logical operators as a condition expression. For more information,
Condition Expressions (p. 346).
Example
The following AWS CLI example queries the Thread table for a particular ForumName (partition key) and
Subject (sort key). Of the items that are found, only the most popular discussion threads are returned—in
other words, only those threads with more than a certain number of Views.
aws dynamodb query \
--table-name Thread \
--key-condition-expression &quot;ForumName = :fn&quot; \
--filter-expression &quot;#v &gt;= :num&quot; \
--expression-attribute-names '{&quot;#v&quot;: &quot;Views&quot;}' \
--expression-attribute-values file://values.json
The arguments for --expression-attribute-values are stored in the ﬁle values.json:
{
}
&quot;:fn&quot;:{&quot;S&quot;:&quot;Amazon DynamoDB#DynamoDB Thread 1&quot;},
&quot;:num&quot;:{&quot;N&quot;:&quot;3&quot;}
Note that Views is a reserved word in DynamoDB (see Reserved Words in DynamoDB (p. 773)), so this
example uses #v as a placeholder. For more information, see Expression Attribute Names (p. 342).
Note
A ﬁlter expression removes items from the Query result set. If possible, avoid using Query where
you expect to retrieve a large number of items, but also need to discard most of those items.
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Limiting the Number of Items in the Result Set
Limiting the Number of Items in the Result Set
The Query operation allows you to limit the number of items that it returns in the result. To do this, set
the Limit parameter to the maximum number of items that you want.
For example, suppose you Query a table, with a Limit value of 6, and without a ﬁlter expression. The
Query result will contain the ﬁrst six items from the table that match the key condition expression from
the request.
Now suppose you add a ﬁlter expression to the Query. In this case, DynamoDB will apply the ﬁlter
expression to the six items that were returned, discarding those that do not match. The ﬁnal Query result
will contain 6 items or fewer, depending on the number of items that were ﬁltered.
Paginating the Results
DynamoDB paginates the results from Query operations. With pagination, the Query results are divided
into &quot;pages&quot; of data that are 1 MB in size (or less). An application can process the ﬁrst page of results,
then the second page, and so on.
A single Query will only return a result set that ﬁts within the 1 MB size limit. To determine whether there
are more results, and to retrieve them one page at a time, applications should do the following:
1. Examine the low-level Query result:
• If the result contains a LastEvaluatedKey element, proceed to step 2.
• If there is not a LastEvaluatedKey in the result, then there are no more items to be retrieved.
2. Construct a new Query request, with the same parameters as the previous one—but this time, take the
LastEvaluatedKey value from step 1 and use it as the ExclusiveStartKey parameter in the new Query
request.
3. Run the new Query request.
4. Go to step 1.
In other words, the LastEvaluatedKey from a Query response should be used as the ExclusiveStartKey
for the next Query request. If there is not a LastEvaluatedKey element in a Query response, then you
have retrieved the ﬁnal page of results. (The absence of LastEvaluatedKey is the only way to know that
you have reached the end of the result set.)
You can use the AWS CLI to view this behavior. The CLI sends low-level Query requests to DynamoDB,
repeatedly, until LastEvaluatedKey is no longer present in the results. Consider the following AWS CLI
example that retrieves movie titles from a particular year:
aws dynamodb query --table-name Movies \
--projection-expression &quot;title&quot; \
--key-condition-expression &quot;#y = :yyyy&quot; \
--expression-attribute-names '{&quot;#y&quot;:&quot;year&quot;}' \
--expression-attribute-values '{&quot;:yyyy&quot;:{&quot;N&quot;:&quot;1989&quot;}}' \
--page-size 5 \
--debug
Ordinarily, the AWS CLI handles pagination automatically; however, in this example, the CLI's -page-size parameter limits the number of items per page. The --debug parameter prints low-level
information about requests and responses.
If you run the example, the ﬁrst response from DynamoDB looks similar to this:
2017-07-07 11:13:15,603 - MainThread - botocore.parsers - DEBUG - Response body:
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b'{&quot;Count&quot;:5,&quot;Items&quot;:[{&quot;title&quot;:{&quot;S&quot;:&quot;Always&quot;}},{&quot;title&quot;:{&quot;S&quot;:&quot;Back to the Future Part
II&quot;}},
{&quot;title&quot;:{&quot;S&quot;:&quot;Batman&quot;}},{&quot;title&quot;:{&quot;S&quot;:&quot;Bill &amp; Ted\'s Excellent Adventure&quot;}},{&quot;title&quot;:
{&quot;S&quot;:&quot;Black Rain&quot;}}],
&quot;LastEvaluatedKey&quot;:{&quot;year&quot;:{&quot;N&quot;:&quot;1989&quot;},&quot;title&quot;:{&quot;S&quot;:&quot;Black Rain&quot;}},
&quot;ScannedCount&quot;:5}
The LastEvaluatedKey in the response indicates that not all of the items have been retrieved. The AWS
CLI will then issue another Query request to DynamoDB. This request and response pattern continues,
until the ﬁnal response:
2017-07-07 11:13:16,291 - MainThread - botocore.parsers - DEBUG - Response body:
b'{&quot;Count&quot;:2,&quot;Items&quot;:[{&quot;title&quot;:{&quot;S&quot;:&quot;Uncle Buck&quot;}},{&quot;title&quot;:{&quot;S&quot;:&quot;Weekend at Bernie\'s&quot;}}],
&quot;ScannedCount&quot;:2}'
The absence of LastEvaluatedKey indicates that there are no more items to retrieve.
Note
The AWS SDKs handle the low-level DynamoDB responses (including the presence or absence of
LastEvaluatedKey), and provide various abstractions for paginating Query results. For example,
the SDK for Java document interface provides java.util.Iterator support, so that you can
walk through the results one at a time.
For code samples in various programming languages, see the Amazon DynamoDB Getting
Started Guide and the AWS SDK documentation for your language.
Counting the Items in the Results
In addition to the items that match your criteria, the Query response contains the following elements:
• ScannedCount — the number of items that matched the key condition expression, before a ﬁlter
expression (if present) was applied.
• Count — the number of items that remain, after a ﬁlter expression (if present) was applied.
Note
If you do not use a ﬁlter expression, then ScannedCount and Count will have the same value.
If the size of the Query result set is larger than 1 MB, then ScannedCount and Count will represent only a
partial count of the total items. You will need to perform multiple Query operations in order to retrieve
all of the results (see Paginating the Results (p. 413)).
Each Query response will contain the ScannedCount and Count for the items that were processed by that
particular Query request. To obtain grand totals for all of the Query requests, you could keep a running
tally of both ScannedCount and Count.
Capacity Units Consumed by Query
You can Query any table or secondary index, provided that it has a composite primary key (partition key
and sort key). Query operations consume read capacity units, as follows:
If you Query a...
DynamoDB consumes read capacity units from...
Table
The table's provisioned read capacity.
Global secondary index
The index's provisioned read capacity.
Local secondary index
The base table's provisioned read capacity.
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Read Consistency for Query
By default, a Query operation does not return any data on how much read capacity it consumes.
However, you can specify the ReturnConsumedCapacity parameter in a Query request to obtain this
information. The following are the valid settings for ReturnConsumedCapacity:
• NONE—no consumed capacity data is returned. (This is the default.)
• TOTAL—the response includes the aggregate number of read capacity units consumed.
• INDEXES—the response shows the aggregate number of read capacity units consumed, together with
the consumed capacity for each table and index that was accessed.
DynamoDB calculates the number of read capacity units consumed based on item size, not on the
amount of data that is returned to an application. For this reason, the number of capacity units
consumed will be the same whether you request all of the attributes (the default behavior) or just some
of them (using a projection expression). The number will also be the same whether or not you use a ﬁlter
expression.
Read Consistency for Query
A Query operation performs eventually consistent reads, by default. This means that the Query results
might not reﬂect changes due to recently completed PutItem or UpdateItem operations. For more
information, see Read Consistency (p. 15).
If you require strongly consistent reads, set the ConsistentRead parameter to true in the Query request.
Querying Tables and Indexes: Java
The Query operation enables you to query a table or a secondary index. You must provide a partition
key value and an equality condition. If the table or index has a sort key, you can reﬁne the results by
providing a sort key value and a condition.
Note
The SDK for Java also provides an object persistence model, allowing you to map your clientside classes to DynamoDB tables. This approach can reduce the amount of code you have to
write. For more information, see Java: DynamoDBMapper (p. 195).
The following are the steps to retrieve an item using the AWS SDK for Java Document API.
1. Create an instance of the DynamoDB class.
2. Create an instance of the Table class to represent the table you want to work with.
3. Call the query method of the Table instance. You must specify the partition key value of the item(s)
that you want to retrieve, along with any optional query parameters.
The response includes an ItemCollection object that provides all items returned by the query.
The following Java code snippet demonstrates the preceding tasks. The snippet assumes you have a
Reply table that stores replies for forum threads. For more information, see Creating Tables and Loading
Sample Data (p. 280).
Reply ( Id, ReplyDateTime, ... )
Each forum thread has a unique ID and can have zero or more replies. Therefore, the Id attribute
of the Reply table is composed of both the forum name and forum subject. Id (partition key) and
ReplyDateTime (sort key) make up the composite primary key for the table.
The following query retrieves all replies for a speciﬁc thread subject. The query requires both the table
name and the Subject value.
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Example
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard()
.withRegion(Regions.US_WEST_2).build();
DynamoDB dynamoDB = new DynamoDB(client);
Table table = dynamoDB.getTable(&quot;Reply&quot;);
QuerySpec spec = new QuerySpec()
.withKeyConditionExpression(&quot;Id = :v_id&quot;)
.withValueMap(new ValueMap()
.withString(&quot;:v_id&quot;, &quot;Amazon DynamoDB#DynamoDB Thread 1&quot;));
ItemCollection&lt;QueryOutcome&gt; items = table.query(spec);
Iterator&lt;Item&gt; iterator = items.iterator();
Item item = null;
while (iterator.hasNext()) {
item = iterator.next();
System.out.println(item.toJSONPretty());
}
Specifying Optional Parameters
The query method supports several optional parameters. For example, you can optionally narrow the
results from the preceding query to return replies in the past two weeks by specifying a condition. The
condition is called a sort key condition, because DynamoDB evaluates the query condition that you
specify against the sort key of the primary key. You can specify other optional parameters to retrieve
only a speciﬁc list of attributes from items in the query result.
The following Java code snippet retrieves forum thread replies posted in the past 15 days. The snippet
speciﬁes optional parameters using:
• A KeyConditionExpression to retrieve the replies from a speciﬁc discussion forum (partition key) and,
within that set of items, replies that were posted within the last 15 days (sort key).
• A FilterExpression to return only the replies from a speciﬁc user. The ﬁlter is applied after the query
is processed, but before the results are returned to the user.
• A ValueMap to deﬁne the actual values for the KeyConditionExpression placeholders.
• A ConsistentRead setting of true, to request a strongly consistent read.
This snippet uses a QuerySpec object which gives access to all of the low-level Query input parameters.
Example
Table table = dynamoDB.getTable(&quot;Reply&quot;);
long twoWeeksAgoMilli = (new Date()).getTime() - (15L*24L*60L*60L*1000L);
Date twoWeeksAgo = new Date();
twoWeeksAgo.setTime(twoWeeksAgoMilli);
SimpleDateFormat df = new SimpleDateFormat(&quot;yyyy-MM-dd'T'HH:mm:ss.SSS'Z'&quot;);
String twoWeeksAgoStr = df.format(twoWeeksAgo);
QuerySpec spec = new QuerySpec()
.withKeyConditionExpression(&quot;Id = :v_id and ReplyDateTime &gt; :v_reply_dt_tm&quot;)
.withFilterExpression(&quot;PostedBy = :v_posted_by&quot;)
.withValueMap(new ValueMap()
.withString(&quot;:v_id&quot;, &quot;Amazon DynamoDB#DynamoDB Thread 1&quot;)
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.withString(&quot;:v_reply_dt_tm&quot;, twoWeeksAgoStr)
.withString(&quot;:v_posted_by&quot;, &quot;User B&quot;))
.withConsistentRead(true);
ItemCollection&lt;QueryOutcome&gt; items = table.query(spec);
Iterator&lt;Item&gt; iterator = items.iterator();
while (iterator.hasNext()) {
System.out.println(iterator.next().toJSONPretty());
}
You can also optionally limit the number of items per page by using the withMaxPageSize method. When
time you call the query method, you get an ItemCollection that contains the resulting items. You can
then step through the results, processing one page at a time, until there are no more pages.
The following Java code snippet modiﬁes the query speciﬁcation shown above. This time, the query spec
uses the withMaxPageSize method. The Page class provides an Iterator that allows the code to process
the items on each page.
Example
spec.withMaxPageSize(10);
ItemCollection&lt;QueryOutcome&gt; items = table.query(spec);
// Process each page of results
int pageNum = 0;
for (Page&lt;Item, QueryOutcome&gt; page : items.pages()) {
System.out.println(&quot;\nPage: &quot; + ++pageNum);
}
// Process each item on the current page
Iterator&lt;Item&gt; item = page.iterator();
while (item.hasNext()) {
System.out.println(item.next().toJSONPretty());
}
Example - Query Using Java
The following tables store information about a collection of forums. For more information, see Creating
Tables and Loading Sample Data (p. 280).
Note
The SDK for Java also provides an object persistence model, allowing you to map your clientside classes to DynamoDB tables. This approach can reduce the amount of code you have to
write. For more information, see Java: DynamoDBMapper (p. 195).
Example
Forum ( Name, ... )
Thread ( ForumName, Subject, Message, LastPostedBy, LastPostDateTime, ...)
Reply ( Id, ReplyDateTime, Message, PostedBy, ...)
In this Java code example, you execute variations of ﬁnding replies for a thread 'DynamoDB Thread 1' in
forum 'DynamoDB'.
• Find replies for a thread.
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• Find replies for a thread, specifying a limit on the number of items per page of results. If the number
of items in the result set exceeds the page size, you get only the ﬁrst page of results. This coding
pattern ensures your code processes all the pages in the query result.
• Find replies in the last 15 days.
• Find replies in a speciﬁc date range.
Both the preceding two queries shows how you can specify sort key conditions to narrow the query
results and use other optional query parameters.
Note
This code sample assumes that you have already loaded data into DynamoDB for your account
by following the instructions in the Creating Tables and Loading Sample Data (p. 280) section.
For step-by-step instructions to run the following example, see Java Code Samples (p. 285).
// Copyright 2012-2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
// Licensed under the Apache License, Version 2.0.
package com.amazonaws.codesamples.document;
import java.text.SimpleDateFormat;
import java.util.Date;
import java.util.Iterator;
import
import
import
import
import
import
import
import
import
import
com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
com.amazonaws.services.dynamodbv2.document.DynamoDB;
com.amazonaws.services.dynamodbv2.document.Item;
com.amazonaws.services.dynamodbv2.document.ItemCollection;
com.amazonaws.services.dynamodbv2.document.Page;
com.amazonaws.services.dynamodbv2.document.QueryOutcome;
com.amazonaws.services.dynamodbv2.document.Table;
com.amazonaws.services.dynamodbv2.document.spec.QuerySpec;
com.amazonaws.services.dynamodbv2.document.utils.ValueMap;
public class DocumentAPIQuery {
static AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
static DynamoDB dynamoDB = new DynamoDB(client);
static String tableName = &quot;Reply&quot;;
public static void main(String[] args) throws Exception {
String forumName = &quot;Amazon DynamoDB&quot;;
String threadSubject = &quot;DynamoDB Thread 1&quot;;
}
findRepliesForAThread(forumName, threadSubject);
findRepliesForAThreadSpecifyOptionalLimit(forumName, threadSubject);
findRepliesInLast15DaysWithConfig(forumName, threadSubject);
findRepliesPostedWithinTimePeriod(forumName, threadSubject);
findRepliesUsingAFilterExpression(forumName, threadSubject);
private static void findRepliesForAThread(String forumName, String threadSubject) {
Table table = dynamoDB.getTable(tableName);
String replyId = forumName + &quot;#&quot; + threadSubject;
QuerySpec spec = new QuerySpec().withKeyConditionExpression(&quot;Id = :v_id&quot;)
.withValueMap(new ValueMap().withString(&quot;:v_id&quot;, replyId));
ItemCollection&lt;QueryOutcome&gt; items = table.query(spec);
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System.out.println(&quot;\nfindRepliesForAThread results:&quot;);
Iterator&lt;Item&gt; iterator = items.iterator();
while (iterator.hasNext()) {
System.out.println(iterator.next().toJSONPretty());
}
}
private static void findRepliesForAThreadSpecifyOptionalLimit(String forumName, String
threadSubject) {
Table table = dynamoDB.getTable(tableName);
String replyId = forumName + &quot;#&quot; + threadSubject;
QuerySpec spec = new QuerySpec().withKeyConditionExpression(&quot;Id = :v_id&quot;)
.withValueMap(new ValueMap().withString(&quot;:v_id&quot;, replyId)).withMaxPageSize(1);
ItemCollection&lt;QueryOutcome&gt; items = table.query(spec);
System.out.println(&quot;\nfindRepliesForAThreadSpecifyOptionalLimit results:&quot;);
// Process each page of results
int pageNum = 0;
for (Page&lt;Item, QueryOutcome&gt; page : items.pages()) {
System.out.println(&quot;\nPage: &quot; + ++pageNum);
}
}
// Process each item on the current page
Iterator&lt;Item&gt; item = page.iterator();
while (item.hasNext()) {
System.out.println(item.next().toJSONPretty());
}
private static void findRepliesInLast15DaysWithConfig(String forumName, String
threadSubject) {
Table table = dynamoDB.getTable(tableName);
long twoWeeksAgoMilli = (new Date()).getTime() - (15L * 24L * 60L * 60L * 1000L);
Date twoWeeksAgo = new Date();
twoWeeksAgo.setTime(twoWeeksAgoMilli);
SimpleDateFormat df = new SimpleDateFormat(&quot;yyyy-MM-dd'T'HH:mm:ss.SSS'Z'&quot;);
String twoWeeksAgoStr = df.format(twoWeeksAgo);
String replyId = forumName + &quot;#&quot; + threadSubject;
QuerySpec spec = new QuerySpec().withProjectionExpression(&quot;Message, ReplyDateTime,
PostedBy&quot;)
.withKeyConditionExpression(&quot;Id = :v_id and ReplyDateTime &lt;= :v_reply_dt_tm&quot;)
.withValueMap(new ValueMap().withString(&quot;:v_id&quot;,
replyId).withString(&quot;:v_reply_dt_tm&quot;, twoWeeksAgoStr));
ItemCollection&lt;QueryOutcome&gt; items = table.query(spec);
System.out.println(&quot;\nfindRepliesInLast15DaysWithConfig results:&quot;);
Iterator&lt;Item&gt; iterator = items.iterator();
while (iterator.hasNext()) {
System.out.println(iterator.next().toJSONPretty());
}
}
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private static void findRepliesPostedWithinTimePeriod(String forumName, String
threadSubject) {
Table table = dynamoDB.getTable(tableName);
long startDateMilli = (new Date()).getTime() - (15L * 24L * 60L * 60L * 1000L);
long endDateMilli = (new Date()).getTime() - (5L * 24L * 60L * 60L * 1000L);
java.text.SimpleDateFormat df = new java.text.SimpleDateFormat(&quot;yyyy-MMdd'T'HH:mm:ss.SSS'Z'&quot;);
String startDate = df.format(startDateMilli);
String endDate = df.format(endDateMilli);
String replyId = forumName + &quot;#&quot; + threadSubject;
QuerySpec spec = new QuerySpec().withProjectionExpression(&quot;Message, ReplyDateTime,
PostedBy&quot;)
.withKeyConditionExpression(&quot;Id = :v_id and ReplyDateTime between :v_start_dt
and :v_end_dt&quot;)
.withValueMap(new ValueMap().withString(&quot;:v_id&quot;,
replyId).withString(&quot;:v_start_dt&quot;, startDate)
.withString(&quot;:v_end_dt&quot;, endDate));
ItemCollection&lt;QueryOutcome&gt; items = table.query(spec);
}
System.out.println(&quot;\nfindRepliesPostedWithinTimePeriod results:&quot;);
Iterator&lt;Item&gt; iterator = items.iterator();
while (iterator.hasNext()) {
System.out.println(iterator.next().toJSONPretty());
}
private static void findRepliesUsingAFilterExpression(String forumName, String
threadSubject) {
Table table = dynamoDB.getTable(tableName);
String replyId = forumName + &quot;#&quot; + threadSubject;
QuerySpec spec = new QuerySpec().withProjectionExpression(&quot;Message, ReplyDateTime,
PostedBy&quot;)
.withKeyConditionExpression(&quot;Id = :v_id&quot;).withFilterExpression(&quot;PostedBy
= :v_postedby&quot;)
.withValueMap(new ValueMap().withString(&quot;:v_id&quot;,
replyId).withString(&quot;:v_postedby&quot;, &quot;User B&quot;));
ItemCollection&lt;QueryOutcome&gt; items = table.query(spec);
}
System.out.println(&quot;\nfindRepliesUsingAFilterExpression results:&quot;);
Iterator&lt;Item&gt; iterator = items.iterator();
while (iterator.hasNext()) {
System.out.println(iterator.next().toJSONPretty());
}
}
Querying Tables and Indexes: .NET
The Query operation enables you to query a table or a secondary index. You must provide a partition
key value and an equality condition. If the table or index has a sort key, you can reﬁne the results by
providing a sort key value and a condition.
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The following are the steps to query a table using low-level .NET SDK API.
1. Create an instance of the AmazonDynamoDBClient class.
2. Create an instance of the QueryRequest class and provide query operation parameters.
3. Execute the Query method and provide the QueryRequest object that you created in the preceding
step.
The response includes the QueryResult object that provides all items returned by the query.
The following C# code snippet demonstrates the preceding tasks. The snippet assumes you have a Reply
table stores replies for forum threads. For more information, see Creating Tables and Loading Sample
Data (p. 280).
Example
Reply ( &lt;emphasis role=&quot;underline&quot;&gt;Id&lt;/emphasis&gt;, &lt;emphasis
role=&quot;underline&quot;&gt;ReplyDateTime&lt;/emphasis&gt;, ... )
Each forum thread has a unique ID and can have zero or more replies. Therefore, the primary key is
composed of both the Id (partition key) and ReplyDateTime (sort key).
The following query retrieves all replies for a speciﬁc thread subject. The query requires both the table
name and the Subject value.
Example
AmazonDynamoDBClient client = new AmazonDynamoDBClient();
var request = new QueryRequest
{
TableName = &quot;Reply&quot;,
KeyConditionExpression = &quot;Id = :v_Id&quot;,
ExpressionAttributeValues = new Dictionary&lt;string, AttributeValue&gt; {
{&quot;:v_Id&quot;, new AttributeValue { S = &quot;Amazon DynamoDB#DynamoDB Thread 1&quot; }}}
};
var response = client.Query(request);
foreach (Dictionary&lt;string, AttributeValue&gt; item in response.Items)
{
// Process the result.
