Amazon AWS Schema Conversion Tool User Guide

For more information, see Storing Driver Paths in the Global

If you store the driver path in the global project settings, the driver path doesn't appear on the connection dialog box.

database. For more information, see Installing the Required

3. Choose Test Connection to verify that you can successfully connect to your source database.

4. Choose OK to connect to your source database.

Connecting to a Greenplum Source Database

Use the following procedure to connect to your Greenplum source database with the AWS Schema

Conversion Tool (AWS SCT).

To connect to a Greenplum source database

1. In the AWS Schema Conversion Tool, choose Connect to Greenplum.

The Connect to Greenplum dialog box appears.

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Connecting to a Greenplum Source Database

2. Provide the Greenplum source database connection information. Use the instructions in the following table.

For This Parameter

Server name

Server port

Database

User name and Password

Do This

Type the DNS name or IP address of your source database server.

Type the port used to connect to your source database server.

Type the name of the Greenplum database.

Type the user name and password to connect to your source database server.

Note

AWS SCT uses the password to connect to your source database only when you create your project or choose the

Connect to

source

option in a project, where

source

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Related Topics

For This Parameter

Use SSL

Greenplum Driver Path

Do This

Select this option if you want to use SSL to connect to your database. Provide the following additional information, as appropriate, on the SSL tab:

• Verify Server Certiﬁcate: Select this option to verify the server certiﬁcate by using a trust store.

• Trust Store: The location of a trust store containing certiﬁcates.

• Trust Store Password: The password for the trust store.

Type the path to the driver to use to connect to the source

For more information, see Storing Driver Paths in the Global

If you store the driver path in the global project settings, the driver path doesn't appear on the connection dialog box.

database. For more information, see Installing the Required

3. Choose Test Connection to verify that you can successfully connect to your source database.

4. Choose OK to connect to your source database.

Connecting to a Microsoft SQL Server Source

Database

Use the following procedure to connect to your Microsoft SQL Server source database with the AWS

Schema Conversion Tool (AWS SCT).

To connect to a Microsoft SQL Server source database

1. In the AWS Schema Conversion Tool, choose Connect to Microsoft SQL Server.

The Connect to Microsoft SQL Server dialog box appears.

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Connecting to a Microsoft SQL Server Source Database

2. Provide the Microsoft SQL Server source database connection information. Use the instructions in the following table.

For This Parameter

Server name

Server port

Instance name

User name and Password

Do This

Type the Domain Name Service (DNS) name or IP address of your source database server.

Type the port used to connect to your source database server.

Type the instance name for the SQL Server database. To ﬁnd the instance name, run the query

SELECT @@servername;

on your

SQL Server database.

Type the user name and password to connect to your source database server.

Note

AWS SCT uses the password to connect to your source database only when you create your project or choose the

Connect to

source

option in a project, where

source

is your source database. To guard against exposing the password for your source database, AWS SCT doesn't store the password. If you close your AWS SCT project

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Related Topics

For This Parameter

Use SSL

Sql Server Driver Path

Do This

and reopen it, you are prompted for the password to connect to your source database as needed.

Select this option if you want to use Secure Sockets Layer (SSL) to connect to your database. Provide the following additional information, as appropriate, on the SSL tab:

• Trust Server Certiﬁcate: Select this option to trust the server certiﬁcate.

• Trust Store: The location of a trust store containing certiﬁcates.

• Trust Store Password: The password for the trust store.

Type the path to the driver to use to connect to the source

For more information, see Storing Driver Paths in the Global

If you store the driver path in the global project settings, the driver path doesn't appear on the connection dialog box.

database. For more information, see Installing the Required

3. Choose Test Connection to verify that you can successfully connect to your source database.

4. Choose OK to connect to your source database.

Connecting to a Microsoft SQL Server Data

Warehouse Source Database

Use the following procedure to connect to your Microsoft SQL Server data warehouse source database with the AWS Schema Conversion Tool (AWS SCT).

To connect to a Microsoft SQL Server data warehouse source database

1. In the AWS Schema Conversion Tool, choose Connect to Microsoft SQL Server DW.

The Connect to Microsoft SQL Server DW dialog box appears.

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Connecting to a Microsoft SQL Server

Data Warehouse Source Database

2. Provide the Microsoft SQL Server data warehouse source database connection information. Use the instructions in the following table.

For This Parameter

Server name

Server port

Instance name

User name and Password

Use SSL

Do This

Type the Domain Name Service (DNS) name or IP address of your source database server.

Type the port used to connect to your source database server.

Type the instance name for the SQL Server database. To ﬁnd the instance name, run the query

SELECT @@servername;

on your

SQL Server database.

Type the user name and password to connect to your source database server.

Note

AWS SCT uses the password to connect to your source database only when you create your project or choose the

Connect to

source

option in a project, where

source

Select this option if you want to use Secure Sockets Layer (SSL) to connect to your database. Provide the following additional information, as appropriate, on the SSL tab:

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For This Parameter

Sql Server Driver Path

Do This

• Trust Server Certiﬁcate: Select this option to trust the server certiﬁcate.

• Trust Store: A trust store that you set up in the Global

Settings.

Type the path to the driver to use to connect to the source

For more information, see Storing Driver Paths in the Global

If you store the driver path in the global project settings, the driver path doesn't appear on the connection dialog box.

database. For more information, see Installing the Required

3. Choose Test Connection to verify that you can successfully connect to your source database.

4. Choose OK to connect to your source database.

Connecting to a MySQL Source Database

Use the following procedure to connect to your MySQL source database with the AWS Schema

Conversion Tool (AWS SCT).

To connect to a MySQL source database

1. In the AWS Schema Conversion Tool, choose Connect to MySQL.

The Connect to MySQL dialog box appears.

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Connecting to a MySQL Source Database

2. Provide the MySQL source database connection information. Use the instructions in the following table.

For This Parameter

Server name

Server port

User name and Password

Use SSL

Do This

Type the DNS name or IP address of your source database server.

Type the port used to connect to your source database server.

Type the user name and password to connect to your source database server.

Note

AWS SCT uses the password to connect to your source database only when you create your project or choose the

Connect to

source

option in a project, where

source

Select this option if you want to use SSL to connect to your database. Provide the following additional information, as appropriate, on the SSL tab:

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For This Parameter

MySql Driver Path

Do This

• Require SSL: Select this option if you want to connect to the server only through SSL.

Note

If you choose Require SSL, it means that if the server doesn't support SSL, you can't connect to the server.

If you don't choose Require SSL and the server doesn't support SSL, you can still connect to the server without using SSL. For more information, see

Using Secure Connections .

• Verify Server Certiﬁcate: Select this option to verify the server certiﬁcate by using a trust store.

• Trust Store: The location of a trust store containing certiﬁcates.

• Trust Store Password: The password for the trust store.

Type the path to the driver to use to connect to the source

For more information, see Storing Driver Paths in the Global

If you store the driver path in the global project settings, the driver path doesn't appear on the connection dialog box.

database. For more information, see Installing the Required

3. Choose Test Connection to verify that you can successfully connect to your source database.

4. Choose OK to connect to your source database.

Connecting to a Netezza Source Database

Use the following procedure to connect to your Netezza source database with the AWS Schema

Conversion Tool (AWS SCT).

To connect to a Netezza source database

1. In the AWS Schema Conversion Tool, choose Connect to Netezza.

The Connect to Netezza dialog box appears.

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Connecting to a Netezza Source Database

2. Provide the Netezza source database connection information. Use the instructions in the following table.

For This Parameter

Server name

Server port

User name and Password

Do This

Type the DNS name or IP address of your source database server.

Type the port used to connect to your source database server.

Type the user name and password to connect to your source database server.

Note

AWS SCT uses the password to connect to your source database only when you create your project or choose the

Connect to

source

option in a project, where

source

Netezza Driver Path

Type the path to the driver to use to connect to the source

For more information, see Storing Driver Paths in the Global

If you store the driver path in the global project settings, the driver path doesn't appear on the connection dialog box.

database. For more information, see Installing the Required

3. Choose Test Connection to verify that you can successfully connect to your source database.

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4. Choose OK to connect to your source database.