PrintItem(item);
}
Specifying Optional Parameters
The Query method supports several optional parameters. For example, you can optionally narrow the
query result in the preceding query to return replies in the past two weeks by specifying a condition. The
condition is called a sort key condition, because Amazon DynamoDB evaluates the query condition that
you specify against the sort key of the primary key. You can specify other optional parameters to retrieve
only a speciﬁc list of attributes from items in the query result. For more information, see Query.
The following C# code snippet retrieves forum thread replies posted in the past 15 days. The snippet
speciﬁes the following optional parameters:
• A KeyConditionExpression to retrieve only the replies in the past 15 days.
• A ProjectionExpression parameter to specify a list of attributes to retrieve for items in the query
result.
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• A ConsistentRead parameter to perform a strongly consistent read.
Example
DateTime twoWeeksAgoDate = DateTime.UtcNow - TimeSpan.FromDays(15);
string twoWeeksAgoString = twoWeeksAgoDate.ToString(AWSSDKUtils.ISO8601DateFormat);
var request = new QueryRequest
{
TableName = &quot;Reply&quot;,
KeyConditionExpression = &quot;Id = :v_Id and ReplyDateTime &gt; :v_twoWeeksAgo&quot;,
ExpressionAttributeValues = new Dictionary&lt;string, AttributeValue&gt; {
{&quot;:v_Id&quot;, new AttributeValue { S = &quot;Amazon DynamoDB#DynamoDB Thread 2&quot; }},
{&quot;:v_twoWeeksAgo&quot;, new AttributeValue { S = twoWeeksAgoString }}
},
ProjectionExpression = &quot;Subject, ReplyDateTime, PostedBy&quot;,
ConsistentRead = true
};
var response = client.Query(request);
foreach (Dictionary&lt;string, AttributeValue&gt; item in response.Items)
{
// Process the result.
PrintItem(item);
}
You can also optionally limit the page size, or the number of items per page, by adding the optional
Limit parameter. Each time you execute the Query method, you get one page of results that has the
speciﬁed number of items. To fetch the next page, you execute the Query method again by providing
the primary key value of the last item in the previous page so that the method can return the next set of
items. You provide this information in the request by setting the ExclusiveStartKey property. Initially,
this property can be null. To retrieve subsequent pages, you must update this property value to the
primary key of the last item in the preceding page.
The following C# code snippet queries the Reply table. In the request, it speciﬁes the Limit and
ExclusiveStartKey optional parameters. The do/while loop continues to scan one page at time until the
LastEvaluatedKey returns a null value.
Example
Dictionary&lt;string,AttributeValue&gt; lastKeyEvaluated = null;
do
{
var request = new QueryRequest
{
TableName = &quot;Reply&quot;,
KeyConditionExpression = &quot;Id = :v_Id&quot;,
ExpressionAttributeValues = new Dictionary&lt;string, AttributeValue&gt; {
{&quot;:v_Id&quot;, new AttributeValue { S = &quot;Amazon DynamoDB#DynamoDB Thread 2&quot; }}
},
};
// Optional parameters.
Limit = 1,
ExclusiveStartKey = lastKeyEvaluated
var response = client.Query(request);
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// Process the query result.
foreach (Dictionary&lt;string, AttributeValue&gt; item in response.Items)
{
PrintItem(item);
}
lastKeyEvaluated = response.LastEvaluatedKey;
} while (lastKeyEvaluated != null &amp;&amp; lastKeyEvaluated.Count != 0);
Example - Querying Using the AWS SDK for .NET
The following tables store information about a collection of forums. For more information, see Creating
Tables and Loading Sample Data (p. 280).
Example
Forum ( &lt;emphasis role=&quot;underline&quot;&gt;Name&lt;/emphasis&gt;, ... )
Thread ( &lt;emphasis role=&quot;underline&quot;&gt;ForumName&lt;/emphasis&gt;, &lt;emphasis
role=&quot;underline&quot;&gt;Subject&lt;/emphasis&gt;, Message, LastPostedBy, LastPostDateTime, ...)
Reply ( &lt;emphasis role=&quot;underline&quot;&gt;Id&lt;/emphasis&gt;, &lt;emphasis
role=&quot;underline&quot;&gt;ReplyDateTime&lt;/emphasis&gt;, Message, PostedBy, ...)
In this C# code example, you execute variations of &quot;Find replies for a thread &quot;DynamoDB Thread 1&quot; in
forum &quot;DynamoDB&quot;.
• Find replies for a thread.
• Find replies for a thread. Specify the Limit query parameter to set page size.
This function illustrate the use of pagination to process multipage result. Amazon DynamoDB has
a page size limit and if your result exceeds the page size, you get only the ﬁrst page of results. This
coding pattern ensures your code processes all the pages in the query result.
• Find replies in the last 15 days.
• Find replies in a speciﬁc date range.
Both of the preceding two queries shows how you can specify sort key conditions to narrow query
results and use other optional query parameters.
For step-by-step instructions to test the following sample, see .NET Code Samples (p. 287).
using
using
using
using
using
using
System;
System.Collections.Generic;
Amazon.DynamoDBv2;
Amazon.DynamoDBv2.Model;
Amazon.Runtime;
Amazon.Util;
namespace com.amazonaws.codesamples
{
class LowLevelQuery
{
private static AmazonDynamoDBClient client = new AmazonDynamoDBClient();
static void Main(string[] args)
{
try
{
// Query a specific forum and thread.
string forumName = &quot;Amazon DynamoDB&quot;;
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string threadSubject = &quot;DynamoDB Thread 1&quot;;
FindRepliesForAThread(forumName, threadSubject);
FindRepliesForAThreadSpecifyOptionalLimit(forumName, threadSubject);
FindRepliesInLast15DaysWithConfig(forumName, threadSubject);
FindRepliesPostedWithinTimePeriod(forumName, threadSubject);
Console.WriteLine(&quot;Example complete. To continue, press Enter&quot;);
Console.ReadLine();
}
catch (AmazonDynamoDBException e) { Console.WriteLine(e.Message);
Console.ReadLine(); }
catch (AmazonServiceException e) { Console.WriteLine(e.Message);
Console.ReadLine(); }
catch (Exception e) { Console.WriteLine(e.Message); Console.ReadLine(); }
}
private static void FindRepliesPostedWithinTimePeriod(string forumName, string
threadSubject)
{
Console.WriteLine(&quot;*** Executing FindRepliesPostedWithinTimePeriod() ***&quot;);
string replyId = forumName + &quot;#&quot; + threadSubject;
// You must provide date value based on your test data.
DateTime startDate = DateTime.UtcNow - TimeSpan.FromDays(21);
string start = startDate.ToString(AWSSDKUtils.ISO8601DateFormat);
// You provide date value based on your test data.
DateTime endDate = DateTime.UtcNow - TimeSpan.FromDays(5);
string end = endDate.ToString(AWSSDKUtils.ISO8601DateFormat);
var request = new QueryRequest
{
TableName = &quot;Reply&quot;,
ReturnConsumedCapacity = &quot;TOTAL&quot;,
KeyConditionExpression = &quot;Id = :v_replyId and ReplyDateTime
between :v_start and :v_end&quot;,
ExpressionAttributeValues = new Dictionary&lt;string, AttributeValue&gt; {
{&quot;:v_replyId&quot;, new AttributeValue {
S = replyId
}},
{&quot;:v_start&quot;, new AttributeValue {
S = start
}},
{&quot;:v_end&quot;, new AttributeValue {
S = end
}}
}
};
var response = client.Query(request);
Console.WriteLine(&quot;\nNo. of reads used (by query in
FindRepliesPostedWithinTimePeriod) {0}&quot;,
response.ConsumedCapacity.CapacityUnits);
foreach (Dictionary&lt;string, AttributeValue&gt; item
in response.Items)
{
PrintItem(item);
}
Console.WriteLine(&quot;To continue, press Enter&quot;);
Console.ReadLine();
}
private static void FindRepliesInLast15DaysWithConfig(string forumName, string
threadSubject)
{
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Console.WriteLine(&quot;*** Executing FindRepliesInLast15DaysWithConfig() ***&quot;);
string replyId = forumName + &quot;#&quot; + threadSubject;
DateTime twoWeeksAgoDate = DateTime.UtcNow - TimeSpan.FromDays(15);
string twoWeeksAgoString =
twoWeeksAgoDate.ToString(AWSSDKUtils.ISO8601DateFormat);
var request = new QueryRequest
{
TableName = &quot;Reply&quot;,
ReturnConsumedCapacity = &quot;TOTAL&quot;,
KeyConditionExpression = &quot;Id = :v_replyId and ReplyDateTime
&gt; :v_interval&quot;,
ExpressionAttributeValues = new Dictionary&lt;string, AttributeValue&gt; {
{&quot;:v_replyId&quot;, new AttributeValue {
S = replyId
}},
{&quot;:v_interval&quot;, new AttributeValue {
S = twoWeeksAgoString
}}
},
};
// Optional parameter.
ProjectionExpression = &quot;Id, ReplyDateTime, PostedBy&quot;,
// Optional parameter.
ConsistentRead = true
var response = client.Query(request);
Console.WriteLine(&quot;No. of reads used (by query in
FindRepliesInLast15DaysWithConfig) {0}&quot;,
response.ConsumedCapacity.CapacityUnits);
foreach (Dictionary&lt;string, AttributeValue&gt; item
in response.Items)
{
PrintItem(item);
}
Console.WriteLine(&quot;To continue, press Enter&quot;);
Console.ReadLine();
}
private static void FindRepliesForAThreadSpecifyOptionalLimit(string forumName,
string threadSubject)
{
Console.WriteLine(&quot;*** Executing FindRepliesForAThreadSpecifyOptionalLimit()
***&quot;);
string replyId = forumName + &quot;#&quot; + threadSubject;
Dictionary&lt;string, AttributeValue&gt; lastKeyEvaluated = null;
do
{
var request = new QueryRequest
{
TableName = &quot;Reply&quot;,
ReturnConsumedCapacity = &quot;TOTAL&quot;,
KeyConditionExpression = &quot;Id = :v_replyId&quot;,
ExpressionAttributeValues = new Dictionary&lt;string, AttributeValue&gt; {
{&quot;:v_replyId&quot;, new AttributeValue {
S = replyId
}}
},
Limit = 2, // The Reply table has only a few sample items. So the page
size is smaller.
ExclusiveStartKey = lastKeyEvaluated
};
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var response = client.Query(request);
Console.WriteLine(&quot;No. of reads used (by query in
FindRepliesForAThreadSpecifyLimit) {0}\n&quot;,
response.ConsumedCapacity.CapacityUnits);
foreach (Dictionary&lt;string, AttributeValue&gt; item
in response.Items)
{
PrintItem(item);
}
lastKeyEvaluated = response.LastEvaluatedKey;
} while (lastKeyEvaluated != null &amp;&amp; lastKeyEvaluated.Count != 0);
Console.WriteLine(&quot;To continue, press Enter&quot;);
}
Console.ReadLine();
private static void FindRepliesForAThread(string forumName, string threadSubject)
{
Console.WriteLine(&quot;*** Executing FindRepliesForAThread() ***&quot;);
string replyId = forumName + &quot;#&quot; + threadSubject;
var request = new QueryRequest
{
TableName = &quot;Reply&quot;,
ReturnConsumedCapacity = &quot;TOTAL&quot;,
KeyConditionExpression = &quot;Id = :v_replyId&quot;,
ExpressionAttributeValues = new Dictionary&lt;string, AttributeValue&gt; {
{&quot;:v_replyId&quot;, new AttributeValue {
S = replyId
}}
}
};
var response = client.Query(request);
Console.WriteLine(&quot;No. of reads used (by query in FindRepliesForAThread)
{0}\n&quot;,
}
response.ConsumedCapacity.CapacityUnits);
foreach (Dictionary&lt;string, AttributeValue&gt; item in response.Items)
{
PrintItem(item);
}
Console.WriteLine(&quot;To continue, press Enter&quot;);
Console.ReadLine();
private static void PrintItem(
Dictionary&lt;string, AttributeValue&gt; attributeList)
{
foreach (KeyValuePair&lt;string, AttributeValue&gt; kvp in attributeList)
{
string attributeName = kvp.Key;
AttributeValue value = kvp.Value;
+ &quot;]&quot;) +
+ &quot;]&quot;)
Console.WriteLine(
attributeName + &quot; &quot; +
(value.S == null ? &quot;&quot; : &quot;S=[&quot; + value.S + &quot;]&quot;) +
(value.N == null ? &quot;&quot; : &quot;N=[&quot; + value.N + &quot;]&quot;) +
(value.SS == null ? &quot;&quot; : &quot;SS=[&quot; + string.Join(&quot;,&quot;, value.SS.ToArray())
(value.NS == null ? &quot;&quot; : &quot;NS=[&quot; + string.Join(&quot;,&quot;, value.NS.ToArray())
);
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Working with Scans
}
}
}
}
Console.WriteLine(&quot;************************************************&quot;);
Working with Scans
Topics
• Filter Expressions for Scan (p. 427)
• Limiting the Number of Items in the Result Set (p. 428)
• Paginating the Results (p. 428)
• Counting the Items in the Results (p. 429)
• Capacity Units Consumed by Scan (p. 429)
• Read Consistency for Scan (p. 430)
• Parallel Scan (p. 430)
• Scanning Tables and Indexes: Java (p. 431)
• Scanning Tables and Indexes: .NET (p. 438)
A Scan operation reads every item in a table or a secondary index. By default, a Scan operation returns
all of the data attributes for every item in the table or index. You can use the ProjectionExpression
parameter so that Scan only returns some of the attributes, rather than all of them.
Scan always returns a result set. If no matching items are found, the result set will be empty.
A single Scan request can retrieve a maximum of 1 MB of data; DynamoDB can optionally apply a ﬁlter
expression to this data, narrowing the results before they are returned to the user.
Filter Expressions for Scan
If you need to further reﬁne the Scan results, you can optionally provide a ﬁlter expression. A ﬁlter
expression determines which items within the Scan results should be returned to you. All of the other
results are discarded.
A ﬁlter expression is applied after a Scan ﬁnishes, but before the results are returned. Therefore, a Scan
will consume the same amount of read capacity, regardless of whether a ﬁlter expression is present.
A Scan operation can retrieve a maximum of 1 MB of data. This limit applies before the ﬁlter expression
is evaluated.
With Scan, you can specify any attributes in a ﬁlter expression—including partition key and sort key
attributes.
The syntax for a ﬁlter expression is identical to that of a condition expression. Filter expressions can use
the same comparators, functions, and logical operators as a condition expression. For more information,
Condition Expressions (p. 346).
Example
The following AWS CLI example scans the Thread table and returns only the items that were last posted
to by a particular user.
aws dynamodb scan \
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--table-name Thread \
--filter-expression &quot;LastPostedBy = :name&quot; \
--expression-attribute-values '{&quot;:name&quot;:{&quot;S&quot;:&quot;User A&quot;}}'
Limiting the Number of Items in the Result Set
The Scan operation allows you to limit the number of items that it returns in the result. To do this, set
the Limit parameter to the maximum number of items that you want.
For example, suppose you Scan a table, with a Limit value of 6, and without a ﬁlter expression. The Scan
result will contain the ﬁrst six items from the table that match the key condition expression from the
request.
Now suppose you add a ﬁlter expression to the Scan. In this case, DynamoDB will apply the ﬁlter
expression to the six items that were returned, discarding those that do not match. The ﬁnal Scan result
will contain 6 items or fewer, depending on the number of items that were ﬁltered.
Paginating the Results
DynamoDB paginates the results from Scan operations. With pagination, the Scan results are divided into
&quot;pages&quot; of data that are 1 MB in size (or less). An application can process the ﬁrst page of results, then
the second page, and so on.
A single Scan will only return a result set that ﬁts within the 1 MB size limit. To determine whether there
are more results, and to retrieve them one page at a time, applications should do the following:
1. Examine the low-level Scan result:
• If the result contains a LastEvaluatedKey element, proceed to step 2.
• If there is not a LastEvaluatedKey in the result, then there are no more items to be retrieved.
2. Construct a new Scan request, with the same parameters as the previous one—but this time, take the
LastEvaluatedKey value from step 1 and use it as the ExclusiveStartKey parameter in the new Scan
request.
3. Run the new Scan request.
4. Go to step 1.
In other words, the LastEvaluatedKey from a Scan response should be used as the ExclusiveStartKey
for the next Scan request. If there is not a LastEvaluatedKey element in a Scan response, then you have
retrieved the ﬁnal page of results. (The absence of LastEvaluatedKey is the only way to know that you
have reached the end of the result set.)
You can use the AWS CLI to view this behavior. The CLI sends low-level Scan requests to DynamoDB,
repeatedly, until LastEvaluatedKey is no longer present in the results. Consider the following AWS CLI
example that scans the entire Movies table but returns only the movies from a particular genre:
aws dynamodb scan \
--table-name Movies \
--projection-expression &quot;title&quot; \
--filter-expression 'contains(info.genres,:gen)' \
--expression-attribute-values '{&quot;:gen&quot;:{&quot;S&quot;:&quot;Sci-Fi&quot;}}' \
--page-size 100 \
--debug
Ordinarily, the AWS CLI handles pagination automatically; however, in this example, the CLI's -page-size parameter limits the number of items per page. The --debug parameter prints low-level
information about requests and responses.
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If you run the example, the ﬁrst response from DynamoDB looks similar to this:
2017-07-07 12:19:14,389 - MainThread - botocore.parsers - DEBUG - Response body:
b'{&quot;Count&quot;:7,&quot;Items&quot;:[{&quot;title&quot;:{&quot;S&quot;:&quot;Monster on the Campus&quot;}},{&quot;title&quot;:{&quot;S&quot;:&quot;+1&quot;}},
{&quot;title&quot;:{&quot;S&quot;:&quot;100 Degrees Below Zero&quot;}},{&quot;title&quot;:{&quot;S&quot;:&quot;About Time&quot;}},{&quot;title&quot;:{&quot;S&quot;:&quot;After
Earth&quot;}},
{&quot;title&quot;:{&quot;S&quot;:&quot;Age of Dinosaurs&quot;}},{&quot;title&quot;:{&quot;S&quot;:&quot;Cloudy with a Chance of Meatballs 2&quot;}}],
&quot;LastEvaluatedKey&quot;:{&quot;year&quot;:{&quot;N&quot;:&quot;2013&quot;},&quot;title&quot;:{&quot;S&quot;:&quot;Curse of
Chucky&quot;}},&quot;ScannedCount&quot;:100}'
The LastEvaluatedKey in the response indicates that not all of the items have been retrieved. The AWS
CLI will then issue another Scan request to DynamoDB. This request and response pattern continues,
until the ﬁnal response:
2017-07-07 12:19:17,830 - MainThread - botocore.parsers - DEBUG - Response body:
b'{&quot;Count&quot;:1,&quot;Items&quot;:[{&quot;title&quot;:{&quot;S&quot;:&quot;WarGames&quot;}}],&quot;ScannedCount&quot;:6}'
The absence of LastEvaluatedKey indicates that there are no more items to retrieve.
Note
The AWS SDKs handle the low-level DynamoDB responses (including the presence or absence of
LastEvaluatedKey), and provide various abstractions for paginating Scan results. For example,
the SDK for Java document interface provides java.util.Iterator support, so that you can
walk through the results one at a time.
For code samples in various programming languages, see the Amazon DynamoDB Getting
Started Guide and the AWS SDK documentation for your language.
Counting the Items in the Results
In addition to the items that match your criteria, the Scan response contains the following elements:
• ScannedCount — the number of items that matched the key condition expression, before a ﬁlter
expression (if present) was applied.
• Count — the number of items that remain, after a ﬁlter expression (if present) was applied.
Note
If you do not use a ﬁlter expression, then ScannedCount and Count will have the same value.
If the size of the Scan result set is larger than 1 MB, then ScannedCount and Count will represent only a
partial count of the total items. You will need to perform multiple Scan operations in order to retrieve all
of the results (see Paginating the Results (p. 428)).
Each Scan response will contain the ScannedCount and Count for the items that were processed by that
particular Scan request. To obtain grand totals for all of the Scan requests, you could keep a running tally
of both ScannedCount and Count.
Capacity Units Consumed by Scan
You can Scan any table or secondary index. Scan operations consume read capacity units, as follows:
If you Scan a...
DynamoDB consumes read capacity units from...
Table
The table's provisioned read capacity.
Global secondary index
The index's provisioned read capacity.
Local secondary index
The base table's provisioned read capacity.
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Read Consistency for Scan
By default, a Scan operation does not return any data on how much read capacity it consumes. However,
you can specify the ReturnConsumedCapacity parameter in a Scan request to obtain this information. The
following are the valid settings for ReturnConsumedCapacity:
• NONE—no consumed capacity data is returned. (This is the default.)
• TOTAL—the response includes the aggregate number of read capacity units consumed.
• INDEXES—the response shows the aggregate number of read capacity units consumed, together with
the consumed capacity for each table and index that was accessed.
DynamoDB calculates the number of read capacity units consumed based on item size, not on the
amount of data that is returned to an application. For this reason, the number of capacity units
consumed will be the same whether you request all of the attributes (the default behavior) or just some
of them (using a projection expression). The number will also be the same whether or not you use a ﬁlter
expression.
Read Consistency for Scan
A Scan operation performs eventually consistent reads, by default. This means that the Scan results
might not reﬂect changes due to recently completed PutItem or UpdateItem operations. For more
information, see Read Consistency (p. 15).
If you require strongly consistent reads, as of the time that the Scan begins, set the ConsistentRead
parameter to true in the Scan request. This will ensure that all of the write operations that completed
before the Scan began will be included in the Scan response.
Setting ConsistentRead to true can be useful in table backup or replication scenarios, in conjunction
with DynamoDB Streams: You ﬁrst use Scan with ConsistentRead set to true, in order to obtain a
consistent copy of the data in the table. During the Scan, DynamoDB Streams records any additional
write activity that occurs on the table. After the Scan completes, you can apply the write activity from
the stream to the table.
Note
Note that a Scan operation with ConsistentRead set to true will consume twice as many read
capacity units, as compared to leaving ConsistentRead at its default value (false).
Parallel Scan
By default, the Scan operation processes data sequentially. DynamoDB returns data to the application in
1 MB increments, and an application performs additional Scan operations to retrieve the next 1 MB of
data.
The larger the table or index being scanned, the more time the Scan will take to complete. In addition, a
sequential Scan might not always be able to fully utilize the provisioned read throughput capacity: Even
though DynamoDB distributes a large table's data across multiple physical partitions, a Scan operation
can only read one partition at a time. For this reason, the throughput of a Scan is constrained by the
maximum throughput of a single partition.