Connecting to an Oracle Source Database

Use the following procedure to connect to your Oracle source database with the AWS Schema

Conversion Tool (AWS SCT).

To connect to an Oracle source database

1. In the AWS Schema Conversion Tool, choose Connect to Oracle.

The Connect to Oracle dialog box appears.

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Connecting to an Oracle Source Database

2. Provide the Oracle source database connection information. Use the instructions in the following table.

For This Parameter

Type

Do This

Choose the connection type to your database. Depending on your type, provide the following additional information:

•

SID

• Server name: The DNS name or IP address of your source database server.

• Server port: The port used to connect to your source database server.

• Oracle SID: The Oracle System ID (SID). To ﬁnd the Oracle

SID, submit the following query to your Oracle database:

SELECT sys_context('userenv','instance_name') AS SID

FROM dual;

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Use SSL

AWS Schema Conversion Tool User Guide

Connecting to an Oracle Source Database

User name and Password

Do This

•

Service Name

•

Server name: The DNS name or IP address of your source database server.

• Server port: The port used to connect to your source database server.

• Service Name: The name of the Oracle service to connect to.

•

TNS Alias

• TNS ﬁle path: The path to the ﬁle that contains the

Transparent Network Substrate (TNS) name connection information.

• TNS ﬁle path: The TNS alias from this ﬁle to use to connect to the source database.

•

TNS Connect Identiﬁer

• TNS identiﬁer: The identiﬁer for the registered TNS connection information.

Type the user name and password to connect to your source database server.

Note

AWS SCT uses the password to connect to your source database only when you create your project or choose the

Connect to

source

option in a project, where

source

Select this option if you want to use SSL to connect to your database. Provide the following additional information, as appropriate, on the SSL tab:

• SSL Authentication: Select this option to use SSL authentication for the connection.

• Trust Store: The location of a trust store containing certiﬁcates.

• Trust Store Password: The password for the trust store.

• Key Store: The location of a key store containing a private key and certiﬁcates. This value is required if SSL Authentication is selected and is otherwise optional.

• Trust Store Password: The password for the key store. This value is required if SSL Authentication is selected and is otherwise optional.

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For This Parameter

Oracle Driver Path

Do This

Type the path to the driver to use to connect to the source

For more information, see Storing Driver Paths in the Global

If you store the driver path in the global project settings, the driver path doesn't appear on the connection dialog box.

database. For more information, see Installing the Required

3. Choose Test Connection to verify that you can successfully connect to your source database.

4. Choose OK to connect to your source database.

Connecting to an Oracle Data Warehouse Source

Database

Use the following procedure to connect to your Oracle data warehouse source database with the AWS

Schema Conversion Tool (AWS SCT).

To connect to an Oracle data warehouse source database

1. In the AWS Schema Conversion Tool, choose Connect to Oracle DW.

The Connect to Oracle dialog box appears.

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Connecting to an Oracle Data Warehouse Source Database

2. Provide the Oracle Data Warehouse source database connection information. Use the instructions in the following table.

For This Parameter

Type

Do This

Choose the connection type to your database. Depending on your type, provide the following additional information:

•

SID

• Server name: The DNS name or IP address of your source database server.

• Server port: The port used to connect to your source database server.

• Oracle SID: The Oracle System ID (SID). To ﬁnd the Oracle

SID, submit the following query to your Oracle database:

SELECT sys_context('userenv','instance_name') AS SID

FROM dual;

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Connecting to an Oracle Data Warehouse Source Database

For This Parameter

User name and Password

Use SSL

Do This

•

Service Name

•

Server name: The DNS name or IP address of your source database server.

• Server port: The port used to connect to your source database server.

• Service Name: The name of the Oracle service to connect to.

•

TNS Alias

• TNS ﬁle path: The path to the ﬁle that contains the

Transparent Network Substrate (TNS) name connection information.

• TNS ﬁle path: The TNS alias from this ﬁle to use to connect to the source database.

•

TNS Connect Identiﬁer

• TNS identiﬁer: The identiﬁer for the registered TNS connection information.

Type the user name and password to connect to your source database server.

Note

AWS SCT uses the password to connect to your source database only when you create your project or choose the

Connect to

source

option in a project, where

source

Select this option if you want to use SSL to connect to your database. Provide the following additional information, as appropriate, on the SSL tab:

• SSL Authentication: Select this option to use SSL authentication for the connection.

• Trust Store: The location of a trust store containing certiﬁcates.

• Trust Store Password: The password for the trust store.

• Key Store: The location of a key store containing a private key and certiﬁcates. This value is required if SSL Authentication is selected and is otherwise optional.

• Trust Store Password: The password for the key store. This value is required if SSL Authentication is selected and is otherwise optional.

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Related Topics

For This Parameter

Oracle Driver Path

Do This

Type the path to the driver to use to connect to the source

For more information, see Storing Driver Paths in the Global

If you store the driver path in the global project settings, the driver path doesn't appear on the connection dialog box.

database. For more information, see Installing the Required

3. Choose Test Connection to verify that you can successfully connect to your source database.

4. Choose OK to connect to your source database.

Connecting to a PostgreSQL Source Database

Use the following procedure to connect to your PostgreSQL source database with the AWS Schema

Conversion Tool (AWS SCT).

To connect to a PostgreSQL source database

1. In the AWS Schema Conversion Tool, choose Connect to PostgreSQL.

The Connect to PostgreSQL dialog box appears.

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Connecting to a PostgreSQL Source Database

2. Provide the PostgreSQL source database connection information. Use the instructions in the following table.

For This Parameter

Server name

Server port

Database

User name and Password

Do This

Type the DNS name or IP address of your source database server.

Type the port used to connect to your source database server.

Type the name of the PostgreSQL database.

Type the user name and password to connect to your source database server.

Note

AWS SCT uses the password to connect to your source database only when you create your project or choose the

Connect to

source

option in a project, where

source

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Related Topics

For This Parameter

Use SSL

PostgreSQL Driver Path

Do This

Select this option if you want to use SSL to connect to your database. Provide the following additional information, as appropriate, on the SSL tab:

• Verify Server Certiﬁcate: Select this option to verify the server certiﬁcate by using a trust store.

• Trust Store: The location of a trust store containing certiﬁcates.

• Trust Store Password: The password for the trust store.

Type the path to the driver to use to connect to the source

For more information, see Storing Driver Paths in the Global

If you store the driver path in the global project settings, the driver path doesn't appear on the connection dialog box.

database. For more information, see Installing the Required

3. Choose Test Connection to verify that you can successfully connect to your source database.

4. Choose OK to connect to your source database.

Connecting to a Teradata Source Database

Use the following procedure to connect to your Teradata source database with the AWS Schema

Conversion Tool (AWS SCT).

To connect to a Teradata source database

1. In the AWS Schema Conversion Tool, choose Connect to Teradata.

The

Connect to Teradata dialog box appears.

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Connecting to a Teradata Source Database

2. Provide the Teradata source database connection information. Use the instructions in the following table.

For This Parameter

Server name

Server port

Database

User name and Password

Do This

Type the DNS name or IP address of your source database server.

Type the port used to connect to your source database server.

Type the name of the Teradata database.

Type the user name and password to connect to your source database server.

Note

AWS SCT uses the password to connect to your source database only when you create your project or choose the

Connect to

source

option in a project, where

source

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For This Parameter

Encrypt Data

Teradata Driver Path

Do This

Select this option if you want to encrypt data that you exchange with the database.

Type the path to the driver to use to connect to the source

For more information, see Storing Driver Paths in the Global

If you store the driver path in the global project settings, the driver path doesn't appear on the connection dialog box.

database. For more information, see Installing the Required

3. Choose Test Connection to verify that you can successfully connect to your source database.

4. Choose OK to connect to your source database.

Connecting to a Vertica Source Database

Use the following procedure to connect to your Vertica source database with the AWS Schema

Conversion Tool (AWS SCT).

To connect to a Vertica source database

1. In the AWS Schema Conversion Tool, choose Connect to Vertica.

The Connect to Vertica dialog box appears.

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Connecting to a Vertica Source Database

2. Provide the Vertica source database connection information. Use the instructions in the following table.

For This Parameter

Server name

Server port

Database

User name and Password

Use SSL

Do This

Type the DNS name or IP address of your source database server.

Type the port used to connect to your source database server.

Type the name of the Vertica database.

Type the user name and password to connect to your source database server.

Note

AWS SCT uses the password to connect to your source database only when you create your project or choose the

Connect to

source

option in a project, where

source

Select this option if you want to use SSL to connect to your database. Provide the following additional information, as appropriate, on the SSL tab:

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For This Parameter

Vertica Driver Path

Do This

• Trust Store: A trust store that you set up in the Global

Settings.

• Key Store: A key store that you set up in the Global Settings.

Type the path to the driver to use to connect to the source

For more information, see Storing Driver Paths in the Global

If you store the driver path in the global project settings, the driver path doesn't appear on the connection dialog box.

Converting Database Schema to Amazon RDS by Using the AWS Schema Conversion Tool (p. 68)

3. Choose Test Connection to verify that you can successfully connect to your source database.

4. Choose OK to connect to your source database.

Working with Databases

You can use the AWS Schema Conversion Tool (AWS SCT) to convert your existing database schema from one database engine to another. Your converted schema is suitable for Amazon Relational Database

Service (Amazon RDS).

You can also use AWS SCT to copy your existing on-premises database schema to an Amazon RDS DB instance running the same engine. You can use this feature to analyze potential cost savings of moving to the cloud and of changing your license type.

In some cases, database features can't be converted to equivalent Amazon RDS features. If you host and self-manage a database on the Amazon Elastic Compute Cloud (Amazon EC2) platform, you can emulate these features by substituting AWS services for them.

Following, you can ﬁnd more information about these processes.

Topics

•

•

The AWS Schema Conversion Tool Extension Pack and AWS Services for Databases (p. 84)

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Converting Database Schema

Converting Database Schema to Amazon RDS by

Using the AWS Schema Conversion Tool

The AWS Schema Conversion Tool (AWS SCT) automates much of the process of converting your online transaction processing (OLTP) database schema to an Amazon Relational Database Service (Amazon

RDS) MySQL DB instance, an Amazon Aurora DB cluster, or a PostgreSQL DB instance. The source and target database engines contain many diﬀerent features and capabilities, and AWS SCT attempts to create an equivalent schema in your Amazon RDS DB instance wherever possible. If no direct conversion is possible, AWS SCT provides a list of possible actions for you to take.

AWS SCT supports the following OLTP conversions.

Source Database

Microsoft SQL Server (version 2008 and later)

MySQL (version 5.6 and later)

Oracle (version 10.2 and later)

PostgreSQL (version 9.1 and later)

Target Database on Amazon RDS

Amazon Aurora (MySQL or PostgreSQL), Microsoft

SQL Server, MySQL, PostgreSQL

Amazon Aurora (PostgreSQL), MySQL, PostgreSQL

Amazon Aurora (MySQL or PostgreSQL), MySQL,

Oracle, PostgreSQL

Amazon Aurora (MySQL), MySQL, PostgreSQL

If you want to convert a data warehouse schema, see

Converting Data Warehouse Schema to Amazon

Redshift by Using the AWS Schema Conversion Tool (p. 87)

Almost all work you do with AWS SCT starts with the following three steps:

1. Create an AWS SCT project.

2. Connect to your source database.

3. Connect to your target database.

If you have not created an AWS SCT project yet, see

Creating Mapping Rules in the AWS Schema Conversion Tool (p. 69)

To convert your database schema to Amazon RDS, you take the following high-level steps:

• Create mapping rules – Before you convert your schema with AWS SCT, you can set up rules that change the data type of columns, move objects from one schema to another, and change the names of objects.

For more information, see

• Convert your schema – AWS SCT creates a local version of the converted schema for you to review, but it doesn't apply it to your target DB instance until you are ready.

For more information, see

Converting Your Schema by Using the AWS Schema Conversion

Tool (p. 71) .

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• Create a database migration assessment report – AWS SCT creates a database migration assessment report that details the schema elements that can't be converted automatically. You can use this report to identify where you need to create a schema in your Amazon RDS DB instance that is compatible with your source database.

For more information, see

Creating and Using the Assessment Report in the AWS Schema Conversion

Tool (p. 75) .

• Decide how to handle manual conversions – If you have schema elements that can't be converted automatically, you have 2 choices: update the source schema and then convert again, or create equivalent schema elements in your target Amazon RDS DB instance.

For more information, see

Handling Manual Conversions in the AWS Schema Conversion

Tool (p. 79) .

• Update and refresh the schema in your AWS SCT project – You can update your AWS SCT project with the most recent schema from your source database.

For more information, see

Updating and Refreshing Your Converted Schema in the AWS Schema

Conversion Tool (p. 80)

• Apply the converted schema to your target database – When you are ready, have AWS SCT apply the converted schema in your local project to your target Amazon RDS DB instance.

For more information, see

Saving and Applying Your Converted Schema in the AWS Schema

Conversion Tool (p. 81)

Creating Mapping Rules in the AWS Schema

Conversion Tool

Before you convert your schema with the AWS Schema Conversion Tool (AWS SCT), you can set up rules that change the data type of columns, move objects from one schema to another, and change the names of objects. For example, if you have a set of tables in your source schema named test_TABLE_NAME

, you can set up a rule that changes the preﬁx test_

to the preﬁx demo_

in the target schema.

Note

You can only create mapping rules if your source database engine and target database engine are diﬀerent.

You can create mapping rules that perform the following tasks:

• Change data type

• Move objects

• Rename objects

• Prefix - add prefix, remove prefix, replace prefix

• Suffix - add suffix, remove suffix, replace suffix

You can create mapping rules for the following objects:

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• Database

• Schema

• Table

• Column

Creating Mapping Rules

You can create mapping rules and save the rules as part of your project. With your project open, use the following procedure to create mapping rules.

To create mapping rules

1. Choose Mapping Rules from the Settings menu. The Mapping Rules dialog box appears.

2. Choose Add new rule. A new row is added to the list of rules.

3. Choose the edit icon to conﬁgure your rule.

a. For Name, type a name for your rule.

b. For For, choose the type of object that the rule applies to.

For where, type a ﬁlter to apply to objects before applying the mapping rule. The where clause is evaluated by using a like clause. You can enter an exact name to select one object, or you can enter a pattern to select multiple objects.

The fields available for the where clause are different depending on the type of the object. For example, if the object type is schema there is only one field available, for the schema name.

d. For Actions, choose the type of mapping rule you want to create.

e. Depending on the rule type, type one or two additional values. For example, to rename an object, type the new name of the object. To replace a prefix, type the old prefix and the new prefix.

4. After you have conﬁgured your mapping rule, choose Save to save your rule. You can also choose

Cancel to cancel your changes.

5. After you are done adding, editing, and deleting rules, choose Save All to save all your changes.

6. Choose Close to close the Mapping Rules dialog box.

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Converting Your Schema

You can use the toggle icon to turn oﬀ a mapping rule without deleting it. You can use the copy icon to duplicate an existing mapping rule. You can use the delete icon to delete an existing mapping rule. To save any changes you make to your mapping rules, choose Save All.

Viewing Mapping Rules for Objects

After you set up your mapping rules, you can view the eﬀect of the rules on speciﬁc objects in your schema before you convert your schema. In the source schema tree, choose the object you are interested in. In the main view, choose the Mapping tab. The Mapping tab opens and displays a list of all mapping rules that are applied to the object. You can see the name of the object in the source schema and the new name of the object in the target schema. If you have data type rules, you also see the data type of the column in the source schema and the new data type of the column in the target schema.

Exporting Mapping Rules

If you use AWS Database Migration Service (AWS DMS) to migrate your data from your source database to your target database, you can provide information about your mapping rules to AWS DMS. For more information about tasks, see Working with AWS Database Migration Service Replication Tasks .