To address these issues, the Scan operation can logically divide a table or secondary index into multiple
segments, with multiple application workers scanning the segments in parallel. Each worker can be a
thread (in programming languages that support multithreading) or an operating system process. To
perform a parallel scan, each worker issues its own Scan request with the following parameters:
• Segment — A segment to be scanned by a particular worker. Each worker should use a diﬀerent value
for Segment.
• TotalSegments — The total number of segments for the parallel scan. This value must be the same as
the number of workers that your application will use.
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The following diagram shows how a multithreaded application performs a parallel Scan with three
degrees of parallelism:
In this diagram, the application spawns three threads and assigns each thread a number. (Segments are
zero-based, so the ﬁrst number is always 0.) Each thread issues a Scan request, setting Segment to its
designated number and setting TotalSegments to 3. Each thread scans its designated segment, retrieving
data 1 MB at a time, and returns the data to the application's main thread.
The values for Segment and TotalSegments apply to individual Scan requests, and you can use diﬀerent
values at any time. You might need to experiment with these values, and the number of workers you use,
until your application achieves its best performance.
Note
A parallel scan with a large number of workers can easily consume all of the provisioned
throughput for the table or index being scanned. It is best to avoid such scans if the table or
index is also incurring heavy read or write activity from other applications.
To control the amount of data returned per request, use the Limit parameter. This can help
prevent situations where one worker consumes all of the provisioned throughput, at the
expense of all other workers.
Scanning Tables and Indexes: Java
The Scan operation reads all of the items in a table or index.
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The following are the steps to scan a table using the AWS SDK for Java Document API.
1. Create an instance of the AmazonDynamoDB class.
2. Create an instance of the ScanRequest class and provide scan parameter.
The only required parameter is the table name.
3. Execute the scan method and provide the ScanRequest object that you created in the preceding step.
The following Reply table stores replies for forum threads.
Example
Reply ( Id, ReplyDateTime, Message, PostedBy )
The table maintains all the replies for various forum threads. Therefore, the primary key is composed
of both the Id (partition key) and ReplyDateTime (sort key). The following Java code snippet scans the
entire table. The ScanRequest instance speciﬁes the name of the table to scan.
Example
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
ScanRequest scanRequest = new ScanRequest()
.withTableName(&quot;Reply&quot;);
ScanResult result = client.scan(scanRequest);
for (Map&lt;String, AttributeValue&gt; item : result.getItems()){
printItem(item);
}
Specifying Optional Parameters
The scan method supports several optional parameters. For example, you can optionally use a ﬁlter
expression to ﬁlter the scan result. In a ﬁlter expression, you can specify a condition and attribute names
and values on which you want the condition evaluated. For more information, see Scan.
The following Java snippet scans the ProductCatalog table to ﬁnd items that are priced less than 0. The
snippet speciﬁes the following optional parameters:
• A ﬁlter expression to retrieve only the items priced less than 0 (error condition).
• A list of attributes to retrieve for items in the query results.
Example
Map&lt;String, AttributeValue&gt; expressionAttributeValues =
new HashMap&lt;String, AttributeValue&gt;();
expressionAttributeValues.put(&quot;:val&quot;, new AttributeValue().withN(&quot;0&quot;));
ScanRequest scanRequest = new ScanRequest()
.withTableName(&quot;ProductCatalog&quot;)
.withFilterExpression(&quot;Price &lt; :val&quot;)
.withProjectionExpression(&quot;Id&quot;)
.withExpressionAttributeValues(expressionAttributeValues);
ScanResult result = client.scan(scanRequest);
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for (Map&lt;String, AttributeValue&gt; item : result.getItems()) {
printItem(item);
}
You can also optionally limit the page size, or the number of items per page, by using the withLimit
method of the scan request. Each time you execute the scan method, you get one page of results that
has the speciﬁed number of items. To fetch the next page, you execute the scan method again by
providing the primary key value of the last item in the previous page so that the scan method can return
the next set of items. You provide this information in the request by using the withExclusiveStartKey
method. Initially, the parameter of this method can be null. To retrieve subsequent pages, you must
update this property value to the primary key of the last item in the preceding page.
The following Java code snippet scans the ProductCatalog table. In the request, the withLimit and
withExclusiveStartKey methods are used. The do/while loop continues to scan one page at time until
the getLastEvaluatedKey method of the result returns a value of null.
Example
Map&lt;String, AttributeValue&gt; lastKeyEvaluated = null;
do {
ScanRequest scanRequest = new ScanRequest()
.withTableName(&quot;ProductCatalog&quot;)
.withLimit(10)
.withExclusiveStartKey(lastKeyEvaluated);
ScanResult result = client.scan(scanRequest);
for (Map&lt;String, AttributeValue&gt; item : result.getItems()){
printItem(item);
}
lastKeyEvaluated = result.getLastEvaluatedKey();
} while (lastKeyEvaluated != null);
Example - Scan Using Java
The following Java code example provides a working sample that scans the ProductCatalog table to ﬁnd
items that are priced less than 100.
Note
The SDK for Java also provides an object persistence model, allowing you to map your clientside classes to DynamoDB tables. This approach can reduce the amount of code you have to
write. For more information, see Java: DynamoDBMapper (p. 195).
Note
This code sample assumes that you have already loaded data into DynamoDB for your account
by following the instructions in the Creating Tables and Loading Sample Data (p. 280) section.
For step-by-step instructions to run the following example, see Java Code Samples (p. 285).
// Copyright 2012-2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
// Licensed under the Apache License, Version 2.0.
package com.amazonaws.codesamples.document;
import java.util.HashMap;
import java.util.Iterator;
import java.util.Map;
import
import
import
import
import
import
com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
com.amazonaws.services.dynamodbv2.document.DynamoDB;
com.amazonaws.services.dynamodbv2.document.Item;
com.amazonaws.services.dynamodbv2.document.ItemCollection;
com.amazonaws.services.dynamodbv2.document.ScanOutcome;
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import com.amazonaws.services.dynamodbv2.document.Table;
public class DocumentAPIScan {
static AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
static DynamoDB dynamoDB = new DynamoDB(client);
static String tableName = &quot;ProductCatalog&quot;;
public static void main(String[] args) throws Exception {
findProductsForPriceLessThanZero();
}
private static void findProductsForPriceLessThanZero() {
Table table = dynamoDB.getTable(tableName);
Map&lt;String, Object&gt; expressionAttributeValues = new HashMap&lt;String, Object&gt;();
expressionAttributeValues.put(&quot;:pr&quot;, 100);
ItemCollection&lt;ScanOutcome&gt; items = table.scan(&quot;Price &lt; :pr&quot;, // FilterExpression
&quot;Id, Title, ProductCategory, Price&quot;, // ProjectionExpression
null, // ExpressionAttributeNames - not used in this example
expressionAttributeValues);
System.out.println(&quot;Scan of &quot; + tableName + &quot; for items with a price less than
100.&quot;);
}
Iterator&lt;Item&gt; iterator = items.iterator();
while (iterator.hasNext()) {
System.out.println(iterator.next().toJSONPretty());
}
}
Example - Parallel Scan Using Java
The following Java code example demonstrates a parallel scan. The program deletes and re-creates
a table named ParallelScanTest, and then loads the table with data. When the data load is ﬁnished,
the program spawns multiple threads and issues parallel Scan requests. The program prints run time
statistics for each parallel request.
Note
The SDK for Java also provides an object persistence model, allowing you to map your clientside classes to DynamoDB tables. This approach can reduce the amount of code you have to
write. For more information, see Java: DynamoDBMapper (p. 195).
Note
This code sample assumes that you have already loaded data into DynamoDB for your account
by following the instructions in the Creating Tables and Loading Sample Data (p. 280) section.
For step-by-step instructions to run the following example, see Java Code Samples (p. 285).
// Copyright 2012-2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
// Licensed under the Apache License, Version 2.0.
package com.amazonaws.codesamples.document;
import
import
import
import
import
java.util.ArrayList;
java.util.Arrays;
java.util.HashSet;
java.util.Iterator;
java.util.List;
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import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.TimeUnit;
import
import
import
import
import
import
import
import
import
import
import
import
import
com.amazonaws.AmazonServiceException;
com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
com.amazonaws.services.dynamodbv2.document.DynamoDB;
com.amazonaws.services.dynamodbv2.document.Item;
com.amazonaws.services.dynamodbv2.document.ItemCollection;
com.amazonaws.services.dynamodbv2.document.ScanOutcome;
com.amazonaws.services.dynamodbv2.document.Table;
com.amazonaws.services.dynamodbv2.document.spec.ScanSpec;
com.amazonaws.services.dynamodbv2.model.AttributeDefinition;
com.amazonaws.services.dynamodbv2.model.KeySchemaElement;
com.amazonaws.services.dynamodbv2.model.KeyType;
com.amazonaws.services.dynamodbv2.model.ProvisionedThroughput;
public class DocumentAPIParallelScan {
// total number of sample items
static int scanItemCount = 300;
// number of items each scan request should return
static int scanItemLimit = 10;
// number of logical segments for parallel scan
static int parallelScanThreads = 16;
// table that will be used for scanning
static String parallelScanTestTableName = &quot;ParallelScanTest&quot;;
static AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
static DynamoDB dynamoDB = new DynamoDB(client);
public static void main(String[] args) throws Exception {
try {
// Clean up the table
deleteTable(parallelScanTestTableName);
createTable(parallelScanTestTableName, 10L, 5L, &quot;Id&quot;, &quot;N&quot;);
// Upload sample data for scan
uploadSampleProducts(parallelScanTestTableName, scanItemCount);
// Scan the table using multiple threads
parallelScan(parallelScanTestTableName, scanItemLimit, parallelScanThreads);
}
{
}
catch (AmazonServiceException ase) {
System.err.println(ase.getMessage());
}
private static void parallelScan(String tableName, int itemLimit, int numberOfThreads)
System.out.println(
&quot;Scanning &quot; + tableName + &quot; using &quot; + numberOfThreads + &quot; threads &quot; + itemLimit
+ &quot; items at a time&quot;);
ExecutorService executor = Executors.newFixedThreadPool(numberOfThreads);
// Divide DynamoDB table into logical segments
// Create one task for scanning each segment
// Each thread will be scanning one segment
int totalSegments = numberOfThreads;
for (int segment = 0; segment &lt; totalSegments; segment++) {
// Runnable task that will only scan one segment
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segment);
}
}
ScanSegmentTask task = new ScanSegmentTask(tableName, itemLimit, totalSegments,
// Execute the task
executor.execute(task);
shutDownExecutorService(executor);
// Runnable task for scanning a single segment of a DynamoDB table
private static class ScanSegmentTask implements Runnable {
// DynamoDB table to scan
private String tableName;
// number of items each scan request should return
private int itemLimit;
// Total number of segments
// Equals to total number of threads scanning the table in parallel
private int totalSegments;
// Segment that will be scanned with by this task
private int segment;
public ScanSegmentTask(String tableName, int itemLimit, int totalSegments, int
segment) {
this.tableName = tableName;
this.itemLimit = itemLimit;
this.totalSegments = totalSegments;
this.segment = segment;
}
@Override
public void run() {
System.out.println(&quot;Scanning &quot; + tableName + &quot; segment &quot; + segment + &quot; out of &quot;
+ totalSegments
+ &quot; segments &quot; + itemLimit + &quot; items at a time...&quot;);
int totalScannedItemCount = 0;
Table table = dynamoDB.getTable(tableName);
try {
ScanSpec spec = new
ScanSpec().withMaxResultSize(itemLimit).withTotalSegments(totalSegments)
.withSegment(segment);
ItemCollection&lt;ScanOutcome&gt; items = table.scan(spec);
Iterator&lt;Item&gt; iterator = items.iterator();
Item currentItem = null;
while (iterator.hasNext()) {
totalScannedItemCount++;
currentItem = iterator.next();
System.out.println(currentItem.toString());
}
}
catch (Exception e) {
System.err.println(e.getMessage());
}
finally {
System.out.println(&quot;Scanned &quot; + totalScannedItemCount + &quot; items from
segment &quot; + segment + &quot; out of &quot;
+ totalSegments + &quot; of &quot; + tableName);
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}
}
}
private static void uploadSampleProducts(String tableName, int itemCount) {
System.out.println(&quot;Adding &quot; + itemCount + &quot; sample items to &quot; + tableName);
for (int productIndex = 0; productIndex &lt; itemCount; productIndex++) {
uploadProduct(tableName, productIndex);
}
}
private static void uploadProduct(String tableName, int productIndex) {
Table table = dynamoDB.getTable(tableName);
try {
System.out.println(&quot;Processing record #&quot; + productIndex);
Item item = new Item().withPrimaryKey(&quot;Id&quot;, productIndex)
.withString(&quot;Title&quot;, &quot;Book &quot; + productIndex + &quot; Title&quot;).withString(&quot;ISBN&quot;,
&quot;111-1111111111&quot;)
.withStringSet(&quot;Authors&quot;, new
HashSet&lt;String&gt;(Arrays.asList(&quot;Author1&quot;))).withNumber(&quot;Price&quot;, 2)
.withString(&quot;Dimensions&quot;, &quot;8.5 x 11.0 x 0.5&quot;).withNumber(&quot;PageCount&quot;, 500)
.withBoolean(&quot;InPublication&quot;, true).withString(&quot;ProductCategory&quot;, &quot;Book&quot;);
table.putItem(item);
}
catch (Exception e) {
System.err.println(&quot;Failed to create item &quot; + productIndex + &quot; in &quot; +
tableName);
System.err.println(e.getMessage());
}
}
private static void deleteTable(String tableName) {
try {
Table table = dynamoDB.getTable(tableName);
table.delete();
System.out.println(&quot;Waiting for &quot; + tableName + &quot; to be deleted...this may take
a while...&quot;);
table.waitForDelete();
}
}
catch (Exception e) {
System.err.println(&quot;Failed to delete table &quot; + tableName);
e.printStackTrace(System.err);
}
private static void createTable(String tableName, long readCapacityUnits, long
writeCapacityUnits,
String partitionKeyName, String partitionKeyType) {
createTable(tableName, readCapacityUnits, writeCapacityUnits, partitionKeyName,
partitionKeyType, null, null);
}
private static void createTable(String tableName, long readCapacityUnits, long
writeCapacityUnits,
String partitionKeyName, String partitionKeyType, String sortKeyName, String
sortKeyType) {
try {
System.out.println(&quot;Creating table &quot; + tableName);
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List&lt;KeySchemaElement&gt; keySchema = new ArrayList&lt;KeySchemaElement&gt;();
keySchema.add(new
KeySchemaElement().withAttributeName(partitionKeyName).withKeyType(KeyType.HASH)); //
Partition
// key
List&lt;AttributeDefinition&gt; attributeDefinitions = new
ArrayList&lt;AttributeDefinition&gt;();
attributeDefinitions
.add(new
AttributeDefinition().withAttributeName(partitionKeyName).withAttributeType(partitionKeyType));
if (sortKeyName != null) {
keySchema.add(new
KeySchemaElement().withAttributeName(sortKeyName).withKeyType(KeyType.RANGE)); // Sort
// key
attributeDefinitions
.add(new
AttributeDefinition().withAttributeName(sortKeyName).withAttributeType(sortKeyType));
}
Table table = dynamoDB.createTable(tableName, keySchema, attributeDefinitions,
new ProvisionedThroughput()
.withReadCapacityUnits(readCapacityUnits).withWriteCapacityUnits(writeCapacityUnits));
System.out.println(&quot;Waiting for &quot; + tableName + &quot; to be created...this may take
a while...&quot;);
table.waitForActive();
}
}
catch (Exception e) {
System.err.println(&quot;Failed to create table &quot; + tableName);
e.printStackTrace(System.err);
}
private static void shutDownExecutorService(ExecutorService executor) {
executor.shutdown();
try {
if (!executor.awaitTermination(10, TimeUnit.SECONDS)) {
executor.shutdownNow();
}
}
catch (InterruptedException e) {
executor.shutdownNow();
}
}
}
// Preserve interrupt status
Thread.currentThread().interrupt();
Scanning Tables and Indexes: .NET
The Scan operation reads all of the items in a table or index.
The following are the steps to scan a table using the AWS SDK for NET low-level API:
1. Create an instance of the AmazonDynamoDBClient class.
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2. Create an instance of the ScanRequest class and provide scan operation parameters.
The only required parameter is the table name.
3. Execute the Scan method and provide the QueryRequest object that you created in the preceding step.
The following Reply table stores replies for forum threads.
Example
&gt;Reply ( &lt;emphasis role=&quot;underline&quot;&gt;Id&lt;/emphasis&gt;, &lt;emphasis
role=&quot;underline&quot;&gt;ReplyDateTime&lt;/emphasis&gt;, Message, PostedBy )
The table maintains all the replies for various forum threads. Therefore, the primary key is composed of
both the Id (partition key) and ReplyDateTime (sort key). The following C# code snippet scans the entire
table. The ScanRequest instance speciﬁes the name of the table to scan.
Example
AmazonDynamoDBClient client = new AmazonDynamoDBClient();
var request = new ScanRequest
{
TableName = &quot;Reply&quot;,
};
var response = client.Scan(request);
var result = response.ScanResult;
foreach (Dictionary&lt;string, AttributeValue&gt; item in response.ScanResult.Items)
{
// Process the result.
PrintItem(item);
}
Specifying Optional Parameters
The Scan method supports several optional parameters. For example, you can optionally use a scan ﬁlter
to ﬁlter the scan result. In a scan ﬁlter, you can specify a condition and an attribute name on which you
want the condition evaluated. For more information, see Scan.
The following C# code scans the ProductCatalog table to ﬁnd items that are priced less than 0. The
sample speciﬁes the following optional parameters:
• A FilterExpression parameter to retrieve only the items priced less than 0 (error condition).
• A ProjectionExpression parameter to specify the attributes to retrieve for items in the query results.
The following C# code snippet scans the ProductCatalog table to ﬁnd all items priced less than 0.
Example
var forumScanRequest = new ScanRequest
{
TableName = &quot;ProductCatalog&quot;,
// Optional parameters.
ExpressionAttributeValues = new Dictionary&lt;string,AttributeValue&gt; {
{&quot;:val&quot;, new AttributeValue { N = &quot;0&quot; }}
},
FilterExpression = &quot;Price &lt; :val&quot;,
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ProjectionExpression = &quot;Id&quot;
};
You can also optionally limit the page size, or the number of items per page, by adding the optional
Limit parameter. Each time you execute the Scan method, you get one page of results that has the
speciﬁed number of items. To fetch the next page, you execute the Scan method again by providing
the primary key value of the last item in the previous page so that the Scan method can return the next
set of items. You provide this information in the request by setting the ExclusiveStartKey property.
Initially, this property can be null. To retrieve subsequent pages, you must update this property value to
the primary key of the last item in the preceding page.
The following C# code snippet scans the ProductCatalog table. In the request, it speciﬁes the Limit and
ExclusiveStartKey optional parameters. The do/while loop continues to scan one page at time until the
LastEvaluatedKey returns a null value.
Example
Dictionary&lt;string, AttributeValue&gt; lastKeyEvaluated = null;
do
{
var request = new ScanRequest
{
TableName = &quot;ProductCatalog&quot;,
Limit = 10,
ExclusiveStartKey = lastKeyEvaluated
};
var response = client.Scan(request);
foreach (Dictionary&lt;string, AttributeValue&gt; item
in response.Items)
{
PrintItem(item);
}
lastKeyEvaluated = response.LastEvaluatedKey;
} while (lastKeyEvaluated != null &amp;&amp; lastKeyEvaluated.Count != 0);
Example - Scan Using .NET
The following C# code example provides a working sample that scans the ProductCatalog table to ﬁnd
items priced less than 0.
For step-by-step instructions to test the following sample, see .NET Code Samples (p. 287).
using
using
using
using
using
System;
System.Collections.Generic;
Amazon.DynamoDBv2;
Amazon.DynamoDBv2.Model;
Amazon.Runtime;
namespace com.amazonaws.codesamples
{
class LowLevelScan
{
private static AmazonDynamoDBClient client = new AmazonDynamoDBClient();
static void Main(string[] args)
{
try
{
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FindProductsForPriceLessThanZero();
Console.WriteLine(&quot;Example complete. To continue, press Enter&quot;);
Console.ReadLine();
}
}
catch (Exception e)
{
Console.WriteLine(e.Message);
Console.WriteLine(&quot;To continue, press Enter&quot;);
Console.ReadLine();
}
private static void FindProductsForPriceLessThanZero()
{
Dictionary&lt;string, AttributeValue&gt; lastKeyEvaluated = null;
do
{
var request = new ScanRequest
{
TableName = &quot;ProductCatalog&quot;,
Limit = 2,
ExclusiveStartKey = lastKeyEvaluated,
ExpressionAttributeValues = new Dictionary&lt;string, AttributeValue&gt; {
{&quot;:val&quot;, new AttributeValue {
N = &quot;0&quot;
}}
},
FilterExpression = &quot;Price &lt; :val&quot;,
};
ProjectionExpression = &quot;Id, Title, Price&quot;
var response = client.Scan(request);
foreach (Dictionary&lt;string, AttributeValue&gt; item
in response.Items)
{
Console.WriteLine(&quot;\nScanThreadTableUsePaging - printing.....&quot;);
PrintItem(item);
}
lastKeyEvaluated = response.LastEvaluatedKey;
} while (lastKeyEvaluated != null &amp;&amp; lastKeyEvaluated.Count != 0);
}
Console.WriteLine(&quot;To continue, press Enter&quot;);
Console.ReadLine();
private static void PrintItem(
Dictionary&lt;string, AttributeValue&gt; attributeList)
{
foreach (KeyValuePair&lt;string, AttributeValue&gt; kvp in attributeList)
{
string attributeName = kvp.Key;
AttributeValue value = kvp.Value;
Console.WriteLine(
attributeName + &quot; &quot; +
(value.S == null ? &quot;&quot; : &quot;S=[&quot; + value.S + &quot;]&quot;) +
(value.N == null ? &quot;&quot; : &quot;N=[&quot; + value.N + &quot;]&quot;) +
(value.SS == null ? &quot;&quot; : &quot;SS=[&quot; + string.Join(&quot;,&quot;, value.SS.ToArray())
+ &quot;]&quot;) +
(value.NS == null ? &quot;&quot; : &quot;NS=[&quot; + string.Join(&quot;,&quot;, value.NS.ToArray())
+ &quot;]&quot;)
}
);
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}
}
}
Console.WriteLine(&quot;************************************************&quot;);
Example - Parallel Scan Using .NET
The following C# code example demonstrates a parallel scan. The program deletes and then re-creates
the ProductCatalog table, then loads the table with data. When the data load is ﬁnished, the program
spawns multiple threads and issues parallel Scan requests. Finally, the program prints a summary of run
time statistics.