To export mapping rules

1. In the AWS Schema Conversion Tool, in the source schema tree, open the context (right-click) menu and choose Export script for DMS. The save dialog box opens.

2. Browse to the location where you want to save your script, and then choose Save. Your mapping rules are saved as a JSON script that can be consumed by AWS DMS.

Converting Your Schema by Using the AWS Schema

Conversion Tool

After you have connected your project to both your source database and your target Amazon RDS DB instance, your AWS Schema Conversion Tool (AWS SCT) project displays the schema from your source database in the left panel. The schema is presented in a tree-view format, and each node of the tree is lazy loaded. When you choose a node in the tree view, AWS SCT requests the schema information from your source database at that time.

You can choose schema items from your source database and then convert the schema to equivalent schema for the DB engine of your target DB instance. You can choose any schema item from your source database to convert. If the schema item that you choose depends on a parent item, then AWS SCT also generates the schema for the parent item. For example, if you choose a column from a table to convert, then AWS SCT generates the schema for the column, the table that the column is in, and the database that the table is in.

Converting Schema

To convert schema from your source database, choose a schema object to convert from the left panel of your project. Open the context (right-click) menu for the object, and then choose Convert schema, as shown following.

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After you have converted the schema from your source database, you can choose schema items from the left panel of your project and view the converted schema in the center panels of your project. The lowercenter panel displays the properties of and the SQL command to create the converted schema, as shown following.

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Converting Your Schema

After you have converted your schema, you can save your project. The schema information from your source database is saved with your project. This functionality means that you can work oﬄine without being connected to your source database. AWS SCT connects to your source database to update the schema in your project if you choose

Refresh from Database for your source database. For more information, see

Updating and Refreshing Your Converted Schema in the AWS Schema Conversion

Tool (p. 80) .

You can create a database migration assessment report of the items that can't be converted automatically. The assessment report is useful for identifying and resolving schema items that can't be converted automatically. For more information, see

Creating and Using the Assessment Report in the

AWS Schema Conversion Tool (p. 75) .

When AWS SCT generates a converted schema, it doesn't immediately apply it to the target DB instance.

Instead, the converted schema is stored locally until you are ready to apply it to the target DB instance.

For more information, see

Applying Your Converted Schema (p. 82) .

Editing Converted Schema

You can edit converted schema and save the changes as part of your project.

To edit converted schema

1. In the left panel that displays the schema from your source database, choose the schema item that you want to edit the converted schema for.

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Converting Your Schema

2. In the lower-center panel that displays the converted schema for the selected item, choose the

SQL

tab.

3. In the text displayed for the SQL tab, change the schema as needed. The schema is automatically saved with your project as you update it.

The changes that you make to converted schema are stored with your project as you make updates. If you newly convert a schema item from your source database, and you have made updates to previously converted schema for that item, those existing updates are replaced by the newly converted schema item based on your source database.

Clearing a Converted Schema

Until you apply the schema to your target DB instance, AWS SCT only stores the converted schema locally in your project. You can clear the planned schema from your project by choosing the tree-view node for your target DB instance, and then choosing Refresh from Database. Because no schema has been written to your target DB instance, refreshing from the database removes the planned schema elements in your AWS SCT project to match what exists in your target DB instance.

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Creating and Using the Assessment Report

Creating and Using the Assessment Report in the

AWS Schema Conversion Tool

The AWS Schema Conversion Tool (AWS SCT) creates a database migration assessment report to help you convert your schema. The database migration assessment report provides important information about the conversion of the schema from your source database to your target Amazon RDS DB instance.

The report summarizes all of the schema conversion tasks and details the action items for schema that can't be converted to the DB engine of your target DB instance. The report also includes estimates of the amount of eﬀort that it will take to write the equivalent code in your target DB instance that can't be converted automatically.

If you are using AWS SCT to copy your existing on-premises database schema to an Amazon RDS DB instance running the same engine, the report can help you analyze requirements for moving to the cloud and for changing your license type.

Creating a Database Migration Assessment Report

Use the following procedure to create a database migration assessment report.

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Creating and Using the Assessment Report

To create a database migration assessment report

1. In the left panel that displays the schema from your source database, choose a schema object to create an assessment report for.

2. Open the context (right-click) menu for the object, and then choose Create Report.

Assessment Report Summary

After you create an assessment report, the assessment report view opens, showing the Summary tab.

The Summary tab displays the summary information from the database migration assessment report. It shows items that were converted automatically, and items that were not converted automatically.

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Creating and Using the Assessment Report

For schema items that can't be converted automatically to the target database engine, the summary includes an estimate of the eﬀort that it takes to create schema items in your target DB instance that are equivalent to those in your source database.

The report categorizes the estimated time to convert these schema items as follows:

• Simple – Actions that can be completed in less than 1 hour.

• Medium – Actions that are more complex and can be completed in 1 to 4 hours.

• Signiﬁcant – Actions that are very complex and take more than 4 hours to complete.

Assessment Report Action Items

The assessment report view also includes an Action Items tab. This tab contains a list of items that can't be converted automatically to the database engine of your target Amazon RDS DB instance. If you select an action item from the list, AWS SCT highlights the item from your schema that the action item applies to.

The report also contains recommendations for how to manually convert the schema item. For more

information about deciding how to handle manual conversions, see Handling Manual Conversions in the

AWS Schema Conversion Tool (p. 79) .

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Saving the Assessment Report

You can save a local copy of the database migration assessment report as either a PDF file or a commaseparated values (CSV) file. The CSV file contains only action item information. The PDF file contains both the summary and action item information, as shown in the following example.

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Handling Manual Conversions

Handling Manual Conversions in the AWS Schema

Conversion Tool

The assessment report includes a list of items that can't be converted automatically to the database engine of your target Amazon RDS DB instance. For each item that can't be converted, there is an action item on the Action Items tab.

You can respond to the action items in the assessment report in the following ways:

• Modify your source database schema.

• Modify your target database schema.

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Updating and Refreshing Your Converted Schema

Modifying Your Source Schema

For some items, it might be easier to modify the database schema in your source database to schema that can be converted automatically. First, verify that the new changes are compatible with your application architecture, then update the schema in your source database. Finally, refresh your project with the updated schema information. You can then convert your updated schema, and generate a new database migration assessment report. The action items no longer appear for the items that changed in the source schema.

The advantage of this process is that your updated schema is always available when you refresh from your source database.

Modifying Your Target Schema

For some items, it might be easier to apply the converted schema to your target database, and then add equivalent schema items manually to your target database for the items that couldn't be converted automatically. You can write all of the schema that can be converted automatically to your target

DB instance by applying the schema. For more information, see

Saving and Applying Your Converted

Schema in the AWS Schema Conversion Tool (p. 81)

The schema that are written to your target DB instance don't contain the items that can't be converted automatically. After applying the schema to your target DB instance, you can then manually create schema in your target DB instance that are equivalent to those in the source database. The action items in the database migration assessment report contain suggestions for how to create the equivalent schema.

Warning

If you manually create schema in your target DB instance, save a copy of any manual work that you do. If you apply the converted schema from your project to your target DB instance again, it overwrites the manual work you have done.

In some cases, you can't create equivalent schema in your target DB instance. You might need to rearchitect a portion of your application and database to use the functionality that is available from the

DB engine for your target DB instance. In other cases, you can simply ignore the schema that can't be converted automatically.

Related Topics

•

Converting Your Schema by Using the AWS Schema Conversion Tool (p. 71)

•

Creating and Using the Assessment Report in the AWS Schema Conversion Tool (p. 75)

•

Updating and Refreshing Your Converted Schema in the AWS Schema Conversion Tool (p. 80)

Updating and Refreshing Your Converted Schema in the AWS Schema Conversion Tool

You can update both the source schema and the target schema in your AWS Schema Conversion Tool

(AWS SCT) project.

• Source – If you update the schema for your source database, AWS SCT replaces the schema in your project with the latest schema from your source database. Using this functionality, you can update your project if changes have been made to the schema of your source database.