For step-by-step instructions to test the following sample, see .NET Code Samples (p. 287).
using
using
using
using
using
using
using
System;
System.Collections.Generic;
System.Threading;
System.Threading.Tasks;
Amazon.DynamoDBv2;
Amazon.DynamoDBv2.Model;
Amazon.Runtime;
namespace com.amazonaws.codesamples
{
class LowLevelParallelScan
{
private static AmazonDynamoDBClient client = new AmazonDynamoDBClient();
private static string tableName = &quot;ProductCatalog&quot;;
private static int exampleItemCount = 100;
private static int scanItemLimit = 10;
private static int totalSegments = 5;
static void Main(string[] args)
{
try
{
DeleteExampleTable();
CreateExampleTable();
UploadExampleData();
ParallelScanExampleTable();
}
catch (AmazonDynamoDBException e) { Console.WriteLine(e.Message); }
catch (AmazonServiceException e) { Console.WriteLine(e.Message); }
catch (Exception e) { Console.WriteLine(e.Message); }
}
Console.WriteLine(&quot;To continue, press Enter&quot;);
Console.ReadLine();
private static void ParallelScanExampleTable()
{
Console.WriteLine(&quot;\n*** Creating {0} Parallel Scan Tasks to scan {1}&quot;,
totalSegments, tableName);
Task[] tasks = new Task[totalSegments];
for (int segment = 0; segment &lt; totalSegments; segment++)
{
int tmpSegment = segment;
Task task = Task.Factory.StartNew(() =&gt;
{
ScanSegment(totalSegments, tmpSegment);
});
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}
tasks[segment] = task;
Console.WriteLine(&quot;All scan tasks are created, waiting for them to
complete.&quot;);
Task.WaitAll(tasks);
}
Console.WriteLine(&quot;All scan tasks are completed.&quot;);
private static void ScanSegment(int totalSegments, int segment)
{
Console.WriteLine(&quot;*** Starting to Scan Segment {0} of {1} out of {2} total
segments ***&quot;, segment, tableName, totalSegments);
Dictionary&lt;string, AttributeValue&gt; lastEvaluatedKey = null;
int totalScannedItemCount = 0;
int totalScanRequestCount = 0;
do
{
var request = new ScanRequest
{
TableName = tableName,
Limit = scanItemLimit,
ExclusiveStartKey = lastEvaluatedKey,
Segment = segment,
TotalSegments = totalSegments
};
var response = client.Scan(request);
lastEvaluatedKey = response.LastEvaluatedKey;
totalScanRequestCount++;
totalScannedItemCount += response.ScannedCount;
foreach (var item in response.Items)
{
Console.WriteLine(&quot;Segment: {0}, Scanned Item with Title: {1}&quot;,
segment, item[&quot;Title&quot;].S);
}
} while (lastEvaluatedKey.Count != 0);
Console.WriteLine(&quot;*** Completed Scan Segment {0} of {1}.
TotalScanRequestCount: {2}, TotalScannedItemCount: {3} ***&quot;, segment, tableName,
totalScanRequestCount, totalScannedItemCount);
}
private static void UploadExampleData()
{
Console.WriteLine(&quot;\n*** Uploading {0} Example Items to {1} Table***&quot;,
exampleItemCount, tableName);
Console.Write(&quot;Uploading Items: &quot;);
for (int itemIndex = 0; itemIndex &lt; exampleItemCount; itemIndex++)
{
Console.Write(&quot;{0}, &quot;, itemIndex);
CreateItem(itemIndex.ToString());
}
Console.WriteLine();
}
private static void CreateItem(string itemIndex)
{
var request = new PutItemRequest
{
TableName = tableName,
Item = new Dictionary&lt;string, AttributeValue&gt;()
{
{ &quot;Id&quot;, new AttributeValue {
N = itemIndex
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}},
{ &quot;Title&quot;, new AttributeValue {
S = &quot;Book &quot; + itemIndex + &quot; Title&quot;
}},
{ &quot;ISBN&quot;, new AttributeValue {
S = &quot;11-11-11-11&quot;
}},
{ &quot;Authors&quot;, new AttributeValue {
SS = new List&lt;string&gt;{&quot;Author1&quot;, &quot;Author2&quot; }
}},
{ &quot;Price&quot;, new AttributeValue {
N = &quot;20.00&quot;
}},
{ &quot;Dimensions&quot;, new AttributeValue {
S = &quot;8.5x11.0x.75&quot;
}},
{ &quot;InPublication&quot;, new AttributeValue {
BOOL = false
} }
}
}
};
client.PutItem(request);
private static void CreateExampleTable()
{
Console.WriteLine(&quot;\n*** Creating {0} Table ***&quot;, tableName);
var request = new CreateTableRequest
{
AttributeDefinitions = new List&lt;AttributeDefinition&gt;()
{
new AttributeDefinition
{
AttributeName = &quot;Id&quot;,
AttributeType = &quot;N&quot;
}
},
KeySchema = new List&lt;KeySchemaElement&gt;
{
new KeySchemaElement
{
AttributeName = &quot;Id&quot;,
KeyType = &quot;HASH&quot; //Partition key
}
},
ProvisionedThroughput = new ProvisionedThroughput
{
ReadCapacityUnits = 5,
WriteCapacityUnits = 6
},
TableName = tableName
};
var response = client.CreateTable(request);
var result = response;
var tableDescription = result.TableDescription;
Console.WriteLine(&quot;{1}: {0} \t ReadsPerSec: {2} \t WritesPerSec: {3}&quot;,
tableDescription.TableStatus,
tableDescription.TableName,
tableDescription.ProvisionedThroughput.ReadCapacityUnits,
tableDescription.ProvisionedThroughput.WriteCapacityUnits);
string status = tableDescription.TableStatus;
Console.WriteLine(tableName + &quot; - &quot; + status);
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WaitUntilTableReady(tableName);
}
private static void DeleteExampleTable()
{
try
{
Console.WriteLine(&quot;\n*** Deleting {0} Table ***&quot;, tableName);
var request = new DeleteTableRequest
{
TableName = tableName
};
var response = client.DeleteTable(request);
var result = response;
Console.WriteLine(&quot;{0} is being deleted...&quot;, tableName);
WaitUntilTableDeleted(tableName);
}
catch (ResourceNotFoundException)
{
Console.WriteLine(&quot;{0} Table delete failed: Table does not exist&quot;,
tableName);
}
}
private static void WaitUntilTableReady(string tableName)
{
string status = null;
// Let us wait until table is created. Call DescribeTable.
do
{
System.Threading.Thread.Sleep(5000); // Wait 5 seconds.
try
{
var res = client.DescribeTable(new DescribeTableRequest
{
TableName = tableName
});
Console.WriteLine(&quot;Table name: {0}, status: {1}&quot;,
res.Table.TableName,
res.Table.TableStatus);
status = res.Table.TableStatus;
}
}
catch (ResourceNotFoundException)
{
// DescribeTable is eventually consistent. So you might
// get resource not found. So we handle the potential exception.
}
} while (status != &quot;ACTIVE&quot;);
private static void WaitUntilTableDeleted(string tableName)
{
string status = null;
// Let us wait until table is deleted. Call DescribeTable.
do
{
System.Threading.Thread.Sleep(5000); // Wait 5 seconds.
try
{
var res = client.DescribeTable(new DescribeTableRequest
{
TableName = tableName
});
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Console.WriteLine(&quot;Table name: {0}, status: {1}&quot;,
res.Table.TableName,
res.Table.TableStatus);
status = res.Table.TableStatus;
tableName);
}
catch (ResourceNotFoundException)
{
Console.WriteLine(&quot;Table name: {0} is not found. It is deleted&quot;,
}
}
}
return;
}
} while (status == &quot;DELETING&quot;);
Improving Data Access with Secondary Indexes
Topics
• Global Secondary Indexes (p. 448)
• Local Secondary Indexes (p. 484)
Amazon DynamoDB provides fast access to items in a table by specifying primary key values. However,
many applications might beneﬁt from having one or more secondary (or alternate) keys available, to
allow eﬃcient access to data with attributes other than the primary key. To address this, you can create
one or more secondary indexes on a table, and issue Query or Scan requests against these indexes.
A secondary index is a data structure that contains a subset of attributes from a table, along with an
alternate key to support Query operations. You can retrieve data from the index using a Query, in much
the same way as you use Query with a table. A table can have multiple secondary indexes, which gives
your applications access to many diﬀerent query patterns.
Note
You can also Scan an index, in much the same way as you would Scan a table.
Every secondary index is associated with exactly one table, from which it obtains its data. This is called
the base table for the index. When you create an index, you deﬁne an alternate key for the index
(partition key and sort key). You also deﬁne the attributes that you want to be projected, or copied, from
the base table into the index. DynamoDB copies these attributes into the index, along with the primary
key attributes from the base table. You can then query or scan the index just as you would query or scan
a table.
Every secondary index is automatically maintained by DynamoDB. When you add, modify, or delete
items in the base table, any indexes on that table are also updated to reﬂect these changes.
DynamoDB supports two types of secondary indexes:
• Global secondary index — an index with a partition key and a sort key that can be diﬀerent from
those on the base table. A global secondary index is considered &quot;global&quot; because queries on the index
can span all of the data in the base table, across all partitions.
• Local secondary index — an index that has the same partition key as the base table, but a diﬀerent
sort key. A local secondary index is &quot;local&quot; in the sense that every partition of a local secondary index is
scoped to a base table partition that has the same partition key value.
You should consider your application's requirements when you determine which type of index to use.
The following table shows the main diﬀerences between a global secondary index and a local secondary
index:
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Characteristic
Global Secondary Index
Local Secondary Index
Key Schema
The primary key of a global
secondary index can be either
simple (partition key) or
composite (partition key and
sort key).
The primary key of a local
secondary index must be
composite (partition key and
sort key).
Key Attributes
The index partition key and sort
key (if present) can be any base
table attributes of type string,
number, or binary.
The partition key of the index
is the same attribute as the
partition key of the base table.
The sort key can be any base
table attribute of type string,
number, or binary.
Size Restrictions Per Partition
Key Value
There are no size restrictions for
global secondary indexes.
For each partition key value, the
total size of all indexed items
must be 10 GB or less.
Online Index Operations
Global secondary indexes can
be created at the same time
that you create a table. You
can also add a new global
secondary index to an existing
table, or delete an existing
global secondary index.
For more information, see
Managing Global Secondary
Indexes (p. 455).
Local secondary indexes are
created at the same time that
you create a table. You cannot
add a local secondary index
to an existing table, nor can
you delete any local secondary
indexes that currently exist.
Queries and Partitions
A global secondary index lets
you query over the entire table,
across all partitions.
A local secondary index lets you
query over a single partition, as
speciﬁed by the partition key
value in the query.
Read Consistency
Queries on global secondary
indexes support eventual
consistency only.
When you query a local
secondary index, you can choose
either eventual consistency or
strong consistency.
Provisioned Throughput
Consumption
Every global secondary index
has its own provisioned
throughput settings for read and
write activity. Queries or scans
on a global secondary index
consume capacity units from the
index, not from the base table.
The same holds true for global
secondary index updates due to
table writes.
Queries or scans on a local
secondary index consume read
capacity units from the base
table. When you write to a table,
its local secondary indexes are
also updated; these updates
consume write capacity units
from the base table.
Projected Attributes
With global secondary index
queries or scans, you can only
request the attributes that
are projected into the index.
DynamoDB will not fetch any
attributes from the table.
If you query or scan a local
secondary index, you can
request attributes that are
not projected in to the index.
DynamoDB will automatically
fetch those attributes from the
table.
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If you want to create more than one table with secondary indexes, you must do so sequentially. For
example, you would create the ﬁrst table and wait for it to become ACTIVE, create the next table and
wait for it to become ACTIVE, and so on. If you attempt to concurrently create more than one table with a
secondary index, DynamoDB will return a LimitExceededException.
For each secondary index, you must specify the following:
• The type of index to be created – either a global secondary index or a local secondary index.
• A name for the index. The naming rules for indexes are the same as those for tables, as listed in Limits
in DynamoDB (p. 724). The name must be unique for the base table it is associated with, but you can
use the same name for indexes that are associated with diﬀerent base tables.
• The key schema for the index. Every attribute in the index key schema must be a top-level attribute of
type String, Number, or Binary. Other data types, including documents and sets, are not allowed. Other
requirements for the key schema depend on the type of index:
• For a global secondary index, the partition key can be any scalar attribute of the base table. A sort
key is optional, and it too can be any scalar attribute of the base table.
• For a local secondary index, the partition key must be the same as the base table's partition key, and
the sort key must be a non-key base table attribute.
• Additional attributes, if any, to project from the base table into the index. These attributes are in
addition to the table's key attributes, which are automatically projected into every index. You can
project attributes of any data type, including scalars, documents, and sets.
• The provisioned throughput settings for the index, if necessary:
• For a global secondary index, you must specify read and write capacity unit settings. These
provisioned throughput settings are independent of the base table's settings.
• For a local secondary index, you do not need to specify read and write capacity unit settings. Any
read and write operations on a local secondary index draw from the provisioned throughput settings
of its base table.
For maximum query ﬂexibility, you can create up to 5 global secondary indexes and up to 5 local
secondary indexes per table.
To get a detailed listing of secondary indexes on a table, use the DescribeTable operation.
DescribeTable will return the name, storage size and item counts for every secondary index on the table.
These values are not updated in real time, but they are refreshed approximately every six hours.
You can access the data in a secondary index using either the Query or Scan operation. You must specify
the name of the base table and the name of the index that you want to use, the attributes to be returned
in the results, and any condition expressions or ﬁlters that you want to apply. DynamoDB can return the
results in ascending or descending order.
When you delete a table, all of the indexes associated with that table are also deleted.
For best practices, see Best Practices for Local Secondary Indexes (p. 675) and Best Practices for Global
Secondary Indexes (p. 677), respectively.
Global Secondary Indexes
Topics
• Attribute Projections (p. 451)
• Querying a Global Secondary Index (p. 452)
• Scanning a Global Secondary Index (p. 453)
• Data Synchronization Between Tables and Global Secondary Indexes (p. 453)
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• Provisioned Throughput Considerations for Global Secondary Indexes (p. 454)
• Storage Considerations for Global Secondary Indexes (p. 455)
• Managing Global Secondary Indexes (p. 455)
• Working with Global Secondary Indexes: Java (p. 467)
• Working with Global Secondary Indexes: .NET (p. 474)
Some applications might need to perform many kinds of queries, using a variety of diﬀerent attributes
as query criteria. To support these requirements, you can create one or more global secondary indexes
and issue Query requests against these indexes. To illustrate, consider a table named GameScores that
keeps track of users and scores for a mobile gaming application. Each item in GameScores is identiﬁed
by a partition key (UserId) and a sort key (GameTitle). The following diagram shows how the items in the
table would be organized. (Not all of the attributes are shown)
Now suppose that you wanted to write a leaderboard application to display top scores for each game.
A query that speciﬁed the key attributes (UserId and GameTitle) would be very eﬃcient; however, if the
application needed to retrieve data from GameScores based on GameTitle only, it would need to use
a Scan operation. As more items are added to the table, scans of all the data would become slow and
ineﬃcient, making it diﬃcult to answer questions such as these:
• What is the top score ever recorded for the game Meteor Blasters?
• Which user had the highest score for Galaxy Invaders?
• What was the highest ratio of wins vs. losses?
To speed up queries on non-key attributes, you can create a global secondary index. A global secondary
index contains a selection of attributes from the base table, but they are organized by a primary key that
is diﬀerent from that of the table. The index key does not need to have any of the key attributes from
the table; it doesn't even need to have the same key schema as a table.
For example, you could create a global secondary index named GameTitleIndex, with a partition key of
GameTitle and a sort key of TopScore. Since the base table's primary key attributes are always projected
into an index, the UserId attribute is also present. The following diagram shows what GameTitleIndex
index would look like:
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Now you can query GameTitleIndex and easily obtain the scores for Meteor Blasters. The results are
ordered by the sort key values, TopScore. If you set the ScanIndexForward parameter to false, the results
are returned in descending order, so the highest score is returned ﬁrst.
Every global secondary index must have a partition key, and can have an optional sort key. The index
key schema can be diﬀerent from the base table schema; you could have a table with a simple primary
key (partition key), and create a global secondary index with a composite primary key (partition key and
sort key) — or vice-versa. The index key attributes can consist of any top-level String, Number, or Binary
attributes from the base table; other scalar types, document types, and set types are not allowed.
You can project other base table attributes into the index if you want. When you query the index,
DynamoDB can retrieve these projected attributes eﬃciently; however, global secondary index queries
cannot fetch attributes from the base table. For example, if you queried GameTitleIndex, as shown in
the diagram above, the query would not be able to access any non-key attributes other than TopScore
(though the key attributes GameTitle and UserId would automatically be projected).
In a DynamoDB table, each key value must be unique. However, the key values in a global secondary
index do not need to be unique. To illustrate, suppose that a game named Comet Quest is especially
diﬃcult, with many new users trying but failing to get a score above zero. Here is some data that we
could use to represent this:
UserId
GameTitle
TopScore
123
Comet Quest
0
201
Comet Quest
0
301
Comet Quest
0
When this data is added to the GameScores table, DynamoDB will propagate it to GameTitleIndex. If
we then query the index using Comet Quest for GameTitle and 0 for TopScore, the following data is
returned:
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Only the items with the speciﬁed key values appear in the response; within that set of data, the items are
in no particular order.
A global secondary index only keeps track of data items where its key attribute(s) actually exist. For
example, suppose that you added another new item to the GameScores table, but only provided the
required primary key attributes:
UserId
GameTitle
400
Comet Quest
Because you didn't specify the TopScore attribute, DynamoDB would not propagate this item to
GameTitleIndex. Thus, if you queried GameScores for all the Comet Quest items, you would get the
following four items:
A similar query on GameTitleIndex would still return three items, rather than four. This is because the
item with the nonexistent TopScore is not propagated to the index:
Attribute Projections
A projection is the set of attributes that is copied from a table into a secondary index. The partition key
and sort key of the table are always projected into the index; you can project other attributes to support
your application's query requirements. When you query an index, Amazon DynamoDB can access any
attribute in the projection as if those attributes were in a table of their own.
When you create a secondary index, you need to specify the attributes that will be projected into the
index. DynamoDB provides three diﬀerent options for this:
• KEYS_ONLY – Each item in the index consists only of the table partition key and sort key values, plus
the index key values. The KEYS_ONLY option results in the smallest possible secondary index.
• INCLUDE – In addition to the attributes described in KEYS_ONLY, the secondary index will include other
non-key attributes that you specify.
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• ALL – The secondary index includes all of the attributes from the source table. Because all of the table
data is duplicated in the index, an ALL projection results in the largest possible secondary index.
In the diagram above, GameTitleIndex does not have any additional projected attributes. An application
can use GameTitle and TopScore in queries; however, it is not possible to eﬃciently determine which user
has the highest score for a particular game, or the highest ratio of wins vs. losses. The most eﬃcient way
to support queries on this data would be to project these attributes from the base table into the global
secondary index, as shown in this diagram:
Because the non-key attributes Wins and Losses are projected into the index, an application can
determine the wins vs. losses ratio for any game, or for any combination of game and user ID.
When you choose the attributes to project into a global secondary index, you must consider the tradeoﬀ
between provisioned throughput costs and storage costs:
• If you need to access just a few attributes with the lowest possible latency, consider projecting only
those attributes into a global secondary index. The smaller the index, the less that it will cost to store
it, and the less your write costs will be.
• If your application will frequently access some non-key attributes, you should consider projecting
those attributes into a global secondary index. The additional storage costs for the global secondary
index will oﬀset the cost of performing frequent table scans.
• If you need to access most of the non-key attributes on a frequent basis, you can project these
attributes—or even the entire base table— into a global secondary index. This will give you maximum
ﬂexibility; however, your storage cost would increase, or even double.
• If your application needs to query a table infrequently, but must perform many writes or updates
against the data in the table, consider projecting KEYS_ONLY. The global secondary index would be of
minimal size, but would still be available when needed for query activity.
Querying a Global Secondary Index
You can use the Query operation to access one or more items in a global secondary index. The query
must specify the name of the base table and the name of the index that you want to use, the attributes
to be returned in the query results, and any query conditions that you want to apply. DynamoDB can
return the results in ascending or descending order.
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Consider the following data returned from a Query that requests gaming data for a leaderboard
application:
{
}
&quot;TableName&quot;: &quot;GameScores&quot;,
&quot;IndexName&quot;: &quot;GameTitleIndex&quot;,
&quot;KeyConditionExpression&quot;: &quot;GameTitle = :v_title&quot;,
&quot;ExpressionAttributeValues&quot;: {
&quot;:v_title&quot;: {&quot;S&quot;: &quot;Meteor Blasters&quot;}
},
&quot;ProjectionExpression&quot;: &quot;UserId, TopScore&quot;,
&quot;ScanIndexForward&quot;: false
In this query:
• DynamoDB accesses GameTitleIndex, using the GameTitle partition key to locate the index items
for Meteor Blasters. All of the index items with this key are stored adjacent to each other for rapid
retrieval.
• Within this game, DynamoDB uses the index to access all of the user IDs and top scores for this game.
• The results are returned, sorted in descending order because the ScanIndexForward parameter is set to
false.
Scanning a Global Secondary Index
You can use the Scan operation to retrieve all of the data from a global secondary index. You must
provide the base table name and the index name in the request. With a Scan, DynamoDB reads all of
the data in the index and returns it to the application. You can also request that only some of the data
be returned, and that the remaining data should be discarded. To do this, use the FilterExpression
parameter of the Scan operation. For more information, see Filter Expressions for Scan (p. 427).
Data Synchronization Between Tables and Global Secondary
Indexes
DynamoDB automatically synchronizes each global secondary index with its base table. When an
application writes or deletes items in a table, any global secondary indexes on that table are updated
asynchronously, using an eventually consistent model. Applications never write directly to an index.
However, it is important that you understand the implications of how DynamoDB maintains these
indexes.
When you create a global secondary index, you specify one or more index key attributes and their
data types. This means that whenever you write an item to the base table, the data types for those
attributes must match the index key schema's data types. In the case of GameTitleIndex, the GameTitle
partition key in the index is deﬁned as a String data type, and the TopScore sort key in the index is of
type Number. If you attempt to add an item to the GameScores table and specify a diﬀerent data type
for either GameTitle or TopScore, DynamoDB will return a ValidationException because of the data type
mismatch.
When you put or delete items in a table, the global secondary indexes on that table are updated in an
eventually consistent fashion. Changes to the table data are propagated to the global secondary indexes
within a fraction of a second, under normal conditions. However, in some unlikely failure scenarios,
longer propagation delays might occur. Because of this, your applications need to anticipate and handle
situations where a query on a global secondary index returns results that are not up-to-date.
If you write an item to a table, you don't have to specify the attributes for any global secondary index
sort key. Using GameTitleIndex as an example, you would not need to specify a value for the TopScore
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attribute in order to write a new item to the GameScores table. In this case, Amazon DynamoDB does not
write any data to the index for this particular item.
A table with many global secondary indexes will incur higher costs for write activity than tables with
fewer indexes. For more information, see Provisioned Throughput Considerations for Global Secondary
Indexes (p. 454).
Provisioned Throughput Considerations for Global Secondary
Indexes
When you create a global secondary index, you must specify read and write capacity units for the
expected workload on that index. The provisioned throughput settings of a global secondary index are
separate from those of its base table. A Query operation on a global secondary index consumes read
capacity units from the index, not the base table. When you put, update or delete items in a table, the
global secondary indexes on that table are also updated; these index updates consume write capacity
units from the index, not from the base table.
For example, if you Query a global secondary index and exceed its provisioned read capacity, your request
will be throttled. If you perform heavy write activity on the table, but a global secondary index on that
table has insuﬃcient write capacity, then the write activity on the table will be throttled.
To view the provisioned throughput settings for a global secondary index, use the DescribeTable
operation; detailed information about all of the table's global secondary indexes will be returned.
Read Capacity Units
Global secondary indexes support eventually consistent reads, each of which consume one half of a read
capacity unit. This means that a single global secondary index query can retrieve up to 2 &times; 4 KB = 8 KB
per read capacity unit.
For global secondary index queries, DynamoDB calculates the provisioned read activity in the same way
as it does for queries against tables. The only diﬀerence is that the calculation is based on the sizes of
the index entries, rather than the size of the item in the base table. The number of read capacity units
is the sum of all projected attribute sizes across all of the items returned; the result is then rounded up
to the next 4 KB boundary. For more information on how DynamoDB calculates provisioned throughput
usage, see Throughput Settings for Reads and Writes (p. 294).
The maximum size of the results returned by a Query operation is 1 MB; this includes the sizes of all the
attribute names and values across all of the items returned.
For example, consider a global secondary index where each item contains 2000 bytes of data. Now
suppose that you Query this index and that the query returns 8 items. The total size of the matching
items is 2000 bytes &times; 8 items = 16,000 bytes; this is then rounded up to the nearest 4 KB boundary.
Since global secondary index queries are eventually consistent, the total cost is 0.5 &times; (16 KB / 4 KB), or 2
read capacity units.
Write Capacity Units
When an item in a table is added, updated, or deleted, and a global secondary index is aﬀected by this,
then the global secondary index will consume provisioned write capacity units for the operation. The
total provisioned throughput cost for a write consists of the sum of write capacity units consumed by
writing to the base table and those consumed by updating the global secondary indexes. Note that if a
write to a table does not require a global secondary index update, then no write capacity is consumed
from the index.
In order for a table write to succeed, the provisioned throughput settings for the table and all of its
global secondary indexes must have enough write capacity to accommodate the write; otherwise, the
write to the table will be throttled.
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The cost of writing an item to a global secondary index depends on several factors:
• If you write a new item to the table that deﬁnes an indexed attribute, or you update an existing item
to deﬁne a previously undeﬁned indexed attribute, one write operation is required to put the item into
the index.
• If an update to the table changes the value of an indexed key attribute (from A to B), two writes are
required, one to delete the previous item from the index and another write to put the new item into
the index. • If an item was present in the index, but a write to the table caused the indexed attribute to be deleted,
one write is required to delete the old item projection from the index.
• If an item is not present in the index before or after the item is updated, there is no additional write
cost for the index.
• If an update to the table only changes the value of projected attributes in the index key schema, but
does not change the value of any indexed key attribute, then one write is required to update the values
of the projected attributes into the index.
All of these factors assume that the size of each item in the index is less than or equal to the 1 KB item
size for calculating write capacity units. Larger index entries will require additional write capacity units.
You can minimize your write costs by considering which attributes your queries will need to return and
projecting only those attributes into the index.
Storage Considerations for Global Secondary Indexes
When an application writes an item to a table, DynamoDB automatically copies the correct subset of
attributes to any global secondary indexes in which those attributes should appear. Your AWS account
is charged for storage of the item in the base table and also for storage of attributes in any global
secondary indexes on that table.
The amount of space used by an index item is the sum of the following:
• The size in bytes of the base table primary key (partition key and sort key)
• The size in bytes of the index key attribute
• The size in bytes of the projected attributes (if any)
• 100 bytes of overhead per index item
To estimate the storage requirements for a global secondary index, you can estimate the average size
of an item in the index and then multiply by the number of items in the base table that have the global
secondary index key attributes.
If a table contains an item where a particular attribute is not deﬁned, but that attribute is deﬁned as an
index partition key or sort key, then DynamoDB does not write any data for that item to the index.
Managing Global Secondary Indexes
This section describes how to create, modify, and delete global secondary indexes.
Topics
• Creating a Table With Global Secondary Indexes (p. 456)
• Describing the Global Secondary Indexes on a Table (p. 456)
• Adding a Global Secondary Index To an Existing Table (p. 456)
• Modifying an Index Creation (p. 458)
• Deleting a Global Secondary Index From a Table (p. 459)
• Detecting and Correcting Index Key Violations (p. 459)
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Creating a Table With Global Secondary Indexes
To create a table with one or more global secondary indexes, use the CreateTable operation with the
GlobalSecondaryIndexes parameter. For maximum query ﬂexibility, you can create up to 5 global
secondary indexes per table.
You must specify one attribute to act as the index partition key; you can optionally specify another
attribute for the index sort key. It is not necessary for either of these key attributes to be the
same as a key attribute in the table. For example, in the GameScores table (see Global Secondary
Indexes (p. 448)), neither TopScore nor TopScoreDateTime are key attributes; you could create a global
secondary index with a partition key of TopScore and a sort key of TopScoreDateTime. You might use such
an index to determine whether there is a correlation between high scores and the time of day a game is
played.
Each index key attribute must be a scalar of type String, Number, or Binary. (It cannot be a document
or a set.) You can project attributes of any data type into a global secondary index; this includes scalars,
documents, and sets. For a complete list of data types, see Data Types (p. 12).
You must provide ProvisionedThroughput settings for the index, consisting of ReadCapacityUnits and
WriteCapacityUnits. These provisioned throughput settings are separate from those of the table, but
behave in similar ways. For more information, see Provisioned Throughput Considerations for Global
Secondary Indexes (p. 454).
Describing the Global Secondary Indexes on a Table
To view the status of all the global secondary indexes on a table, use the DescribeTable operation. The
GlobalSecondaryIndexes portion of the response shows all of the indexes on the table, along with the
current status of each ( IndexStatus).
The IndexStatus for a global secondary index will be one of the following:
• CREATING—The index is currently being created, and is not yet available for use.
• ACTIVE—The index is ready for use, and applications can perform Query operations on the index
• UPDATING—The provisioned throughput settings of the index are being changed.
• DELETING—The index is currently being deleted, and can no longer be used.
When DynamoDB has ﬁnished building a global secondary index, the index status changes from
CREATING to ACTIVE.
Adding a Global Secondary Index To an Existing Table
To add a global secondary index to an existing table, use the UpdateTable operation with the
GlobalSecondaryIndexUpdates parameter. You must provide the following:
• An index name. The name must be unique among all the indexes on the table.
• The key schema of the index. You must specify one attribute for the index partition key; you can
optionally specify another attribute for the index sort key. It is not necessary for either of these key
attributes to be the same as a key attribute in the table. The data types for each schema attribute
must be scalar: String, Number, or Binary.
• The attributes to be projected from the table into the index:
• KEYS_ONLY – Each item in the index consists only of the table partition key and sort key values, plus
the index key values.
• INCLUDE – In addition to the attributes described in KEYS_ONLY, the secondary index will include
other non-key attributes that you specify.
• ALL – The index includes all of the attributes from the source table.
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• The provisioned throughput settings for the index, consisting of ReadCapacityUnits
and WriteCapacityUnits. These provisioned throughput settings are separate from those of the table.
You can only create one global secondary index per UpdateTable operation.
Note
You cannot cancel an in-ﬂight global secondary index creation.
Phases of Index Creation
When you add a new global secondary index to an existing table, the table continues to be available
while the index is being built. However, the new index is not available for Query operations until its
status changes from CREATING to ACTIVE.
Behind the scenes, DynamoDB builds the index in two phases:
Resource Allocation
DynamoDB allocates the compute and storage resources that will be needed for building the index.
During the resource allocation phase, the IndexStatus attribute is CREATING and the Backfilling
attribute is false. Use the DescribeTable operation to retrieve the status of a table and all of its
secondary indexes.
While the index is in the resource allocation phase, you cannot delete its parent table; nor can you
modify the provisioned throughput of the index or the table. You cannot add or delete other indexes
on the table; however, you can modify the provisioned throughput of these other indexes.
Backﬁlling
For each item in the table, DynamoDB determines which set of attributes to write to the index
based on its projection (KEYS_ONLY, INCLUDE, or ALL). It then writes these attributes to the index.
During the backﬁll phase, DynamoDB keeps track of items that are being added, deleted, or updated
in the table. The attributes from these items are also added, deleted, or updated in the index as
appropriate.
During the backﬁlling phase, the IndexStatus attribute is CREATING and the Backfilling attribute
is true. Use the DescribeTable operation to retrieve the status of a table and all of its secondary
indexes.
While the index is backﬁlling, you cannot delete its parent table. However, you can still modify the
provisioned throughput of the table and any of its global secondary indexes.
Note
During the backﬁlling phase, some writes of violating items may succeed while others will
be rejected. After backﬁlling, all writes to items that violate the new index's key schema
will be rejected. We recommend that you run the Violation Detector tool after the backﬁll
phase completes, to detect and resolve any key violations that may have occurred. For more
information, see Detecting and Correcting Index Key Violations (p. 459).
While the resource allocation and backﬁlling phases are in progress, the index is in the CREATING state.
During this time, DynamoDB performs read operations on the table; you will not be charged for this read
activity.
When the index build is complete, its status changes to ACTIVE. You will not be able to Query or Scan the
index until it is ACTIVE.
Note
In some cases, DynamoDB will not be able to write data from the table to the index due to index
key violations. This can occur if the data type of an attribute value does not match the data type
of an index key schema data type, or if the size of an attribute exceeds the maximum length
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for an index key attribute. Index key violations do not interfere with global secondary index
creation; however, when the index becomes ACTIVE, the violating keys will not be present in the
index.
DynamoDB provides a standalone tool for ﬁnding and resolving these issues. For more
information, see Detecting and Correcting Index Key Violations (p. 459).
Adding a Global Secondary Index To a Large Table
The time required for building a global secondary index depends on several factors, such as:
• The size of the table
• The number of items in the table that qualify for inclusion in the index
• The number of attributes projected into the index
• The provisioned write capacity of the index
• Write activity on the main table during index builds.
If you are adding a global secondary index to a very large table, it might take a long time for the creation
process to complete. To monitor progress and determine whether the index has suﬃcient write capacity,
consult the following Amazon CloudWatch metrics:
• OnlineIndexPercentageProgress
• OnlineIndexConsumedWriteCapacity
• OnlineIndexThrottleEvents
Note
For more information on CloudWatch metrics related to DynamoDB, see DynamoDB
Metrics (p. 637).
If the provisioned write throughput setting on the index is too low, the index build will take longer
to complete. To shorten the time it takes to build a new global secondary index, you can increase its
provisioned write capacity temporarily.
Note
As a general rule, we recommend setting the provisioned write capacity of the index to 1.5 times
the write capacity of the table. This is a good setting for many use cases; however, your actual
requirements may be higher or lower.
While an index is being backﬁlled, DynamoDB uses internal system capacity to read from the table. This
is to minimize the impact of the index creation and to assure that your table does not run out of read
capacity.
However, it is possible that the volume of incoming write activity might exceed the provisioned write
capacity of the index. This is a bottleneck scenario, in which the index creation takes more time because
the write activity to the index is throttled. During the index build, we recommend that you monitor
the Amazon CloudWatch metrics for the index to determine whether its consumed write capacity is
exceeding its provisioned capacity. In a bottleneck scenario, you should increase the provisioned write
capacity on the index to avoid write throttling during the backﬁll phase.
After the index has been created, you should set its provisioned write capacity to reﬂect the normal
usage of your application.
Modifying an Index Creation
While an index is being built, you can use the DescribeTable operation to determine what phase it
is in. The description for the index includes a Boolean attribute, Backfilling, to indicate whether
DynamoDB is currently loading the index with items from the table. If Backfilling is true, then the
resource allocation phase is complete and the index is now backﬁlling.
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While the backﬁll is proceeding, you can update the provisioned throughput parameters for the index.
You might decide to do this in order to speed up the index build: You can increase the write capacity of
the index while it is being built, and then decrease it afterward. To modify the provisioned throughput
settings of the index, use the UpdateTable operation. The index status will change to UPDATING, and
Backfilling will be true until the index is ready for use.
During the backﬁlling phase, you cannot add or delete other indexes on the table.
Note
For indexes that were created as part of a CreateTable operation, the Backfilling attribute
does not appear in the DescribeTable output. For more information, see Phases of Index
Creation (p. 457).
Deleting a Global Secondary Index From a Table
If you no longer need a global secondary index, you can delete it using the UpdateTable operation.
You can only delete one global secondary index per UpdateTable operation.
While the global secondary index, is being deleted, there is no eﬀect on any read or write activity in the
parent table. While the deletion is in progress, you can still modify the provisioned throughput on other
indexes
Note
When you delete a table using the DeleteTable action, all of the global secondary indexes on
that table are also deleted. Detecting and Correcting Index Key Violations
During the backﬁll phase of global secondary index creation, DynamoDB examines each item in the table
to determine whether it is eligible for inclusion in the index. Some items might not be eligible because
they would cause index key violations. In these cases, the items will remain in the table, but the index
will not have a corresponding entry for that item.
An index key violation occurs if:
• There is a data type mismatch between an attribute value and the index key schema data type. For
example, suppose one of the items in the GameScores table had a TopScore value of type String. If you
added a global secondary index with a partition key of TopScore, of type Number, the item from the
table would violate the index key.
• An attribute value from the table exceeds the maximum length for an index key attribute. The
maximum length of a partition key is 2048 bytes, and the maximum length of a sort key is 1024 bytes.
If any of the corresponding attribute values in the table exceed these limits, the item from the table
would violate the index key.
If an index key violation occurs, the backﬁll phase continues without interruption; however, any violating
items are not included in the index. After the backﬁll phase completes, all writes to items that violate the
new index's key schema will be rejected.
To identify and ﬁx attribute values in a table that violate an index key, use the Violation Detector tool. To
run Violation Detector, you create a conﬁguration ﬁle that speciﬁes the name of a table to be scanned,
the names and data types of the global secondary index partition key and sort key, and what actions to
take if any index key violations are found. Violation Detector can run in one of two diﬀerent modes:
• Detection mode—detect index key violations. Use detection mode to report the items in the table that
would cause key violations in a global secondary index. (You can optionally request that these violating
table items be deleted immediately when they are found.) The output from detection mode is written
to a ﬁle, which you can use for further analysis.
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• Correction mode— correct index key violations. In correction mode, Violation Detector reads an input
ﬁle with the same format as the output ﬁle from detection mode. Correction mode reads the records
from the input ﬁle and, for each record, it either deletes or updates the corresponding items in the
table. (Note that if you choose to update the items, you must edit the input ﬁle and set appropriate
values for these updates.)
Downloading and Running Violation Detector
Violation Detector is available as an executable Java archive (.jar ﬁle), and will run on Windows, Mac, or
Linux computers. Violation Detector requires Java 1.7 (or above) and Maven.
• https://github.com/awslabs/dynamodb-online-index-violation-detector
Follow the instructions in the README.md ﬁle to download and install Violation Detector using Maven
To start Violation Detector, go to the directory where you have built ViolationDetector.java and enter
the following command:
java -jar ViolationDetector.jar [options]
The Violation Detector command line accepts the following options:
• -h | --help — Prints a usage summary and options for Violation Detector.
• -p | --configFilePath value — The fully qualiﬁed name of a Violation Detector conﬁguration ﬁle.
For more information, see The Violation Detector Conﬁguration File (p. 460) .
• -t | --detect value — Detect index key violations in the table, and write them to the Violation
Detector output ﬁle. If the value of this parameter is set to keep, items with key violations will not be
modiﬁed. If the value is set to delete, items with key violations will be deleted from the table.
• -c | --correct value — Read index key violations from an input ﬁle, and take corrective actions on
the items in the table. If the value of this parameter is set to update, items with key violations will be
updated with new, non-violating values. If the value is set to delete, items with key violations will be
deleted from the table.
The Violation Detector Conﬁguration File
At runtime, the Violation Detector tool requires a conﬁguration ﬁle. The parameters in this ﬁle determine
which DynamoDB resources that Violation Detector can access, and how much provisioned throughput it
can consume. The following table describes these parameters.
Parameter Name
Description
Required?
awsCredentialsFile
The fully qualiﬁed name of a ﬁle Yes
containing your AWS credentials.
The credentials ﬁle must be in
the following format:
accessKey
= access_key_id_goes_here
secretKey
= secret_key_goes_here
dynamoDBRegion
The AWS region in which the
table resides. For example: uswest-2.
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Parameter Name
Description
Required?
tableName
The name of the DynamoDB
table to be scanned.
Yes
gsiHashKeyName
The name of the index partition
key.
Yes
gsiHashKeyType
The data type of the index
partition key—String, Number,
or Binary:
Yes
S | N | B
gsiRangeKeyName
The name of the index sort key.
Do not specify this parameter
if the index only has a simple
primary key (partition key).
No
gsiRangeKeyType
The data type of the index sort
key—String, Number, or Binary:
No
S | N | B
Do not specify this parameter
if the index only has a simple
primary key (partition key).
recordDetails
Whether to write the full details
of index key violations to the
output ﬁle. If set to true (the
default), full information about
the violating items are reported.
If set to false, only the number
of violations is reported.
recordGsiValueInViolationRecordWhether to write the values
of the violating index keys to
the output ﬁle. If set to true
(default), the key values are
reported. If set to false, the key
values are not reported.
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Parameter Name
Description
Required?
detectionOutputPath
The full path of the Violation
Detector output ﬁle. This
parameter supports writing to
a local directory or to Amazon
Simple Storage Service (Amazon
S3). The following are examples:
No
detectionOutputPath =
//local/path/filename.csv
detectionOutputPath =
s3://bucket/filename.csv
Information in the output ﬁle
appears in CSV format (commaseparated values). If you do
not set detectionOutputPath,
then the output ﬁle is named
violation_detection.csv and is
written to your current working
directory.
numOfSegments
The number of parallel scan
segments to be used when
Violation Detector scans the
table. The default value is 1,
meaning that the table will be
scanned in a sequential manner.
If the value is 2 or higher, then
Violation Detector will divide
the table into that many logical
segments and an equal number
of scan threads.
The maximum setting for
numOfSegments is 4096.
For larger tables, a parallel
scan is generally faster than a
sequential scan. In addition, if
the table is large enough to span
multiple partitions, a parallel
scan will distribute its read
activity evenly across multiple
partitions.
For more information on parallel
scans in DynamoDB, see Parallel
Scan (p. 430).
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Parameter Name
Description
Required?
numOfViolations
The upper limit of index key
violations to write to the output
ﬁle. If set to -1 (the default), the
entire table will be scanned. If
set to a positive integer, then
Violation Detector will stop after
it encounters that number of
violations.
No
numOfRecords
The number of items in the table No
to be scanned. If set to -1 (the
default), the entire table will
be scanned. If set to a positive
integer, then Violation Detector
will stop after it scans that many
items in the table.
readWriteIOPSPercent
Regulates the percentage of
provisioned read capacity units
that are consumed during the
table scan. Valid values range
from 1 to 100. The default
value (25) means that Violation
Detector will consume no
more than 25% of the table's
provisioned read throughput.
No
correctionInputPath
The full path of the Violation
Detector correction input ﬁle.
If you run Violation Detector in
correction mode, the contents
of this ﬁle are used to modify
or delete data items in the
table that violate the global
secondary index.
No
The format of the
correctionInputPath ﬁle
is the same as that of the
detectionOutputPath ﬁle. This
lets you process the output
from detection mode as input in
correction mode.
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Parameter Name
Description
Required?
correctionOutputPath
The full path of the Violation
Detector correction output ﬁle.
This ﬁle is created only if there
are update errors.
No
This parameter supports writing
to a local directory or to Amazon
Simple Storage Service (Amazon
S3). The following are examples:
correctionOutputPath =
//local/path/filename.csv
correctionOutputPath =
s3://bucket/filename.csv
Information in the output ﬁle
appears in CSV format (commaseparated values). If you do
not set correctionOutputPath,
then the output ﬁle is named
violation_update_errors.csv
and is written to your current
working directory.
Detection
To detect index key violations, use Violation Detector with the --detect command line option. To
show how this option works, consider the ProductCatalog table shown in Creating Tables and Loading
Sample Data (p. 280). The following is a list of items in the table; only the primary key (Id) and the Price
attribute are shown.
Id (Primary Key)
Price
101
-2
102
20
103
200
201
100
202
200
203
300
204
400
205
500
Note that all of the values for Price are of type Number. However, because DynamoDB is schemaless, it
is possible to add an item with a non-numeric Price. For example, suppose that we add another item to
the ProductCatalog table:
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Id (Primary Key)
Price
999
&quot;Hello&quot;
The table now has a total of nine items.
Now we will add a new global secondary index to the table: PriceIndex. The primary key for this index is
a partition key, Price, which is of type Number. After the index has been built, it will contain eight items
—but the ProductCatalog table has nine items. The reason for this discrepancy is that the value &quot;Hello&quot;
is of type String, but PriceIndex has a primary key of type Number. The String value violates the global
secondary index key, so it is not present in the index.
To use Violation Detector in this scenario, you ﬁrst create a conﬁguration ﬁle such as the following:
# Properties file for violation detection tool configuration.
# Parameters that are not specified will use default values.
awsCredentialsFile = /home/alice/credentials.txt
dynamoDBRegion = us-west-2
tableName = ProductCatalog
gsiHashKeyName = Price
gsiHashKeyType = N
recordDetails = true
recordGsiValueInViolationRecord = true
detectionOutputPath = ./gsi_violation_check.csv
correctionInputPath = ./gsi_violation_check.csv
numOfSegments = 1
readWriteIOPSPercent = 40
Next, you run Violation Detector as in this example:
$
java -jar ViolationDetector.jar --configFilePath config.txt --detect keep
Violation detection started: sequential scan, Table name: ProductCatalog, GSI name:
PriceIndex
Progress: Items scanned in total: 9,
Items scanned by this thread: 9,
Violations
found by this thread: 1, Violations deleted by this thread: 0
Violation detection finished: Records scanned: 9, Violations found: 1, Violations deleted:
0, see results at: ./gsi_violation_check.csv
If the recordDetails conﬁg parameter is set to true, then Violation Detector writes details of each
violation to the output ﬁle, as in the following example:
Table Hash Key,GSI Hash Key Value,GSI Hash Key Violation Type,GSI Hash Key Violation
Description,GSI Hash Key Update Value(FOR USER),Delete Blank Attributes When Updating?(Y/
N)
999,&quot;{&quot;&quot;S&quot;&quot;:&quot;&quot;Hello&quot;&quot;}&quot;,Type Violation,Expected: N Found: S,,
The output ﬁle is in comma-separated value format (CSV). The ﬁrst line in the ﬁle is a header, followed
by one record per item that violates the index key. The ﬁelds of these violation records are as follows:
• Table Hash Key—the partition key value of the item in the table.