•

Target – If you update the schema for your target Amazon RDS DB instance, AWS SCT replaces the schema in your project with the latest schema from your target DB instance. If you haven't applied any

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Saving and Applying Your Schema

schema to your target DB instance, AWS SCT clears the converted schema from your project. You can then convert the schema from your source database for a clean target DB instance.

You update the schema in your AWS SCT project by choosing Refresh from Database, as shown following.

Saving and Applying Your Converted Schema in the

AWS Schema Conversion Tool

When the AWS Schema Conversion Tool (AWS SCT) generates converted schema (as shown in

Converting

Your Schema by Using the AWS Schema Conversion Tool (p. 71) ), it doesn't immediately apply the

converted schema to the target DB instance. Instead, converted schema are stored locally in your project until you are ready to apply them to the target DB instance. Using this functionality, you can work with schema items that can't be converted automatically to your target DB engine. For more information on

items that can't be converted automatically, see Creating and Using the Assessment Report in the AWS

Schema Conversion Tool (p. 75)

You can optionally have the tool save your converted schema to a ﬁle as a SQL script prior to applying the schema to your target DB instance. You can also have the tool apply the converted schema directly to your target DB instance.

Saving Your Converted Schema to a File

You can save your converted schema as SQL scripts in a text ﬁle. By using this approach, you can modify the generated SQL scripts from AWS SCT to address items that the tool can't convert automatically. You

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Saving and Applying Your Schema can then run your updated scripts on your target DB instance to apply your converted schema to your target database.

To save your converted schema as SQL scripts, open the context (right-click) menu for the schema element, and choose Save as SQL, as shown following.

Applying Your Converted Schema

When you are ready to apply your converted schema to your target Amazon RDS DB instance, choose the schema element from the right panel of your project. Open the context (right-click) menu for the schema element, and then choose Apply to database, as shown following.

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Saving and Applying Your Schema

The Extension Pack Schema

The ﬁrst time that you apply your converted schema to your target DB instance, AWS SCT adds an additional schema to your target DB instance. This schema implements system functions of the source database that are required when writing your converted schema to your target DB instance. The schema is called the extension pack schema.

Don't modify the extension pack schema, or you might encounter unexpected results in the converted schema that is written to your target DB instance. When your schema is fully migrated to your target DB instance, and you no longer need AWS SCT, you can delete the extension pack schema.

The extension pack schema is named according to your source database as follows:

• Microsoft SQL Server:

AWS_SQLSERVER_EXT

• MySQL:

AWS_MYSQL_EXT

• Oracle:

AWS_ORACLE_EXT

• PostgreSQL:

AWS_POSTGRESQL_EXT

For more information, see

The AWS Schema Conversion Tool Extension Pack and AWS Services for

Databases (p. 84) .

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The Extension Pack and AWS Services for Databases

The AWS Schema Conversion Tool Extension Pack and AWS Services for Databases

When you convert your database schema, the AWS Schema Conversion Tool (AWS SCT) adds an additional schema to your target DB instance. This schema implements system functions of the source database that are required when writing your converted schema to your target DB instance. The schema is called the extension pack schema.

The extension pack schema is named according to your source database as follows:

• Microsoft SQL Server:

AWS_SQLSERVER_EXT

• MySQL:

AWS_MYSQL_EXT

• Oracle:

AWS_ORACLE_EXT

• PostgreSQL:

AWS_POSTGRESQL_EXT

In two cases, you might want to install the extension pack manually:

• You accidentally delete the extension pack database schema from your target database.

• You want to use AWS services to emulate database functionality.

Using AWS Services to Emulate Database

Functionality

In some cases, database features can't be converted to equivalent Amazon Relational Database Service

(Amazon RDS) features. Some examples are Oracle send email calls that use

UTL_SMTP

, and Microsoft

SQL Server jobs that use a job scheduler. If you host and self-manage a database on the Amazon Elastic

Compute Cloud (Amazon EC2) platform, you can emulate these features by substituting AWS services for them.

The AWS SCT extension pack wizard helps you install, create, and conﬁgure AWS Lambda functions to emulate email, job scheduling, and other features.

Before You Begin

Almost all work you do with the AWS SCT starts with the following three steps:

1. Create an AWS SCT project.

2. Connect to your source database.

3. Connect to your target database.

If you have not created an AWS SCT project yet, see

see Converting Database Schema to Amazon RDS by Using the AWS Schema Conversion Tool (p. 68) .

Before you install the extension pack, you need to convert your database schema. For more information,

Applying the Extension Pack

Use the following procedure to apply the extension pack.

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Applying the Extension Pack

Important

The AWS service emulation features are supported only for databases installed and selfmanaged on the Amazon EC2 platform. Don't install the service emulation features if your target database is on an Amazon RDS DB instance.

To apply the extension pack

1. In the AWS Schema Conversion Tool, in the target database tree, open the context (right-click) menu, and choose Apply Extension Pack.

The extension pack wizard appears.

2. Read the Welcome page, and then choose Next.

3. On the AWS Services Settings page, do the following:

• If you are reinstalling the extension pack database schema only, choose Skip this step for now, and then choose Next.

• If you are installing AWS services, provide the credentials to connect to your AWS account. You can use your AWS Command Line Interface (AWS CLI) credentials if you have the AWS CLI installed.

You can also use credentials that you previously stored in a profile in the global application settings and associated with the project. If necessary, choose Navigate to Project Settings to associate a different profile with the project. If necessary, choose Global Settings to create a new profile. For more information, see

Storing AWS Proﬁles in the AWS Schema Conversion

Tool (p. 131)

4. On the Email Sending Service page, do the following:

• If you are reinstalling the extension pack database schema only, choose Skip this step for now, and then choose Next.

• If you are installing AWS services and you have an existing AWS Lambda function, you can provide it. Otherwise the wizard creates it for you. When you are done, choose Next.

5. On the Job Emulation Service page, do the following:

• If you are reinstalling the extension pack database schema only, choose Skip this step for now, and then choose Next.

• If you are installing AWS services and you have an existing AWS Lambda function, you can provide it. Otherwise the wizard creates it for you. When you are done, choose Next.

6. On the Functions Emulation page, choose Create Extension Pack. Messages appear with the status of the extension pack operations. When you are done, choose Finish.

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Working with Data Warehouses

You can use the AWS Schema Conversion Tool (AWS SCT) to convert your existing data warehouse schema. Your converted schema is suitable for an Amazon Redshift cluster.

In some cases, source database features can't be converted to equivalent Amazon Redshift features.

The AWS SCT extension pack contains a custom Python library that emulates some source database functionality on Amazon Redshift.

You can use data extraction agents to extract data from your data warehouse to prepare to migrate it to

Amazon Redshift. To manage the data extraction agents, you can use AWS SCT.

You can use AWS SCT to optimize your existing Amazon Redshift database. AWS SCT recommends sort keys and distribution keys to optimize your database.

Following, you can ﬁnd more information about these processes.

Topics

•

Converting Data Warehouse Schema to Amazon Redshift by Using the AWS Schema Conversion

Tool (p. 87)

•

The AWS Schema Conversion Tool Extension Pack and Python Libraries for Data

Warehouses (p. 108)

•

Using Data Extraction Agents (p. 110)

•

Optimizing Amazon Redshift by Using the AWS Schema Conversion Tool (p. 119)

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Converting Data Warehouse Schema

Converting Data Warehouse Schema to Amazon

Redshift by Using the AWS Schema Conversion

Tool

The AWS Schema Conversion Tool (AWS SCT) automates much of the process of converting your data warehouse schema to a Amazon Redshift database schema. The source and target database engines contain many diﬀerent features and capabilities, and AWS SCT attempts to create an equivalent schema in your target database wherever possible. If no direct conversion is possible, AWS SCT provides a list of possible actions for you to take.

AWS SCT supports the following data warehouse conversions.

Source Database

Greenplum Database (version 4.3 and later)

Microsoft SQL Server (version 2008 and later)

Netezza (version 7.2 and later)

Oracle (version 11 and later)

Teradata (version 14 and later)

Vertica (version 7.2.2 and later)

Target Database on Amazon Redshift

Amazon Redshift

If you want to convert an online transaction processing (OLTP) database schema, see Converting

Database Schema to Amazon RDS by Using the AWS Schema Conversion Tool (p. 68)

Almost all work you do with AWS SCT starts with the following three steps:

1. Create an AWS SCT project.

2. Connect to your source database.

3. Connect to your target database.

If you have not created an AWS SCT project yet, see

Choosing Optimization Strategies and Rules for Use with the AWS Schema

To convert your data warehouse schema to Amazon RDS, you take the following high-level steps:

• Choose your optimization strategy – To optimize how AWS SCT converts your data warehouse schema, you can choose the strategies and rules you want the tool to use.

For more information, see

Conversion Tool (p. 89)

• Collect statistics – To optimize how AWS SCT converts your data warehouse schema, you can provide statistics from your source database that the tool can use. You can either collect statistics directly from the database, or upload an existing statistics ﬁle.

For more information, see

Collecting or Uploading Statistics for the AWS Schema Conversion

Tool (p. 90) .

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Converting Data Warehouse Schema

For more information, see

Creating Mapping Rules in the AWS Schema Conversion Tool (p. 91)

• Convert your schema – AWS SCT creates a local version of the converted schema for you to review, but it doesn't apply it to your target database until you are ready.

For more information, see

Converting Your Schema by Using the AWS Schema Conversion

Tool (p. 93) .

• Manage and customize keys – After you convert your schema, you can manage and edit your keys. Key management is the heart of a data warehouse conversion.

For more information, see

Managing and Customizing Keys in the AWS Schema Conversion

Tool (p. 97) .

• Create a database migration assessment report – AWS SCT creates a database migration assessment report that details the schema elements that can't be converted automatically. You can use this report to identify where you need to manually create a schema in your target database that is compatible with your source database.

For more information, see

Creating and Using the Assessment Report in the AWS Schema Conversion

Tool (p. 98) .

• Decide how to handle manual conversions – If you have schema elements that can't be converted automatically, you have two choices: update the source schema and then convert again, or create equivalent schema elements in your target database.

For more information, see

Handling Manual Conversions in the AWS Schema Conversion

Tool (p. 102) .

• Update and refresh the schema in your AWS SCT project – You can update your AWS SCT project with the most recent schema from your source database.

For more information, see

Updating and Refreshing Your Converted Schema in the AWS Schema

Conversion Tool (p. 103)

• Apply the converted schema to your target database – When you are ready, have AWS SCT apply the converted schema in your local project to your target database.

For more information, see

Saving and Applying Your Converted Schema in the AWS Schema

Conversion Tool (p. 104)

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Choosing Optimization Strategies and Rules

Choosing Optimization Strategies and Rules for Use with the AWS Schema Conversion Tool

To optimize how the AWS Schema Conversion Tool (AWS SCT) converts your data warehouse schema, you can choose the strategies and rules you want the tool to use. After converting your schema, and reviewing the suggested keys, you can adjust your rules or change your strategy to get the results you want.

To choose your optimization strategies and rules

1. Choose Settings, and then choose Project Settings. The Current project settings dialog box appears.

2. In the left pane, choose Optimization Strategies. The optimization strategies appear in the right pane with the defaults selected.

3. For Strategy Sector, choose the optimization strategy you want to use. You can choose from the following:

•

Use metadata, ignore statistical information – In this strategy, only information from the metadata is used for optimization decisions. For example, if there is more than one index on a source table, the source database sort order is used, and the ﬁrst index becomes a distribution key.

• Ignore metadata, use statistical information – In this strategy, optimization decisions are derived from statistical information only. This strategy applies only to tables and columns for which statistics are provided. For more information, see

Collecting or Uploading Statistics for the AWS

Schema Conversion Tool (p. 90) .

• Use metadata and use statistical information – In this strategy, both metadata and statistics are used for optimization decisions.

4. After you choose your optimization strategy, you can choose the rules you want to use. You can choose from the following:

•

Choose Distribution Key and Sort Keys using metadata

•

Choose fact table and appropriate dimension for collation

•

Analyze cardinality of indexes' columns

•

Find the most used tables and columns from QueryLog table

For each rule, you can enter a weight for the sort key and a weight for the distribution key. AWS SCT uses the weights you choose when it converts your schema. Later, when you review the suggested keys, if you are not satisﬁed with the results, you can return here and change your settings. For more

information, see Managing and Customizing Keys in the AWS Schema Conversion Tool (p. 97) .

Related Topics

• Choose the Best Sort Key

• Choose the Best Distribution Style

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Collecting or Uploading Statistics

Collecting or Uploading Statistics for the AWS

Schema Conversion Tool

To optimize how the AWS Schema Conversion Tool (AWS SCT) converts your data warehouse schema, you can provide statistics from your source database that the tool can use. You can either collect statistics directly from the database, or upload an existing statistics ﬁle.

To provide and review statistics

1. Connect to your source database. For more information, see

Connecting to Your Source

Database (p. 13)

2. Choose a schema object from the left panel of your project, and open the context (right-click) menu for the object. Choose Collect Statistics or Upload Statistics as shown following.

3. Choose a schema object from the left panel of your project, and then choose the Statistics tab. You can review the statistics for the object.

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Creating Mapping Rules

Later, when you review the suggested keys, if you are not satisﬁed with the results, you can collect additional statistics and repeat this procedure. For more information, see

Managing and Customizing

Keys in the AWS Schema Conversion Tool (p. 97)

Related Topics

•

Choosing Optimization Strategies and Rules for Use with the AWS Schema Conversion Tool (p. 89)

• Choose the Best Sort Key

• Choose the Best Distribution Style

Creating Mapping Rules in the AWS Schema

Conversion Tool

Before you convert your schema with the AWS Schema Conversion Tool (AWS SCT), you can set up rules that change the data type of columns, move objects from one schema to another, and change the names

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Creating Mapping Rules of objects. For example, if you have a set of tables in your source schema named test_TABLE_NAME

, you can set up a rule that changes the preﬁx test_

to the preﬁx demo_

in the target schema.

Note

You can only create mapping rules if your source database engine and target database engine are diﬀerent.

You can create mapping rules that perform the following tasks:

• Change data type

• Move objects

• Rename objects

• Prefix - add prefix, remove prefix, replace prefix

• Suffix - add suffix, remove suffix, replace suffix

You can create mapping rules for the following objects:

• Database

• Schema

• Table

• Column

Creating Mapping Rules

You can create mapping rules and save the rules as part of your project. With your project open, use the following procedure to create mapping rules.

To create mapping rules

1. Choose Mapping Rules from the Settings menu. The Mapping Rules dialog box appears.

2. Choose

Add new rule. A new row is added to the list of rules.

3. Choose the edit icon to conﬁgure your rule.

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Converting Your Schema a. For Name, type a name for your rule.

b. For For, choose the type of object that the rule applies to.

The fields available for the where clause are different depending on the type of the object. For example, if the object type is schema there is only one field available, for the schema name.

d. For Actions, choose the type of mapping rule you want to create.

e. Depending on the rule type, type one or two additional values. For example, to rename an object, type the new name of the object. To replace a prefix, type the old prefix and the new prefix.

4. After you have conﬁgured your mapping rule, choose Save to save your rule. You can also choose

Cancel to cancel your changes.

5. After you are done adding, editing, and deleting rules, choose Save All to save all your changes.

6. Choose Close to close the Mapping Rules dialog box.

Viewing Mapping Rules for Objects

Exporting Mapping Rules

To export mapping rules

1. In the AWS Schema Conversion Tool, in the source schema tree, open the context (right-click) menu and choose Export script for DMS. The save dialog box opens.

2. Browse to the location where you want to save your script, and then choose Save. Your mapping rules are saved as a JSON script that can be consumed by AWS DMS.