• Table Range Key—the sort key value of the item in the table.
• GSI Hash Key Value—the partition key value of the global secondary index
• GSI Hash Key Violation Type—either Type Violation or Size Violation.
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• GSI Hash Key Violation Description—the cause of the violation.
• GSI Hash Key Update Value(FOR USER)—in correction mode, a new user-supplied value for the
attribute.
• GSI Range Key Value—the sort key value of the global secondary index
• GSI Range Key Violation Type—either Type Violation or Size Violation.
• GSI Range Key Violation Description—the cause of the violation.
• GSI Range Key Update Value(FOR USER)—in correction mode, a new user-supplied value for the
attribute.
• Delete Blank Attribute When Updating(Y/N)—in correction mode, determines whether to delete (Y)
or keep (N) the violating item in the table—but only if either of the following ﬁelds are blank:
• GSI Hash Key Update Value(FOR USER)
• GSI Range Key Update Value(FOR USER)
If either of these ﬁelds are non-blank, then Delete Blank Attribute When Updating(Y/N) has no
eﬀect.
Note
The output format might vary, depending on the conﬁguration ﬁle and command line options.
For example, if the table has a simple primary key (without a sort key), no sort key ﬁelds will be
present in the output.
The violation records in the ﬁle might not be in sorted order.
Correction
To correct index key violations, use Violation Detector with the --correct command line option.
In correction mode, Violation Detector reads the input ﬁle speciﬁed by the correctionInputPath
parameter. This ﬁle has the same format as the detectionOutputPath ﬁle, so that you can use the output
from detection as input for correction.
Violation Detector provides two diﬀerent ways to correct index key violations:
• Delete violations—delete the table items that have violating attribute values.
• Update violations—update the table items, replacing the violating attributes with non-violating
values.
In either case, you can use the output ﬁle from detection mode as input for correction mode.
Continuing with our ProductCatalog example, suppose that we want to delete the violating item from
the table. To do this, we use the following command line:
$
java -jar ViolationDetector.jar --configFilePath config.txt --correct delete
At this point, you are asked to conﬁrm whether you want to delete the violating items.
Are you sure to delete all violations on the table?y/n
y
Confirmed, will delete violations on the table...
Violation correction from file started: Reading records from file: ./
gsi_violation_check.csv, will delete these records from table.
Violation correction from file finished: Violations delete: 1, Violations Update: 0
Now both ProductCatalog and PriceIndex have the same number of items.
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Working with Global Secondary Indexes: Java
You can use the AWS SDK for Java Document API to create a table with one or more global secondary
indexes, describe the indexes on the table and perform queries using the indexes.
The following are the common steps for table operations.
1. Create an instance of the DynamoDB class.
2. Provide the required and optional parameters for the operation by creating the corresponding request
objects.
3. Call the appropriate method provided by the client that you created in the preceding step.
Create a Table With a Global Secondary Index
You can create global secondary indexes at the same time that you create a table. To do this, use
CreateTable and provide your speciﬁcations for one or more global secondary indexes. The following
Java code snippet creates a table to hold information about weather data. The partition key is Location
and the sort key is Date. A global secondary index named PrecipIndex allows fast access to precipitation
data for various locations.
The following are the steps to create a table with a global secondary index, using the DynamoDB
document API.
1. Create an instance of the DynamoDB class.
2. Create an instance of the CreateTableRequest class to provide the request information.
You must provide the table name, its primary key, and the provisioned throughput values. For the
global secondary index, you must provide the index name, its provisioned throughput settings, the
attribute deﬁnitions for the index sort key, the key schema for the index, and the attribute projection.
3. Call the createTable method by providing the request object as a parameter.
The following Java code snippet demonstrates the preceding steps. The snippet creates a table
(WeatherData) with a global secondary index (PrecipIndex). The index partition key is Date and its sort
key is Precipitation. All of the table attributes are projected into the index. Users can query this index to
obtain weather data for a particular date, optionally sorting the data by precipitation amount.
Note that since Precipitation is not a key attribute for the table, it is not required; however, WeatherData
items without Precipitation will not appear in PrecipIndex.
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
DynamoDB dynamoDB = new DynamoDB(client);
// Attribute definitions
ArrayList&lt;AttributeDefinition&gt; attributeDefinitions = new ArrayList&lt;AttributeDefinition&gt;();
attributeDefinitions.add(new AttributeDefinition()
.withAttributeName(&quot;Location&quot;)
.withAttributeType(&quot;S&quot;));
attributeDefinitions.add(new AttributeDefinition()
.withAttributeName(&quot;Date&quot;)
.withAttributeType(&quot;S&quot;));
attributeDefinitions.add(new AttributeDefinition()
.withAttributeName(&quot;Precipitation&quot;)
.withAttributeType(&quot;N&quot;));
// Table key schema
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ArrayList&lt;KeySchemaElement&gt; tableKeySchema = new ArrayList&lt;KeySchemaElement&gt;();
tableKeySchema.add(new KeySchemaElement()
.withAttributeName(&quot;Location&quot;)
.withKeyType(KeyType.HASH)); //Partition key
tableKeySchema.add(new KeySchemaElement()
.withAttributeName(&quot;Date&quot;)
.withKeyType(KeyType.RANGE)); //Sort key
// PrecipIndex
GlobalSecondaryIndex precipIndex = new GlobalSecondaryIndex()
.withIndexName(&quot;PrecipIndex&quot;)
.withProvisionedThroughput(new ProvisionedThroughput()
.withReadCapacityUnits((long) 10)
.withWriteCapacityUnits((long) 1))
.withProjection(new Projection().withProjectionType(ProjectionType.ALL));
ArrayList&lt;KeySchemaElement&gt; indexKeySchema = new ArrayList&lt;KeySchemaElement&gt;();
indexKeySchema.add(new KeySchemaElement()
.withAttributeName(&quot;Date&quot;)
.withKeyType(KeyType.HASH)); //Partition key
indexKeySchema.add(new KeySchemaElement()
.withAttributeName(&quot;Precipitation&quot;)
.withKeyType(KeyType.RANGE)); //Sort key
precipIndex.setKeySchema(indexKeySchema);
CreateTableRequest createTableRequest = new CreateTableRequest()
.withTableName(&quot;WeatherData&quot;)
.withProvisionedThroughput(new ProvisionedThroughput()
.withReadCapacityUnits((long) 5)
.withWriteCapacityUnits((long) 1))
.withAttributeDefinitions(attributeDefinitions)
.withKeySchema(tableKeySchema)
.withGlobalSecondaryIndexes(precipIndex);
Table table = dynamoDB.createTable(createTableRequest);
System.out.println(table.getDescription());
You must wait until DynamoDB creates the table and sets the table status to ACTIVE. After that, you can
begin putting data items into the table.
Describe a Table With a Global Secondary Index
To get information about global secondary indexes on a table, use DescribeTable. For each index, you
can access its name, key schema, and projected attributes.
The following are the steps to access global secondary index information a table.
1. Create an instance of the DynamoDB class.
2. Create an instance of the Table class to represent the index you want to work with.
3. Call the describe method on the Table object.
The following Java code snippet demonstrates the preceding steps.
Example
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
DynamoDB dynamoDB = new DynamoDB(client);
Table table = dynamoDB.getTable(&quot;WeatherData&quot;);
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TableDescription tableDesc = table.describe();
Iterator&lt;GlobalSecondaryIndexDescription&gt; gsiIter =
tableDesc.getGlobalSecondaryIndexes().iterator();
while (gsiIter.hasNext()) {
GlobalSecondaryIndexDescription gsiDesc = gsiIter.next();
System.out.println(&quot;Info for index &quot;
+ gsiDesc.getIndexName() + &quot;:&quot;);
}
Iterator&lt;KeySchemaElement&gt; kseIter = gsiDesc.getKeySchema().iterator();
while (kseIter.hasNext()) {
KeySchemaElement kse = kseIter.next();
System.out.printf(&quot;\t%s: %s\n&quot;, kse.getAttributeName(), kse.getKeyType());
}
Projection projection = gsiDesc.getProjection();
System.out.println(&quot;\tThe projection type is: &quot;
+ projection.getProjectionType());
if (projection.getProjectionType().toString().equals(&quot;INCLUDE&quot;)) {
System.out.println(&quot;\t\tThe non-key projected attributes are: &quot;
+ projection.getNonKeyAttributes());
}
Query a Global Secondary Index
You can use Query on a global secondary index, in much the same way you Query a table. You need to
specify the index name, the query criteria for the index partition key and sort key (if present), and the
attributes that you want to return. In this example, the index is PrecipIndex, which has a partition key of
Date and a sort key of Precipitation. The index query returns all of the weather data for a particular date,
where the precipitation is greater than zero.
The following are the steps to query a global secondary index using the AWS SDK for Java Document
API.
1. Create an instance of the DynamoDB class.
2. Create an instance of the Table class to represent the index you want to work with.
3. Create an instance of the Index class for the index you want to query.
4. Call the query method on the Index object.
The attribute name Date is a DynamoDB reserved word. Therefore, we must use an expression attribute
name as a placeholder in the KeyConditionExpression.
The following Java code snippet demonstrates the preceding steps.
Example
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
DynamoDB dynamoDB = new DynamoDB(client);
Table table = dynamoDB.getTable(&quot;WeatherData&quot;);
Index index = table.getIndex(&quot;PrecipIndex&quot;);
QuerySpec spec = new QuerySpec()
.withKeyConditionExpression(&quot;#d = :v_date and Precipitation = :v_precip&quot;)
.withNameMap(new NameMap()
.with(&quot;#d&quot;, &quot;Date&quot;))
.withValueMap(new ValueMap()
.withString(&quot;:v_date&quot;,&quot;2013-08-10&quot;)
.withNumber(&quot;:v_precip&quot;,0));
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ItemCollection&lt;QueryOutcome&gt; items = index.query(spec);
Iterator&lt;Item&gt; iter = items.iterator();
while (iter.hasNext()) {
System.out.println(iter.next().toJSONPretty());
}
Example: Global Secondary Indexes Using the AWS SDK for Java Document API
The following Java code example shows how to work with global secondary indexes. The example
creates a table named Issues, which might be used in a simple bug tracking system for software
development. The partition key is IssueId and the sort key is Title. There are three global secondary
indexes on this table:
• CreateDateIndex—the partition key is CreateDate and the sort key is IssueId. In addition to the table
keys, the attributes Description and Status are projected into the index.
• TitleIndex—the partition key is IssueId and the sort key is Title. No attributes other than the table
keys are projected into the index.
• DueDateIndex—the partition key is DueDate, and there is no sort key. All of the table attributes are
projected into the index.
After the Issues table is created, the program loads the table with data representing software bug
reports, and then queries the data using the global secondary indexes. Finally, the program deletes the
Issues table.
For step-by-step instructions to test the following sample, see Java Code Samples (p. 285).
Example
// Copyright 2012-2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
// Licensed under the Apache License, Version 2.0.
package com.amazonaws.codesamples.document;
import java.util.ArrayList;
import java.util.Iterator;
import
import
import
import
import
import
import
import
import
import
import
import
import
import
import
import
import
com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;
com.amazonaws.services.dynamodbv2.document.DynamoDB;
com.amazonaws.services.dynamodbv2.document.Index;
com.amazonaws.services.dynamodbv2.document.Item;
com.amazonaws.services.dynamodbv2.document.ItemCollection;
com.amazonaws.services.dynamodbv2.document.QueryOutcome;
com.amazonaws.services.dynamodbv2.document.Table;
com.amazonaws.services.dynamodbv2.document.spec.QuerySpec;
com.amazonaws.services.dynamodbv2.document.utils.ValueMap;
com.amazonaws.services.dynamodbv2.model.AttributeDefinition;
com.amazonaws.services.dynamodbv2.model.CreateTableRequest;
com.amazonaws.services.dynamodbv2.model.GlobalSecondaryIndex;
com.amazonaws.services.dynamodbv2.model.KeySchemaElement;
com.amazonaws.services.dynamodbv2.model.KeyType;
com.amazonaws.services.dynamodbv2.model.Projection;
com.amazonaws.services.dynamodbv2.model.ProvisionedThroughput;
public class DocumentAPIGlobalSecondaryIndexExample {
static AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
static DynamoDB dynamoDB = new DynamoDB(client);
public static String tableName = &quot;Issues&quot;;
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public static void main(String[] args) throws Exception {
createTable();
loadData();
queryIndex(&quot;CreateDateIndex&quot;);
queryIndex(&quot;TitleIndex&quot;);
queryIndex(&quot;DueDateIndex&quot;);
deleteTable(tableName);
}
public static void createTable() {
// Attribute definitions
ArrayList&lt;AttributeDefinition&gt; attributeDefinitions = new
ArrayList&lt;AttributeDefinition&gt;();
attributeDefinitions.add(new
AttributeDefinition().withAttributeName(&quot;IssueId&quot;).withAttributeType(&quot;S&quot;));
attributeDefinitions.add(new
AttributeDefinition().withAttributeName(&quot;Title&quot;).withAttributeType(&quot;S&quot;));
attributeDefinitions.add(new
AttributeDefinition().withAttributeName(&quot;CreateDate&quot;).withAttributeType(&quot;S&quot;));
attributeDefinitions.add(new
AttributeDefinition().withAttributeName(&quot;DueDate&quot;).withAttributeType(&quot;S&quot;));
// Key schema for table
ArrayList&lt;KeySchemaElement&gt; tableKeySchema = new ArrayList&lt;KeySchemaElement&gt;();
tableKeySchema.add(new
KeySchemaElement().withAttributeName(&quot;IssueId&quot;).withKeyType(KeyType.HASH)); // Partition
// key
tableKeySchema.add(new
KeySchemaElement().withAttributeName(&quot;Title&quot;).withKeyType(KeyType.RANGE)); // Sort
// key
// Initial provisioned throughput settings for the indexes
ProvisionedThroughput ptIndex = new
ProvisionedThroughput().withReadCapacityUnits(1L)
.withWriteCapacityUnits(1L);
// CreateDateIndex
GlobalSecondaryIndex createDateIndex = new
GlobalSecondaryIndex().withIndexName(&quot;CreateDateIndex&quot;)
.withProvisionedThroughput(ptIndex)
.withKeySchema(new
KeySchemaElement().withAttributeName(&quot;CreateDate&quot;).withKeyType(KeyType.HASH), // Partition
// key
new
KeySchemaElement().withAttributeName(&quot;IssueId&quot;).withKeyType(KeyType.RANGE)) // Sort
// key
.withProjection(
new
Projection().withProjectionType(&quot;INCLUDE&quot;).withNonKeyAttributes(&quot;Description&quot;, &quot;Status&quot;));
// TitleIndex
GlobalSecondaryIndex titleIndex = new
GlobalSecondaryIndex().withIndexName(&quot;TitleIndex&quot;)
.withProvisionedThroughput(ptIndex)
.withKeySchema(new
KeySchemaElement().withAttributeName(&quot;Title&quot;).withKeyType(KeyType.HASH), // Partition
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// key
new
KeySchemaElement().withAttributeName(&quot;IssueId&quot;).withKeyType(KeyType.RANGE)) // Sort
// key
.withProjection(new Projection().withProjectionType(&quot;KEYS_ONLY&quot;));
// DueDateIndex
GlobalSecondaryIndex dueDateIndex = new
GlobalSecondaryIndex().withIndexName(&quot;DueDateIndex&quot;)
.withProvisionedThroughput(ptIndex)
.withKeySchema(new
KeySchemaElement().withAttributeName(&quot;DueDate&quot;).withKeyType(KeyType.HASH)) // Partition
// key
.withProjection(new Projection().withProjectionType(&quot;ALL&quot;));
CreateTableRequest createTableRequest = new
CreateTableRequest().withTableName(tableName)
.withProvisionedThroughput(
new ProvisionedThroughput().withReadCapacityUnits((long)
1).withWriteCapacityUnits((long) 1))
.withAttributeDefinitions(attributeDefinitions).withKeySchema(tableKeySchema)
.withGlobalSecondaryIndexes(createDateIndex, titleIndex, dueDateIndex);
System.out.println(&quot;Creating table &quot; + tableName + &quot;...&quot;);
dynamoDB.createTable(createTableRequest);
}
// Wait for table to become active
System.out.println(&quot;Waiting for &quot; + tableName + &quot; to become ACTIVE...&quot;);
try {
Table table = dynamoDB.getTable(tableName);
table.waitForActive();
}
catch (InterruptedException e) {
e.printStackTrace();
}
public static void queryIndex(String indexName) {
Table table = dynamoDB.getTable(tableName);
\n&quot;);
System.out.println(&quot;\n***********************************************************
System.out.print(&quot;Querying index &quot; + indexName + &quot;...&quot;);
Index index = table.getIndex(indexName);
ItemCollection&lt;QueryOutcome&gt; items = null;
QuerySpec querySpec = new QuerySpec();
if (indexName == &quot;CreateDateIndex&quot;) {
System.out.println(&quot;Issues filed on 2013-11-01&quot;);
querySpec.withKeyConditionExpression(&quot;CreateDate = :v_date and
begins_with(IssueId, :v_issue)&quot;)
.withValueMap(new ValueMap().withString(&quot;:v_date&quot;,
&quot;2013-11-01&quot;).withString(&quot;:v_issue&quot;, &quot;A-&quot;));
items = index.query(querySpec);
}
else if (indexName == &quot;TitleIndex&quot;) {
System.out.println(&quot;Compilation errors&quot;);
querySpec.withKeyConditionExpression(&quot;Title = :v_title and
begins_with(IssueId, :v_issue)&quot;)
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.withValueMap(new ValueMap().withString(&quot;:v_title&quot;, &quot;Compilation
error&quot;).withString(&quot;:v_issue&quot;, &quot;A-&quot;));
items = index.query(querySpec);
}
else if (indexName == &quot;DueDateIndex&quot;) {
System.out.println(&quot;Items that are due on 2013-11-30&quot;);
querySpec.withKeyConditionExpression(&quot;DueDate = :v_date&quot;)
.withValueMap(new ValueMap().withString(&quot;:v_date&quot;, &quot;2013-11-30&quot;));
items = index.query(querySpec);
}
else {
System.out.println(&quot;\nNo valid index name provided&quot;);
return;
}
Iterator&lt;Item&gt; iterator = items.iterator();
System.out.println(&quot;Query: printing results...&quot;);
while (iterator.hasNext()) {
System.out.println(iterator.next().toJSONPretty());
}
}
public static void deleteTable(String tableName) {
System.out.println(&quot;Deleting table &quot; + tableName + &quot;...&quot;);
Table table = dynamoDB.getTable(tableName);
table.delete();
}
// Wait for table to be deleted
System.out.println(&quot;Waiting for &quot; + tableName + &quot; to be deleted...&quot;);
try {
table.waitForDelete();
}
catch (InterruptedException e) {
e.printStackTrace();
}
public static void loadData() {
System.out.println(&quot;Loading data into table &quot; + tableName + &quot;...&quot;);
//
//
//
//
IssueId, Title,
Description,
CreateDate, LastUpdateDate, DueDate,
Priority, Status
putItem(&quot;A-101&quot;, &quot;Compilation error&quot;, &quot;Can't compile Project X - bad version
number. What does this mean?&quot;,
&quot;2013-11-01&quot;, &quot;2013-11-02&quot;, &quot;2013-11-10&quot;, 1, &quot;Assigned&quot;);
putItem(&quot;A-102&quot;, &quot;Can't read data file&quot;, &quot;The main data file is missing, or the
permissions are incorrect&quot;,
&quot;2013-11-01&quot;, &quot;2013-11-04&quot;, &quot;2013-11-30&quot;, 2, &quot;In progress&quot;);
putItem(&quot;A-103&quot;, &quot;Test failure&quot;, &quot;Functional test of Project X produces errors&quot;,
&quot;2013-11-01&quot;, &quot;2013-11-02&quot;,
&quot;2013-11-10&quot;, 1, &quot;In progress&quot;);
putItem(&quot;A-104&quot;, &quot;Compilation error&quot;, &quot;Variable 'messageCount' was not
initialized.&quot;, &quot;2013-11-15&quot;,
&quot;2013-11-16&quot;, &quot;2013-11-30&quot;, 3, &quot;Assigned&quot;);
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putItem(&quot;A-105&quot;, &quot;Network issue&quot;, &quot;Can't ping IP address 127.0.0.1. Please fix
this.&quot;, &quot;2013-11-15&quot;,
&quot;2013-11-16&quot;, &quot;2013-11-19&quot;, 5, &quot;Assigned&quot;);
}
public static void putItem(
String issueId, String title, String description, String createDate, String
lastUpdateDate, String dueDate,
Integer priority, String status) {
Table table = dynamoDB.getTable(tableName);
title)
}
Item item = new Item().withPrimaryKey(&quot;IssueId&quot;, issueId).withString(&quot;Title&quot;,
.withString(&quot;Description&quot;, description).withString(&quot;CreateDate&quot;, createDate)
.withString(&quot;LastUpdateDate&quot;, lastUpdateDate).withString(&quot;DueDate&quot;, dueDate)
.withNumber(&quot;Priority&quot;, priority).withString(&quot;Status&quot;, status);
table.putItem(item);
}
Working with Global Secondary Indexes: .NET
Topics
• Create a Table With a Global Secondary Index (p. 474)
• Describe a Table With a Global Secondary Index (p. 476)
• Query a Global Secondary Index (p. 477)
• Example: Global Secondary Indexes Using the AWS SDK for .NET Low-Level API (p. 478)
You can use the AWS SDK for .NET low-level API to create a table with one or more global secondary
indexes, describe the indexes on the table, and perform queries using the indexes. These operations map
to the corresponding DynamoDB operations. For more information, see the Amazon DynamoDB API
Reference.
The following are the common steps for table operations using the .NET low-level API.
1. Create an instance of the AmazonDynamoDBClient class.
2. Provide the required and optional parameters for the operation by creating the corresponding request
objects.
For example, create a CreateTableRequest object to create a table and QueryRequest object to query
a table or an index.