Converting Your Schema by Using the AWS Schema

Conversion Tool

After you have connected your project to both your source database and your target database, your AWS

Schema Conversion Tool (AWS SCT) project displays the schema from your source database in the left panel. The schema is presented in a tree-view format, and each node of the tree is lazy loaded. When you choose a node in the tree view, AWS SCT requests the schema information from your source database at that time.

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Converting Your Schema

You can choose schema items from your source database and then convert the schema to equivalent schema for the database engine of your target database. You can choose any schema item from your source database to convert. If the schema item that you choose depends on a parent item, then AWS

SCT also generates the schema for the parent item. For example, if you choose a column from a table to convert, then AWS SCT generates the schema for the column, the table that the column is in, and the database that the table is in.

Converting Schema

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Converting Your Schema

Refresh from Database for your source database. For more information, see

Updating and Refreshing Your Converted Schema in the AWS Schema Conversion

Tool (p. 103) .

Creating and Using the Assessment Report in the

AWS Schema Conversion Tool (p. 98) .

When AWS SCT generates a converted schema, it doesn't immediately apply it to the target database.

Instead, the converted schema is stored locally until you are ready to apply it to the target database. For more information, see

Applying Your Converted Schema (p. 105) .

Editing Converted Schema

You can edit converted schema and save the changes as part of your project.

To edit converted schema

1. In the left panel that displays the schema from your source database, choose the schema item that you want to edit the converted schema for.

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Converting Your Schema

2. In the lower-center panel that displays the converted schema for the selected item, choose the

SQL

tab.

3. In the text displayed for the SQL tab, change the schema as needed. The schema is automatically saved with your project as you update it.

Clearing a Converted Schema

Until you apply the schema to your target database, AWS SCT only stores the converted schema locally in your project. You can clear the planned schema from your project by choosing the tree-view node for your target database, and then choosing Refresh from Database. Because no schema has been written to your target database, refreshing from the database removes the planned schema elements in your

AWS SCT project to match what exists in your target database.

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Managing and Customizing Keys

Managing and Customizing Keys in the AWS Schema

Conversion Tool

After you convert your schema with the AWS Schema Conversion Tool (AWS SCT), you can manage and edit your keys. Key management is the heart of a data warehouse conversion.

To manage keys, select a table in your target database, and then choose the Key Management tab as shown following.

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Creating and Using the Assessment Report

The left pane contains key suggestions, and includes the conﬁdence rating for each suggestion. You can choose one of the suggestions, or you can customize the key by editing it in the right pane.

If the choices for the key don't look like what you expected, you can edit your edit your optimization strategies, and then retry the conversion. For more information, see

Choosing Optimization Strategies and Rules for Use with the AWS Schema Conversion Tool (p. 89)

Related Topics

• Choose the Best Sort Key

• Choose the Best Distribution Style

Creating and Using the Assessment Report in the

AWS Schema Conversion Tool

DB engine of your target database. The report also includes estimates of the amount of eﬀort that it will take to write the equivalent code in your target database that can't be converted automatically.

Creating a Database Migration Assessment Report

Use the following procedure to create a database migration assessment report.

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Creating and Using the Assessment Report

To create a database migration assessment report

1. In the left panel that displays the schema from your source database, choose a schema object to create an assessment report for.

2. Open the context (right-click) menu for the object, and then choose Create Report.

Assessment Report Summary

After you create an assessment report, the assessment report view opens, showing the Summary tab.

The Summary tab displays the summary information from the database migration assessment report. It shows items that were converted automatically, and items that were not converted automatically.

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Creating and Using the Assessment Report

For schema items that can't be converted automatically to the target database engine, the summary includes an estimate of the eﬀort that it will take to create schema items in your target database that are equivalent to those in your source database.

The report categorizes the estimated time to convert these schema items as follows:

• Simple – Actions that can be completed in less than 1 hour.

• Medium – Actions that are more complex and can be completed in 1 to 4 hours.

• Signiﬁcant – Actions that are very complex and take more than 4 hours to complete.

Assessment Report Action Items

The assessment report view also includes an Action Items tab. This tab contains a list of items that can't be converted automatically to the database engine of your target database. If you select an action item from the list, AWS SCT highlights the item from your schema that the action item applies to.

The report also contains recommendations for how to manually convert the schema item. For more

information about deciding how to handle manual conversions, see Handling Manual Conversions in the

AWS Schema Conversion Tool (p. 102)

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Handling Manual Conversions

Handling Manual Conversions in the AWS Schema

Conversion Tool

The assessment report includes a list of items that can't be converted automatically to the database engine of your target database. For each item that can't be converted, there is an action item on the

Action Items tab.

You can respond to the action items in the assessment report in the following ways:

• Modify your source database schema.

• Modify your target database schema.

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Modifying Your Source Schema

The advantage of this process is that your updated schema is always available when you refresh from your source database.

Modifying Your Target Schema

database by applying the schema. For more information, see Saving and Applying Your Converted

Schema in the AWS Schema Conversion Tool (p. 104)

The schema that are written to your target database don't contain the items that can't be converted automatically. After applying the schema to your target database, you can then manually create schema in your target database that are equivalent to those in the source database. The action items in the database migration assessment report contain suggestions for how to create the equivalent schema.

Warning

If you manually create schema in your target database, save a copy of any manual work that you do. If you apply the converted schema from your project to your target database again, it overwrites the manual work you have done.

In some cases, you can't create equivalent schema in your target database. You might need to rearchitect a portion of your application and database to use the functionality that is available from the engine for your target database. In other cases, you can simply ignore the schema that can't be converted automatically.

Related Topics

•

Converting Your Schema by Using the AWS Schema Conversion Tool (p. 93)

•

Creating and Using the Assessment Report in the AWS Schema Conversion Tool (p. 98)

•

Updating and Refreshing Your Converted Schema in the AWS Schema Conversion Tool (p. 103)

Updating and Refreshing Your Converted Schema in the AWS Schema Conversion Tool

You can update both the source schema and the target schema in your AWS Schema Conversion Tool

(AWS SCT) project.

• Target – If you update the schema for your target database, AWS SCT replaces the schema in your project with the latest schema from your target database. If you haven't applied any schema to your

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target database, AWS SCT clears the converted schema from your project. You can then convert the schema from your source database for a clean target database.

You update the schema in your AWS SCT project by choosing Refresh from Database, as shown following.

Saving and Applying Your Converted Schema in the

AWS Schema Conversion Tool

When the AWS Schema Conversion Tool (AWS SCT) generates converted schema (as shown in

Converting

Your Schema by Using the AWS Schema Conversion Tool (p. 93) ), it doesn't immediately apply

the converted schema to the target database. Instead, converted schema are stored locally in your project until you are ready to apply them to the target database. Using this functionality, you can work with schema items that can't be converted automatically to your target database engine. For more

information on items that can't be converted automatically, see Creating and Using the Assessment

Report in the AWS Schema Conversion Tool (p. 98) .

You can optionally have the tool save your converted schema to a ﬁle as a SQL script prior to applying the schema to your target database. You can also have the tool apply the converted schema directly to your target database.

Saving Your Converted Schema to a File

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You can then run your updated scripts on your target database to apply your converted schema to your target database.

To save your converted schema as SQL scripts, open the context (right-click) menu for the schema element, and choose Save as SQL, as shown following.

Applying Your Converted Schema

When you are ready to apply your converted schema to your target database, choose the schema element from the right panel of your project. Open the context (right-click) menu for the schema element, and then choose Apply to database, as shown following.

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The Extension Pack Schema

The extension pack schema is named according to your source database as follows:

• Greenplum:

AWS_GREENPLUM_EXT

• Microsoft SQL Server:

AWS_SQLSERVER_EXT

• Netezza:

AWS_NETEZZA_EXT

• Oracle:

AWS_ORACLE_EXT

• Teradata:

AWS_TERADATA_EXT

• Vertica:

AWS_VERTICA_EXT

For more information, see

The AWS Schema Conversion Tool Extension Pack and Python Libraries for

Data Warehouses (p. 108) .

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Python Libraries

To create custom functions in Amazon Redshift, you use the Python language. Use the AWS SCT extension pack to install python libraries for your Amazon Redshift database. For more information, see

The AWS Schema Conversion Tool Extension Pack and Python Libraries for Data Warehouses (p. 108) .