3. Execute the appropriate method provided by the client that you created in the preceding step.
Create a Table With a Global Secondary Index
You can create global secondary indexes at the same time that you create a table. To do this, use
CreateTable and provide your speciﬁcations for one or more global secondary indexes. The following C#
code snippet creates a table to hold information about weather data. The partition key is Location and
the sort key is Date. A global secondary index named PrecipIndex allows fast access to precipitation data
for various locations.
The following are the steps to create a table with a global secondary index, using the .NET low-level API.
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1. Create an instance of the AmazonDynamoDBClient class.
2. Create an instance of the CreateTableRequest class to provide the request information.
You must provide the table name, its primary key, and the provisioned throughput values. For the
global secondary index, you must provide the index name, its provisioned throughput settings, the
attribute deﬁnitions for the index sort key, the key schema for the index, and the attribute projection.
3. Execute the CreateTable method by providing the request object as a parameter.
The following C# code snippet demonstrates the preceding steps. The snippet creates a table
(WeatherData) with a global secondary index (PrecipIndex). The index partition key is Date and its sort
key is Precipitation. All of the table attributes are projected into the index. Users can query this index to
obtain weather data for a particular date, optionally sorting the data by precipitation amount.
Note that since Precipitation is not a key attribute for the table, it is not required; however, WeatherData
items without Precipitation will not appear in PrecipIndex.
client = new AmazonDynamoDBClient();
string tableName = &quot;WeatherData&quot;;
// Attribute definitions
var attributeDefinitions = new List&lt;AttributeDefinition&gt;()
{
{new AttributeDefinition{
AttributeName = &quot;Location&quot;,
AttributeType = &quot;S&quot;}},
{new AttributeDefinition{
AttributeName = &quot;Date&quot;,
AttributeType = &quot;S&quot;}},
{new AttributeDefinition(){
AttributeName = &quot;Precipitation&quot;,
AttributeType = &quot;N&quot;}
}
};
// Table key schema
var tableKeySchema = new List&lt;KeySchemaElement&gt;()
{
{new KeySchemaElement {
AttributeName = &quot;Location&quot;,
KeyType = &quot;HASH&quot;}}, //Partition key
{new KeySchemaElement {
AttributeName = &quot;Date&quot;,
KeyType = &quot;RANGE&quot;} //Sort key
}
};
// PrecipIndex
var precipIndex = new GlobalSecondaryIndex
{
IndexName = &quot;PrecipIndex&quot;,
ProvisionedThroughput = new ProvisionedThroughput
{
ReadCapacityUnits = (long)10,
WriteCapacityUnits = (long)1
},
Projection = new Projection { ProjectionType = &quot;ALL&quot; }
};
var indexKeySchema = new List&lt;KeySchemaElement&gt; {
{new KeySchemaElement { AttributeName = &quot;Date&quot;, KeyType = &quot;HASH&quot;}}, //Partition key
{new KeySchemaElement{AttributeName = &quot;Precipitation&quot;,KeyType = &quot;RANGE&quot;}} //Sort key
};
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precipIndex.KeySchema = indexKeySchema;
CreateTableRequest createTableRequest = new CreateTableRequest
{
TableName = tableName,
ProvisionedThroughput = new ProvisionedThroughput
{
ReadCapacityUnits = (long)5,
WriteCapacityUnits = (long)1
},
AttributeDefinitions = attributeDefinitions,
KeySchema = tableKeySchema,
GlobalSecondaryIndexes = { precipIndex }
};
CreateTableResponse response = client.CreateTable(createTableRequest);
Console.WriteLine(response.CreateTableResult.TableDescription.TableName);
Console.WriteLine(response.CreateTableResult.TableDescription.TableStatus);
You must wait until DynamoDB creates the table and sets the table status to ACTIVE. After that, you can
begin putting data items into the table.
Describe a Table With a Global Secondary Index
To get information about global secondary indexes on a table, use DescribeTable. For each index, you
can access its name, key schema, and projected attributes.
The following are the steps to access global secondary index information a table using the .NET low-level
API.
1. Create an instance of the AmazonDynamoDBClient class.
2. Create an instance of the DescribeTableRequest class to provide the request information. You must
provide the table name.
3. Execute the describeTable method by providing the request object as a parameter.
The following C# code snippet demonstrates the preceding steps.
Example
client = new AmazonDynamoDBClient();
string tableName = &quot;WeatherData&quot;;
DescribeTableResponse response = client.DescribeTable(new DescribeTableRequest { TableName
= tableName});
List&lt;GlobalSecondaryIndexDescription&gt; globalSecondaryIndexes =
response.DescribeTableResult.Table.GlobalSecondaryIndexes;
// This code snippet will work for multiple indexes, even though
// there is only one index in this example.
foreach (GlobalSecondaryIndexDescription gsiDescription in globalSecondaryIndexes) {
Console.WriteLine(&quot;Info for index &quot; + gsiDescription.IndexName + &quot;:&quot;);
foreach (KeySchemaElement kse in gsiDescription.KeySchema) {
Console.WriteLine(&quot;\t&quot; + kse.AttributeName + &quot;: key type is &quot; + kse.KeyType);
}
Projection projection = gsiDescription.Projection;
Console.WriteLine(&quot;\tThe projection type is: &quot; + projection.ProjectionType);
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}
if (projection.ProjectionType.ToString().Equals(&quot;INCLUDE&quot;)) {
Console.WriteLine(&quot;\t\tThe non-key projected attributes are: &quot;
+ projection.NonKeyAttributes);
}
Query a Global Secondary Index
You can use Query on a global secondary index, in much the same way you Query a table. You need to
specify the index name, the query criteria for the index partition key and sort key (if present), and the
attributes that you want to return. In this example, the index is PrecipIndex, which has a partition key of
Date and a sort key of Precipitation. The index query returns all of the weather data for a particular date,
where the precipitation is greater than zero.
The following are the steps to query a global secondary index using the .NET low-level API.
1. Create an instance of the AmazonDynamoDBClient class.
2. Create an instance of the QueryRequest class to provide the request information.
3. Execute the query method by providing the request object as a parameter.
The attribute name Date is a DynamoDB reserved word. Therefore, we must use an expression attribute
name as a placeholder in the KeyConditionExpression.
The following C# code snippet demonstrates the preceding steps.
Example
client = new AmazonDynamoDBClient();
QueryRequest queryRequest = new QueryRequest
{
TableName = &quot;WeatherData&quot;,
IndexName = &quot;PrecipIndex&quot;,
KeyConditionExpression = &quot;#dt = :v_date and Precipitation &gt; :v_precip&quot;,
ExpressionAttributeNames = new Dictionary&lt;String, String&gt; {
{&quot;#dt&quot;, &quot;Date&quot;}
},
ExpressionAttributeValues = new Dictionary&lt;string, AttributeValue&gt; {
{&quot;:v_date&quot;, new AttributeValue { S = &quot;2013-08-01&quot; }},
{&quot;:v_precip&quot;, new AttributeValue { N = &quot;0&quot; }}
},
ScanIndexForward = true
};
var result = client.Query(queryRequest);
var items = result.Items;
foreach (var currentItem in items)
{
foreach (string attr in currentItem.Keys)
{
Console.Write(attr + &quot;---&gt; &quot;);
if (attr == &quot;Precipitation&quot;)
{
Console.WriteLine(currentItem[attr].N);
}
else
{
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Console.WriteLine(currentItem[attr].S);
}
}
}
Console.WriteLine();
Example: Global Secondary Indexes Using the AWS SDK for .NET Low-Level API
The following C# code example shows how to work with global secondary indexes. The example creates
a table named Issues, which might be used in a simple bug tracking system for software development.
The partition key is IssueId and the sort key is Title. There are three global secondary indexes on this
table:
• CreateDateIndex—the partition key is CreateDate and the sort key is IssueId. In addition to the table
keys, the attributes Description and Status are projected into the index.
• TitleIndex—the partition key is IssueId and the sort key is Title. No attributes other than the table keys
are projected into the index.
• DueDateIndex—the partition key is DueDate, and there is no sort key. All of the table attributes are
projected into the index.
After the Issues table is created, the program loads the table with data representing software bug
reports, and then queries the data using the global secondary indexes. Finally, the program deletes the
Issues table.
For step-by-step instructions to test the following sample, see .NET Code Samples (p. 287).
Example
using
using
using
using
using
using
using
using
using
System;
System.Collections.Generic;
System.Linq;
Amazon.DynamoDBv2;
Amazon.DynamoDBv2.DataModel;
Amazon.DynamoDBv2.DocumentModel;
Amazon.DynamoDBv2.Model;
Amazon.Runtime;
Amazon.SecurityToken;
namespace com.amazonaws.codesamples
{
class LowLevelGlobalSecondaryIndexExample
{
private static AmazonDynamoDBClient client = new AmazonDynamoDBClient();
public static String tableName = &quot;Issues&quot;;
public static void Main(string[] args)
{
CreateTable();
LoadData();
QueryIndex(&quot;CreateDateIndex&quot;);
QueryIndex(&quot;TitleIndex&quot;);
QueryIndex(&quot;DueDateIndex&quot;);
DeleteTable(tableName);
}
Console.WriteLine(&quot;To continue, press enter&quot;);
Console.Read();
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private static void CreateTable()
{
// Attribute definitions
var attributeDefinitions = new List&lt;AttributeDefinition&gt;()
{
{new AttributeDefinition {
AttributeName = &quot;IssueId&quot;, AttributeType = &quot;S&quot;
}},
{new AttributeDefinition {
AttributeName = &quot;Title&quot;, AttributeType = &quot;S&quot;
}},
{new AttributeDefinition {
AttributeName = &quot;CreateDate&quot;, AttributeType = &quot;S&quot;
}},
{new AttributeDefinition {
AttributeName = &quot;DueDate&quot;, AttributeType = &quot;S&quot;
}}
};
};
// Key schema for table
var tableKeySchema = new List&lt;KeySchemaElement&gt;() {
{
new KeySchemaElement {
AttributeName= &quot;IssueId&quot;,
KeyType = &quot;HASH&quot; //Partition key
}
},
{
new KeySchemaElement {
AttributeName = &quot;Title&quot;,
KeyType = &quot;RANGE&quot; //Sort key
}
}
// Initial provisioned throughput settings for the indexes
var ptIndex = new ProvisionedThroughput
{
ReadCapacityUnits = 1L,
WriteCapacityUnits = 1L
};
// CreateDateIndex
var createDateIndex = new GlobalSecondaryIndex()
{
IndexName = &quot;CreateDateIndex&quot;,
ProvisionedThroughput = ptIndex,
KeySchema = {
new KeySchemaElement {
AttributeName = &quot;CreateDate&quot;, KeyType = &quot;HASH&quot; //Partition key
},
new KeySchemaElement {
AttributeName = &quot;IssueId&quot;, KeyType = &quot;RANGE&quot; //Sort key
}
},
Projection = new Projection
{
ProjectionType = &quot;INCLUDE&quot;,
NonKeyAttributes = {
&quot;Description&quot;, &quot;Status&quot;
}
}
};
// TitleIndex
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var titleIndex = new GlobalSecondaryIndex()
{
IndexName = &quot;TitleIndex&quot;,
ProvisionedThroughput = ptIndex,
KeySchema = {
new KeySchemaElement {
AttributeName = &quot;Title&quot;, KeyType = &quot;HASH&quot; //Partition key
},
new KeySchemaElement {
AttributeName = &quot;IssueId&quot;, KeyType = &quot;RANGE&quot; //Sort key
}
},
Projection = new Projection
{
ProjectionType = &quot;KEYS_ONLY&quot;
}
};
// DueDateIndex
var dueDateIndex = new GlobalSecondaryIndex()
{
IndexName = &quot;DueDateIndex&quot;,
ProvisionedThroughput = ptIndex,
KeySchema = {
new KeySchemaElement {
AttributeName = &quot;DueDate&quot;,
KeyType = &quot;HASH&quot; //Partition key
}
},
Projection = new Projection
{
ProjectionType = &quot;ALL&quot;
}
};
var createTableRequest = new CreateTableRequest
{
TableName = tableName,
ProvisionedThroughput = new ProvisionedThroughput
{
ReadCapacityUnits = (long)1,
WriteCapacityUnits = (long)1
},
AttributeDefinitions = attributeDefinitions,
KeySchema = tableKeySchema,
GlobalSecondaryIndexes = {
createDateIndex, titleIndex, dueDateIndex
}
};
Console.WriteLine(&quot;Creating table &quot; + tableName + &quot;...&quot;);
client.CreateTable(createTableRequest);
}
WaitUntilTableReady(tableName);
private static void LoadData()
{
Console.WriteLine(&quot;Loading data into table &quot; + tableName + &quot;...&quot;);
//
//
//
//
IssueId, Title,
Description,
CreateDate, LastUpdateDate, DueDate,
Priority, Status
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putItem(&quot;A-101&quot;, &quot;Compilation error&quot;,
&quot;Can't compile Project X - bad version number. What does this mean?&quot;,
&quot;2013-11-01&quot;, &quot;2013-11-02&quot;, &quot;2013-11-10&quot;,
1, &quot;Assigned&quot;);
putItem(&quot;A-102&quot;, &quot;Can't read data file&quot;,
&quot;The main data file is missing, or the permissions are incorrect&quot;,
&quot;2013-11-01&quot;, &quot;2013-11-04&quot;, &quot;2013-11-30&quot;,
2, &quot;In progress&quot;);
putItem(&quot;A-103&quot;, &quot;Test failure&quot;,
&quot;Functional test of Project X produces errors&quot;,
&quot;2013-11-01&quot;, &quot;2013-11-02&quot;, &quot;2013-11-10&quot;,
1, &quot;In progress&quot;);
putItem(&quot;A-104&quot;, &quot;Compilation error&quot;,
&quot;Variable 'messageCount' was not initialized.&quot;,
&quot;2013-11-15&quot;, &quot;2013-11-16&quot;, &quot;2013-11-30&quot;,
3, &quot;Assigned&quot;);
}
putItem(&quot;A-105&quot;, &quot;Network issue&quot;,
&quot;Can't ping IP address 127.0.0.1. Please fix this.&quot;,
&quot;2013-11-15&quot;, &quot;2013-11-16&quot;, &quot;2013-11-19&quot;,
5, &quot;Assigned&quot;);
private static void putItem(
String issueId, String title,
String description,
String createDate, String lastUpdateDate, String dueDate,
Int32 priority, String status)
{
Dictionary&lt;String, AttributeValue&gt; item = new Dictionary&lt;string,
AttributeValue&gt;();
item.Add(&quot;IssueId&quot;, new AttributeValue
{
S = issueId
});
item.Add(&quot;Title&quot;, new AttributeValue
{
S = title
});
item.Add(&quot;Description&quot;, new AttributeValue
{
S = description
});
item.Add(&quot;CreateDate&quot;, new AttributeValue
{
S = createDate
});
item.Add(&quot;LastUpdateDate&quot;, new AttributeValue
{
S = lastUpdateDate
});
item.Add(&quot;DueDate&quot;, new AttributeValue
{
S = dueDate
});
item.Add(&quot;Priority&quot;, new AttributeValue
{
N = priority.ToString()
});
item.Add(&quot;Status&quot;, new AttributeValue
{
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});
try
{
}
S = status
client.PutItem(new PutItemRequest
{
TableName = tableName,
Item = item
});
}
catch (Exception e)
{
Console.WriteLine(e.ToString());
}
private static void QueryIndex(string indexName)
{
Console.WriteLine
(&quot;\n***********************************************************\n&quot;);
Console.WriteLine(&quot;Querying index &quot; + indexName + &quot;...&quot;);
QueryRequest queryRequest = new QueryRequest
{
TableName = tableName,
IndexName = indexName,
ScanIndexForward = true
};
String keyConditionExpression;
Dictionary&lt;string, AttributeValue&gt; expressionAttributeValues = new
Dictionary&lt;string, AttributeValue&gt;();
if (indexName == &quot;CreateDateIndex&quot;)
{
Console.WriteLine(&quot;Issues filed on 2013-11-01\n&quot;);
keyConditionExpression = &quot;CreateDate = :v_date and
begins_with(IssueId, :v_issue)&quot;;
expressionAttributeValues.Add(&quot;:v_date&quot;, new AttributeValue
{
S = &quot;2013-11-01&quot;
});
expressionAttributeValues.Add(&quot;:v_issue&quot;, new AttributeValue
{
S = &quot;A-&quot;
});
}
else if (indexName == &quot;TitleIndex&quot;)
{
Console.WriteLine(&quot;Compilation errors\n&quot;);
keyConditionExpression = &quot;Title = :v_title and
begins_with(IssueId, :v_issue)&quot;;
expressionAttributeValues.Add(&quot;:v_title&quot;, new AttributeValue
{
S = &quot;Compilation error&quot;
});
expressionAttributeValues.Add(&quot;:v_issue&quot;, new AttributeValue
{
S = &quot;A-&quot;
});
// Select
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queryRequest.Select = &quot;ALL_PROJECTED_ATTRIBUTES&quot;;
}
else if (indexName == &quot;DueDateIndex&quot;)
{
Console.WriteLine(&quot;Items that are due on 2013-11-30\n&quot;);
keyConditionExpression = &quot;DueDate = :v_date&quot;;
expressionAttributeValues.Add(&quot;:v_date&quot;, new AttributeValue
{
S = &quot;2013-11-30&quot;
});
// Select
queryRequest.Select = &quot;ALL_PROJECTED_ATTRIBUTES&quot;;
}
else
{
}
Console.WriteLine(&quot;\nNo valid index name provided&quot;);
return;
queryRequest.KeyConditionExpression = keyConditionExpression;
queryRequest.ExpressionAttributeValues = expressionAttributeValues;
}
var result = client.Query(queryRequest);
var items = result.Items;
foreach (var currentItem in items)
{
foreach (string attr in currentItem.Keys)
{
if (attr == &quot;Priority&quot;)
{
Console.WriteLine(attr + &quot;---&gt; &quot; + currentItem[attr].N);
}
else
{
Console.WriteLine(attr + &quot;---&gt; &quot; + currentItem[attr].S);
}
}
Console.WriteLine();
}
private static void DeleteTable(string tableName)
{
Console.WriteLine(&quot;Deleting table &quot; + tableName + &quot;...&quot;);
client.DeleteTable(new DeleteTableRequest
{
TableName = tableName
});
WaitForTableToBeDeleted(tableName);
}
private static void WaitUntilTableReady(string tableName)
{
string status = null;
// Let us wait until table is created. Call DescribeTable.
do
{
System.Threading.Thread.Sleep(5000); // Wait 5 seconds.
try
{
var res = client.DescribeTable(new DescribeTableRequest
{
TableName = tableName
});
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Console.WriteLine(&quot;Table name: {0}, status: {1}&quot;,
res.Table.TableName,
res.Table.TableStatus);
status = res.Table.TableStatus;
}
}
catch (ResourceNotFoundException)
{
// DescribeTable is eventually consistent. So you might
// get resource not found. So we handle the potential exception.
}
} while (status != &quot;ACTIVE&quot;);
private static void WaitForTableToBeDeleted(string tableName)
{
bool tablePresent = true;
while (tablePresent)
{
System.Threading.Thread.Sleep(5000); // Wait 5 seconds.
try
{
var res = client.DescribeTable(new DescribeTableRequest
{
TableName = tableName
});
Console.WriteLine(&quot;Table name: {0}, status: {1}&quot;,
res.Table.TableName,
res.Table.TableStatus);
}
}
}
}
}
catch (ResourceNotFoundException)
{
tablePresent = false;
}
Local Secondary Indexes
Topics
• Attribute Projections (p. 486)
• Creating a Local Secondary Index (p. 488)
• Querying a Local Secondary Index (p. 488)
• Scanning a Local Secondary Index (p. 489)
• Item Writes and Local Secondary Indexes (p. 489)
• Provisioned Throughput Considerations for Local Secondary Indexes (p. 490)
• Storage Considerations for Local Secondary Indexes (p. 491)
• Item Collections (p. 492)
• Working with Local Secondary Indexes: Java (p. 494)
• Working with Local Secondary Indexes: .NET (p. 503)
Some applications only need to query data using the base table's primary key; however, there may be
situations where an alternate sort key would be helpful. To give your application a choice of sort keys,
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you can create one or more local secondary indexes on a table and issue Query or Scan requests against
these indexes.
For example, consider the Thread table that is deﬁned in Creating Tables and Loading Sample
Data (p. 280). This table is useful for an application such as the AWS Discussion Forums. The following
diagram shows how the items in the table would be organized. (Not all of the attributes are shown.)
DynamoDB stores all of the items with the same partition key value contiguously. In this example, given
a particular ForumName, a Query operation could immediately locate all of the threads for that forum.
Within a group of items with the same partition key value, the items are sorted by sort key value. If the
sort key (Subject) is also provided in the query, DynamoDB can narrow down the results that are returned
—for example, returning all of the threads in the &quot;S3&quot; forum that have a Subject beginning with the
letter &quot;a&quot;.
Some requests might require more complex data access patterns. For example:
• Which forum threads get the most views and replies?
• Which thread in a particular forum has the largest number of messages?
• How many threads were posted in a particular forum within a particular time period?
To answer these questions, the Query action would not be suﬃcient. Instead, you would have to Scan the
entire table. For a table with millions of items, this would consume a large amount of provisioned read
throughput and take a long time to complete.
However, you can specify one or more local secondary indexes on non-key attributes, such as Replies or
LastPostDateTime.
A local secondary index maintains an alternate sort key for a given partition key value. A local secondary
index also contains a copy of some or all of the attributes from its base table; you specify which
attributes are projected into the local secondary index when you create the table. The data in a local
secondary index is organized by the same partition key as the base table, but with a diﬀerent sort key.
This lets you access data items eﬃciently across this diﬀerent dimension. For greater query or scan
ﬂexibility, you can create up to ﬁve local secondary indexes per table.
Suppose that an application needs to ﬁnd all of the threads that have been posted within the last three
months. Without a local secondary index, the application would have to Scan the entire Thread table and
discard any posts that were not within the speciﬁed time frame. With a local secondary index, a Query
operation could use LastPostDateTime as a sort key and ﬁnd the data quickly.
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The following diagram shows a local secondary index named LastPostIndex. Note that the partition key is
the same as that of the Thread table, but the sort key is LastPostDateTime.
Every local secondary index must meet the following conditions:
• The partition key is the same as that of its base table.
• The sort key consists of exactly one scalar attribute.
• The sort key of the base table is projected into the index, where it acts as a non-key attribute.
In this example, the partition key is ForumName and the sort key of the local secondary index is
LastPostDateTime. In addition, the sort key value from the base table (in this example, Subject) is
projected into the index, but it is not a part of the index key. If an application needs a list that is based on
ForumName and LastPostDateTime, it can issue a Query request against LastPostIndex. The query results
are sorted by LastPostDateTime, and can be returned in ascending or descending order. The query can
also apply key conditions, such as returning only items that have a LastPostDateTime within a particular
time span.
Every local secondary index automatically contains the partition and sort keys from its base table; you
can optionally project non-key attributes into the index. When you query the index, DynamoDB can
retrieve these projected attributes eﬃciently. When you query a local secondary index, the query can
also retrieve attributes that are not projected into the index. DynamoDB will automatically fetch these
attributes from the base table, but at a greater latency and with higher provisioned throughput costs.
For any local secondary index, you can store up to 10 GB of data per distinct partition key value. This
ﬁgure includes all of the items in the base table, plus all of the items in the indexes, that have the same
partition key value. For more information, see Item Collections (p. 492).
Attribute Projections
With LastPostIndex, an application could use ForumName and LastPostDateTime as query criteria;
however, to retrieve any additional attributes, DynamoDB would need to perform additional read
operations against the Thread table. These extra reads are known as fetches, and they can increase the
total amount of provisioned throughput required for a query.
Suppose that you wanted to populate a web page with a list of all the threads in &quot;S3&quot; and the number
of replies for each thread, sorted by the last reply date/time beginning with the most recent reply. To
populate this list, you would need the following attributes:
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• Subject
• Replies
• LastPostDateTime
The most eﬃcient way to query this data, and to avoid fetch operations, would be to project the Replies
attribute from the table into the local secondary index, as shown in this diagram:
A projection is the set of attributes that is copied from a table into a secondary index. The partition key
and sort key of the table are always projected into the index; you can project other attributes to support
your application's query requirements. When you query an index, Amazon DynamoDB can access any
attribute in the projection as if those attributes were in a table of their own.
When you create a secondary index, you need to specify the attributes that will be projected into the
index. DynamoDB provides three diﬀerent options for this:
• KEYS_ONLY – Each item in the index consists only of the table partition key and sort key values, plus
the index key values. The KEYS_ONLY option results in the smallest possible secondary index.
• INCLUDE – In addition to the attributes described in KEYS_ONLY, the secondary index will include other
non-key attributes that you specify.
• ALL – The secondary index includes all of the attributes from the source table. Because all of the table
data is duplicated in the index, an ALL projection results in the largest possible secondary index.
In the previous diagram, the non-key attribute Replies is projected into LastPostIndex. An application can
query LastPostIndex instead of the full Thread table to populate a web page with Subject, Replies and
LastPostDateTime. If any other non-key attributes are requested, DynamoDB would need to fetch those
attributes from the Thread table.
From an application's point of view, fetching additional attributes from the base table is automatic and
transparent, so there is no need to rewrite any application logic. However, note that such fetching can
greatly reduce the performance advantage of using a local secondary index.
When you choose the attributes to project into a local secondary index, you must consider the tradeoﬀ
between provisioned throughput costs and storage costs:
• If you need to access just a few attributes with the lowest possible latency, consider projecting only
those attributes into a local secondary index. The smaller the index, the less that it will cost to store it,
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and the less your write costs will be. If there are attributes that you occasionally need to fetch, the cost
for provisioned throughput may well outweigh the longer-term cost of storing those attributes.
• If your application will frequently access some non-key attributes, you should consider projecting
those attributes into a local secondary index. The additional storage costs for the local secondary
index will oﬀset the cost of performing frequent table scans.
• If you need to access most of the non-key attributes on a frequent basis, you can project these
attributes—or even the entire base table— into a local secondary index. This will give you maximum
ﬂexibility and lowest provisioned throughput consumption, because no fetching would be required;
however, your storage cost would increase, or even double if you are projecting all attributes.
• If your application needs to query a table infrequently, but must perform many writes or updates
against the data in the table, consider projecting KEYS_ONLY. The local secondary index would be of
minimal size, but would still be available when needed for query activity.
Creating a Local Secondary Index
To create one or more local secondary indexes on a table, use the LocalSecondaryIndexes parameter
of the CreateTable operation. Local secondary indexes on a table are created when the table is created.
When you delete a table, any local secondary indexes on that table are also deleted.
You must specify one non-key attribute to act as the sort key of the local secondary index. The attribute
that you choose must be a scalar String, Number, or Binary; other scalar types, document types, and set
types are not allowed. For a complete list of data types, see Data Types (p. 12).
Important
For tables with local secondary indexes, there is a 10 GB size limit per partition key value. A
table with local secondary indexes can store any number of items, as long as the total size for
any one partition key value does not exceed 10 GB. For more information, see Item Collection
Size Limit (p. 493).
You can project attributes of any data type into a local secondary index. This includes scalars, documents,
and sets. For a complete list of data types, see Data Types (p. 12).
Querying a Local Secondary Index
In a DynamoDB table, the combined partition key value and sort key value for each item must be unique.
However, in a local secondary index, the sort key value does not need to be unique for a given partition
key value. If there are multiple items in the local secondary index that have the same sort key value, a
Query operation will return all of the items that have the same partition key value. In the response, the
matching items are not returned in any particular order.
You can query a local secondary index using either eventually consistent or strongly consistent reads. To
specify which type of consistency you want, use the ConsistentRead parameter of the Query operation. A
strongly consistent read from a local secondary index will always return the latest updated values. If the
query needs to fetch additional attributes from the base table, then those attributes will be consistent
with respect to the index.
Example
Consider the following data returned from a Query that requests data from the discussion threads in a
particular forum:
{
&quot;TableName&quot;: &quot;Thread&quot;,
&quot;IndexName&quot;: &quot;LastPostIndex&quot;,
&quot;ConsistentRead&quot;: false,
&quot;ProjectionExpression&quot;: &quot;Subject, LastPostDateTime, Replies, Tags&quot;,
&quot;KeyConditionExpression&quot;:
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}
&quot;ForumName = :v_forum and LastPostDateTime between :v_start and :v_end&quot;,
&quot;ExpressionAttributeValues&quot;: {
&quot;:v_start&quot;: {&quot;S&quot;: &quot;2015-08-31T00:00:00.000Z&quot;},
&quot;:v_end&quot;: {&quot;S&quot;: &quot;2015-11-31T00:00:00.000Z&quot;},
&quot;:v_forum&quot;: {&quot;S&quot;: &quot;EC2&quot;}
}
In this query:
• DynamoDB accesses LastPostIndex, using the ForumName partition key to locate the index items for
&quot;EC2&quot;. All of the index items with this key are stored adjacent to each other for rapid retrieval.
• Within this forum, DynamoDB uses the index to look up the keys that match the speciﬁed
LastPostDateTime condition.
• Because the Replies attribute is projected into the index, DynamoDB can retrieve this attribute without
consuming any additional provisioned throughput.
• The Tags attribute is not projected into the index, so DynamoDB must access the Thread table and
fetch this attribute.
• The results are returned, sorted by LastPostDateTime. The index entries are sorted by partition key
value and then by sort key value, and Query returns them in the order they are stored. (You can use the
ScanIndexForward parameter to return the results in descending order.)
Because the Tags attribute is not projected into the local secondary index, DynamoDB must consume
additional read capacity units to fetch this attribute from the base table. If you need to run this query
often, you should project Tags into LastPostIndex to avoid fetching from the base table; however, if you
needed to access Tags only occasionally, then the additional storage cost for projecting Tags into the
index might not be worthwhile.
Scanning a Local Secondary Index
You can use Scan to retrieve all of the data from a local secondary index. You must provide the base table
name and the index name in the request. With a Scan, DynamoDB reads all of the data in the index and
returns it to the application. You can also request that only some of the data be returned, and that the
remaining data should be discarded. To do this, use the FilterExpression parameter of the Scan API. For
more information, see Filter Expressions for Scan (p. 427).
Item Writes and Local Secondary Indexes
DynamoDB automatically keeps all local secondary indexes synchronized with their respective base
tables. Applications never write directly to an index. However, it is important that you understand the
implications of how DynamoDB maintains these indexes.
When you create a local secondary index, you specify an attribute to serve as the sort key for the index.
You also specify a data type for that attribute. This means that whenever you write an item to the base
table, if the item deﬁnes an index key attribute, its type must match the index key schema's data type. In
the case of LastPostIndex, the LastPostDateTime sort key in the index is deﬁned as a String data type. If
you attempt to add an item to the Thread table and specify a diﬀerent data type for LastPostDateTime
(such as Number), DynamoDB will return a ValidationException because of the data type mismatch.
If you write an item to a table, you don't have to specify the attributes for any local secondary index sort
key. Using LastPostIndex as an example, you would not need to specify a value for the LastPostDateTime
attribute in order to write a new item to the Thread table. In this case, DynamoDB does not write any
data to the index for this particular item.
There is no requirement for a one-to-one relationship between the items in a base table and the items
in a local secondary index; in fact, this behavior can be advantageous for many applications. For more
information, see Take Advantage of Sparse Indexes (p. 676).
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A table with many local secondary indexes will incur higher costs for write activity than tables with
fewer indexes. For more information, see Provisioned Throughput Considerations for Local Secondary
Indexes (p. 490).
Important
For tables with local secondary indexes, there is a 10 GB size limit per partition key value. A
table with local secondary indexes can store any number of items, as long as the total size for
any one partition key value does not exceed 10 GB. For more information, see Item Collection
Size Limit (p. 493).
Provisioned Throughput Considerations for Local Secondary
Indexes
When you create a table in DynamoDB, you provision read and write capacity units for the table's
expected workload. That workload includes read and write activity on the table's local secondary indexes.
To view the current rates for provisioned throughput capacity, go to https://aws.amazon.com/
dynamodb/pricing.
Read Capacity Units
When you query a local secondary index, the number of read capacity units consumed depends on how
the data is accessed.
As with table queries, an index query can use either eventually consistent or strongly consistent reads
depending on the value of ConsistentRead. One strongly consistent read consumes one read capacity
unit; an eventually consistent read consumes only half of that. Thus, by choosing eventually consistent
reads, you can reduce your read capacity unit charges.
For index queries that request only index keys and projected attributes, DynamoDB calculates the
provisioned read activity in the same way as it does for queries against tables. The only diﬀerence is
that the calculation is based on the sizes of the index entries, rather than the size of the item in the
base table. The number of read capacity units is the sum of all projected attribute sizes across all of
the items returned; the result is then rounded up to the next 4 KB boundary. For more information
on how DynamoDB calculates provisioned throughput usage, see Throughput Settings for Reads and
Writes (p. 294).
For index queries that read attributes that are not projected into the local secondary index, DynamoDB
will need to fetch those attributes from the base table, in addition to reading the projected attributes
from the index. These fetches occur when you include any non-projected attributes in the Select or
ProjectionExpression parameters of the Query operation. Fetching causes additional latency in query
responses, and it also incurs a higher provisioned throughput cost: In addition to the reads from the
local secondary index described above, you are charged for read capacity units for every base table item
fetched. This charge is for reading each entire item from the table, not just the requested attributes.
The maximum size of the results returned by a Query operation is 1 MB; this includes the sizes of all
the attribute names and values across all of the items returned. However, if a Query against a local
secondary index causes DynamoDB to fetch item attributes from the base table, the maximum size of the
data in the results might be lower. In this case, the result size is the sum of:
• The size of the matching items in the index, rounded up to the next 4 KB.
• The size of each matching item in the base table, with each item individually rounded up to the next 4
KB.
Using this formula, the maximum size of the results returned by a Query operation is still 1 MB.
For example, consider a table where the size of each item is 300 bytes. There is a local secondary index
on that table, but only 200 bytes of each item is projected into the index. Now suppose that you Query
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this index, that the query requires table fetches for each item, and that the query returns 4 items.
DynamoDB sums up the following:
• The size of the matching items in the index: 200 bytes &times; 4 items = 800 bytes; this is then rounded up
to 4 KB.
• The size of each matching item in the base table: (300 bytes, rounded up to 4 KB) &times; 4 items = 16 KB.
The total size of the data in the result is therefore 20 KB.
Write Capacity Units
When an item in a table is added, updated, or deleted, updating the local secondary indexes will
consume provisioned write capacity units for the table. The total provisioned throughput cost for a write
is the sum of write capacity units consumed by writing to the table and those consumed by updating the
local secondary indexes.
The cost of writing an item to a local secondary index depends on several factors:
• If you write a new item to the table that deﬁnes an indexed attribute, or you update an existing item
to deﬁne a previously undeﬁned indexed attribute, one write operation is required to put the item into
the index.
• If an update to the table changes the value of an indexed key attribute (from A to B), two writes are
required, one to delete the previous item from the index and another write to put the new item into
the index. • If an item was present in the index, but a write to the table caused the indexed attribute to be deleted,
one write is required to delete the old item projection from the index.
• If an item is not present in the index before or after the item is updated, there is no additional write
cost for the index.
All of these factors assume that the size of each item in the index is less than or equal to the 1 KB item
size for calculating write capacity units. Larger index entries will require additional write capacity units.
You can minimize your write costs by considering which attributes your queries will need to return and
projecting only those attributes into the index.
Storage Considerations for Local Secondary Indexes
When an application writes an item to a table, DynamoDB automatically copies the correct subset of
attributes to any local secondary indexes in which those attributes should appear. Your AWS account is
charged for storage of the item in the base table and also for storage of attributes in any local secondary
indexes on that table.
The amount of space used by an index item is the sum of the following:
• The size in bytes of the base table primary key (partition key and sort key)
• The size in bytes of the index key attribute
• The size in bytes of the projected attributes (if any)
• 100 bytes of overhead per index item
To estimate the storage requirements for a local secondary index, you can estimate the average size of
an item in the index and then multiply by the number of items in the base table.
If a table contains an item where a particular attribute is not deﬁned, but that attribute is deﬁned as an
index sort key, then DynamoDB does not write any data for that item to the index. For more information
about this behavior, see Take Advantage of Sparse Indexes (p. 676).
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Item Collections
Note
The following section pertains only to tables that have local secondary indexes.
In DynamoDB, an item collection is any group of items that have the same partition key value in a table
and all of its local secondary indexes. In the examples used throughout this section, the partition key
for the Thread table is ForumName, and the partition key for LastPostIndex is also ForumName. All the
table and index items with the same ForumName are part of the same item collection. For example, in
the Thread table and the LastPostIndex local secondary index, there is an item collection for forum EC2
and a diﬀerent item collection for forum RDS.
The following diagram shows the item collection for forum S3:
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In this diagram, the item collection consists of all the items in Thread and LastPostIndex where the
ForumName partition key value is &quot;S3&quot;. If there were other local secondary indexes on the table, then any
items in those indexes with ForumName equal to &quot;S3&quot; would also be part of the item collection.
You can use any of the following operations in DynamoDB to return information about item collections:
• BatchWriteItem
• DeleteItem
• PutItem
• UpdateItem
Each of these operations support the ReturnItemCollectionMetrics parameter. When you set this
parameter to SIZE, you can view information about the size of each item collection in the index.
Example
Here is a snippet from the output of an UpdateItem operation on the Thread table, with
ReturnItemCollectionMetrics set to SIZE. The item that was updated had a ForumName value of &quot;EC2&quot;,
so the output includes information about that item collection.
{
}
ItemCollectionMetrics: {
ItemCollectionKey: {
ForumName: &quot;EC2&quot;
},
SizeEstimateRangeGB: [0.0, 1.0]
}
The SizeEstimateRangeGB object shows that the size of this item collection is between 0 and 1 gigabyte.
DynamoDB periodically updates this size estimate, so the numbers might be diﬀerent next time the item
is modiﬁed.
Item Collection Size Limit
The maximum size of any item collection is 10 GB. This limit does not apply to tables without local
secondary indexes; only tables that have one or more local secondary indexes are aﬀected.
If an item collection exceeds the 10 GB limit, DynamoDB will return an
ItemCollectionSizeLimitExceededException and you won't be able to add more items to the item
collection or increase the sizes of items that are in the item collection. (Read and write operations that
shrink the size of the item collection are still allowed.) You will still be able to add items to other item
collections.
To reduce the size of an item collection, you can do one of the following:
• Delete any unnecessary items with the partition key value in question. When you delete these items
from the base table, DynamoDB will also remove any index entries that have the same partition key
value.
• Update the items by removing attributes or by reducing the size of the attributes. If these
attributes are projected into any local secondary indexes, DynamoDB will also reduce the size of the
corresponding index entries.
• Create a new table with the same partition key and sort key, and then move items from the old table
to the new table. This might be a good approach if a table has historical data that is infrequently
accessed. You might also consider archiving this historical data to Amazon Simple Storage Service
(Amazon S3).
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When the total size of the item collection drops below 10 GB, you will once again be able to add items
with the same partition key value.
We recommend as a best practice that you instrument your application to monitor the sizes of your
item collections. One way to do so is to set the ReturnItemCollectionMetrics parameter to SIZE
whenever you use BatchWriteItem, DeleteItem, PutItem or UpdateItem. Your application should examine
the ReturnItemCollectionMetrics object in the output and log an error message whenever an item
collection exceeds a user-deﬁned limit (8 GB, for example). Setting a limit that is less than 10 GB would
provide an early warning system so you know that an item collection is approaching the limit in time to
do something about it.
Item Collections and Partitions
The table and index data for each item collection is stored in a single partition. Referring to the Thread
table example, all of the base table and index items with the same ForumName attribute would be
stored in the same partition. The &quot;S3&quot; item collection would be stored on one partition, &quot;EC2&quot; in another
partition, and &quot;RDS&quot; in a third partition.
You should design your applications so that table data is evenly distributed across distinct partition key
values. For tables with local secondary indexes, your applications should not create &quot;hot spots&quot; of read
and write activity within a single item collection on a single partition. For more information see Best
Practices for Tables (p. 659).
Working with Local Secondary Indexes: Java
Topics
• Create a Table With a Local Secondary Index (p. 494)
• Describe a Table With a Local Secondary Index (p. 496)
• Query a Local Secondary Index (p. 497)
• Example: Local Secondary Indexes Using the Java Document API (p. 497)
You can use the AWS SDK for Java Document API to create a table with one or more local secondary
indexes, describe the indexes on the table, and perform queries using the indexes.
The following are the common steps for table operations using the AWS SDK for Java Document API.
1. Create an instance of the DynamoDB class.
2. Provide the required and optional parameters for the operation by creating the corresponding request
objects.
3. Call the appropriate method provided by the client that you created in the preceding step.
Create a Table With a Local Secondary Index
Local secondary indexes must be created at the same time you create a table. To do this, use the
createTable method and provide your speciﬁcations for one or more local secondary indexes. The
following Java code snippet creates a table to hold information about songs in a music collection. The
partition key is Artist and the sort key is SongTitle. A secondary index, AlbumTitleIndex, facilitates queries
by album title.
The following are the steps to create a table with a local secondary index, using the DynamoDB
document API.
1. Create an instance of the DynamoDB class.
2. Create an instance of the CreateTableRequest class to provide the request information.
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You must provide the table name, its primary key, and the provisioned throughput values. For the
local secondary index, you must provide the index name, the name and data type for the index sort
key, the key schema for the index, and the attribute projection.
3. Call the createTable method by providing the request object as a parameter.
The following Java code snippet demonstrates the preceding steps. The snippet creates a table (Music)
with a secondary index on the AlbumTitle attribute. The table partition key and sort key, plus the index
sort key, are the only attributes projected into the index.
AmazonDynamoDB client = AmazonDynamoDBClientBuilder.standard().build();
DynamoDB dynamoDB = new DynamoDB(client);
String tableName = &quot;Music&quot;;
CreateTableRequest createTableRequest = new CreateTableRequest().withTableName(tableName);
//ProvisionedThroughput
createTableRequest.setProvisionedThroughput(new
ProvisionedThroughput().withReadCapacityUnits((long)5).withWriteCapacityUnits((long)5));
//AttributeDefinitions
ArrayList&lt;AttributeDefinition&gt; attributeDefinitions= new ArrayList&lt;AttributeDefinition&gt;();
attributeDefinitions.add(new
AttributeDefinition().withAttributeName(&quot;Artist&quot;).withAttributeType(&quot;S&quot;));
attributeDefinitions.add(new
AttributeDefinition().withAttributeName(&quot;SongTitle&quot;).withAttributeType(&quot;S&quot;));
attributeDefinitions.add(new
AttributeDefinition().withAttributeName(&quot;AlbumTitle&quot;).withAttributeType(&quot;S&quot;));
createTableRequest.setAttributeDefinitions(attributeDefinitions);
//KeySchema
ArrayList&lt;KeySchemaElement&gt; tableKeySchema = new ArrayList&lt;KeySchemaElement&gt;();
tableKeySchema.add(new
KeySchemaElement().withAttributeName(&quot;Artist&quot;).withKeyType(KeyType.HASH)); //Partition
key
tableKeySchema.add(new
KeySchemaElement().withAttributeName(&quot;SongTitle&quot;).withKeyType(KeyType.RANGE)); //Sort key
createTableRequest.setKeySchema(tableKeySchema);
ArrayList&lt;KeySchemaElement&gt; indexKeySchema = new ArrayList&lt;KeySchemaElement&gt;();
indexKeySchema.add(new
KeySchemaElement().withAttributeName(&quot;Artist&quot;).withKeyType(KeyType.HASH)); //Partition
key
indexKeySchema.add(new
KeySchemaElement().withAttributeName(&quot;AlbumTitle&quot;).withKeyType(KeyType.RANGE)); //Sort
key
Projection projection = new Projection().withProjectionType(ProjectionType.INCLUDE);
ArrayList&lt;String&gt; nonKeyAttributes = new ArrayList&lt;String&gt;();
nonKeyAttributes.add(&quot;Genre&quot;);
nonKeyAttributes.add(&quot;Year&quot;);
projection.setNonKeyAttributes(nonKeyAttributes);
LocalSecondaryIndex localSecondaryIndex = new LocalSecondaryIndex()
.withIndexName(&quot;AlbumTitleIndex&quot;).withKeySchema(indexKeySchema).withProjection(projection);
ArrayList&lt;LocalSecondaryIndex&gt; localSecondaryIndexes = new
ArrayList&lt;LocalSecondaryIndex&gt;();
localSecondaryIndexes.add(localSecondaryIndex);
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createTableRequest.setLocalSecondaryIndexes(localSecondaryIndexes);
Table table = dynamoDB.createTable(createTableRequest);
System.out.println(table.getDescription());
You must wait until DynamoDB creates the table and sets the table status to ACTIVE. After that, you can
begin putting data items into the table.
Describe a Table With a Local Secondary Index
To get information about local secondary indexes on a table, use the describeTable method. For each
index, you can access its name, key schema, and projected attributes.
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Key features

NoSQL database service
Single-digit millisecond latency
Seamless scalability
Fully managed
Frequently asked questions

Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability.
The core components are tables, items, and attributes.
Throughput capacity refers to the amount of read and write activity that DynamoDB can handle for a table or index.
What is DynamoDB?

What are the core components of DynamoDB?

What is throughput capacity?

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