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The Extension Pack and Python

Libraries for Data Warehouses

The AWS Schema Conversion Tool Extension Pack and Python Libraries for Data Warehouses

When you convert your data warehouse schema, the AWS Schema Conversion Tool (AWS SCT) adds an additional schema to your target DB instance. This schema implements system functions of the source database that are required when writing your converted schema to your target DB instance. The schema is called the extension pack schema.

The extension pack schema is named according to your source database as follows:

• Greenplum:

AWS_GREENPLUM_EXT

• Microsoft SQL Server:

AWS_SQLSERVER_EXT

• Netezza:

AWS_NETEZZA_EXT

• Oracle:

AWS_ORACLE_EXT

• Teradata:

AWS_TERADATA_EXT

• Vertica:

AWS_VERTICA_EXT

In two cases, you might want to install the extension pack manually:

• You accidentally delete the extension pack database schema from your target database.

• You want to upload custom Python libraries to emulate database functionality.

Using AWS Services to Upload Custom Python

Libraries

In some cases, source database features can't be converted to equivalent Amazon Redshift features. AWS

SCT contains a custom Python library that emulates some source database functionality on Amazon

Redshift.

The AWS SCT extension pack wizard helps you install the custom Python library.

Before You Begin

Almost all work you do with AWS SCT starts with the following three steps:

1. Create an AWS SCT project.

2. Connect to your source database.

3. Connect to your target database.

If you have not created an AWS SCT project yet, see

see Converting Data Warehouse Schema to Amazon Redshift by Using the AWS Schema Conversion

Before you install the extension pack, you need to convert your database schema. For more information,

Tool (p. 87) .

Applying the Extension Pack

Use the following procedure to apply the extension pack.

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To apply the extension pack

1. In the AWS Schema Conversion Tool, in the target database tree, open the context (right-click) menu, and choose

Apply Extension Pack.

The extension pack wizard appears.

2. Read the Welcome page, and then choose Next.

3. On the AWS Services Settings page, do the following:

• If you are reinstalling the extension pack database schema only, choose Skip this step for now, and then choose

Next.

• If you are uploading the Python library, provide the credentials to connect to your AWS account.

You can use your AWS Command Line Interface (AWS CLI) credentials if you have the AWS

CLI installed. You can also use credentials that you previously stored in a proﬁle in the global application settings and associated with the project. If necessary, choose

Navigate to Project

Settings to associate a different profile with the project. If necessary, choose Global Settings to create a new profile. For more information, see

Storing AWS Proﬁles in the AWS Schema

Conversion Tool (p. 131)

4. On the Python Library Upload page, do the following:

• If you are reinstalling the extension pack database schema only, choose Skip this step for now, and then choose Next.

• If you are uploading the Python library, provide the Amazon S3 path, and then choose

Upload

Library to S3. When you are done, choose Next.

5. On the Functions Emulation page, choose Create Extension Pack. Messages appear with the status of the extension pack operations. When you are done, choose Finish.

Amazon S3 Settings

After your agents extract your data, they upload it to your Amazon S3 bucket. Before you continue, you must provide the credentials to connect to your AWS account and your Amazon S3 bucket. You store your credentials and bucket information in a profile in the global application settings, and then associate the profile with your AWS SCT project. If necessary, choose Global Settings to create a new profile. For more information, see

Storing AWS Proﬁles in the AWS Schema Conversion Tool (p. 131)

Security Settings

The AWS Schema Conversion Tool and the extraction agents can communicate through Secure Sockets

Layer (SSL). To enable SSL, set up a trust store and key store.

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To set up secure communication with your extraction agent

1. Start the AWS Schema Conversion Tool.

2. Open the Settings menu, and then choose Global Settings. The Global settings dialog box appears.

Choose the Security tab as shown following.

3. Choose Generate Trust and Key Store, or choose Select existing Trust and Key Store.

If you choose Generate Trust and Key Store, you then specify the name and password for the trust and key stores, and the path to the location for the generated file. A .zip file is generated that contains the trust and key store files. You will use these files in later steps.

If you choose Select existing Trust and Key Store, you then specify the password and ﬁle name for the trust and key stores. You use these ﬁles in later steps.

4. After you have speciﬁed the trust store and key store, choose OK to close the Global Settings dialog box.

Installing Extraction Agents

We recommend that you install multiple extraction agents on individual computers, separate from the computer that is running the AWS Schema Conversion Tool.

Extraction agents are currently supported on the following operating systems:

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• macOS

• Microsoft Windows

• Red Hat Enterprise Linux (RHEL) 6.0

• Ubuntu Linux (version 14.04 and later)

Use the following procedure to install extraction agents. Repeat this procedure for each computer that you want to install an extraction agent on.

To install an extraction agent

1. If you have not already downloaded the AWS SCT installer ﬁle, follow the instructions at Installing and Updating the AWS Schema Conversion Tool (p. 6) to download it. The .zip ﬁle that contains the

AWS SCT installer ﬁle also contains the extraction agent installer ﬁle.

2. Locate the installer ﬁle for your extraction agent in a subfolder named agents. The correct ﬁle for the operating system of the computer that you want to install the extraction agent on is shown following.

Operating System

macOS

Microsoft Windows

File Name

aws-schema-conversion-tool-extractor-1.0.

build-number

.dmg

aws-schema-conversion-tool-extractor-1.0.

build-number

.msi

RHEL aws-schema-conversion-tool-extractor-1.0.

buildnumber

.x86_64.rpm

Ubuntu Linux aws-schema-conversion-tool-extractor-1.0.

build-number

.deb

3. To install the extraction agent on a separate computer, copy the installer ﬁle to the new computer.

4. Run the installer ﬁle. Use the instructions for your operating system, shown following.

Operating System

macOS

Microsoft Windows

RHEL

Install Instructions

In Finder, open aws-schema-conversion-tool-extractor-1.0.

buildnumber

.dmg

Drag aws-schema-conversion-tool-extractor-1.0.

build-number

.dmg

to the Applications folder.

Double-click the ﬁle to run the installer.

Run the following command in the folder that you downloaded or moved the ﬁle to:

Ubuntu Linux sudo rpm -ivh aws-schema-conversion-tool-extractor-1.0.

buildnumber

.x86_64.rpm

Run the following command in the folder that you downloaded or moved the ﬁle to: sudo dpkg -i aws-schema-conversion-tool-extractor-1.0.

buildnumber

.deb

5. Install the Java Database Connectivity (JDBC) drivers for your source database engine. For

instructions and download links, see Installing the Required Database Drivers (p. 7)

. Follow the instructions for your source database engine only, not your target database engine.

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6. Copy the SSL trust and key stores (.zip or individual ﬁles) that you generated in an earlier procedure.

If you copy the .zip file to a new computer, extract the individual files from the .zip file on the new computer.

You can put the files anywhere you want, but note the locations because in a future procedure you tell the agent where to find the files.

Continue installing your extraction agent by completing the procedure in the following section.

Conﬁguring Extraction Agents

Use the following procedure to conﬁgure extraction agents. Repeat this procedure on each computer that has an extraction agent installed.

To conﬁgure your extraction agent

• From the location where you installed the agent, run the setup program. For RHEL and Ubuntu, the ﬁle is named sct-extractor-setup.sh

. For macOS and Microsoft Windows, the ﬁle is named

AWS

SCT Data Extractor Agent

, and you can double-click the ﬁle to run it.

The setup program prompts you for information. For each prompt, a default value appears. You can accept the default value, or type a new value. You specify the following information:

• The data warehouse engine.

• The port number the agent listens on.

• The location where you installed the JDBC drivers.

• The working folder. Your extracted data goes into a subfolder of this location. The working folder can be on a diﬀerent computer from the agent, and a single working folder can be shared by multiple agents on diﬀerent computers.

• The location of the key store ﬁle.

• The password for the key store.

• The location of the trust store ﬁle.

• The password for the trust store.

The setup program updates the settings ﬁle for the extraction agent. The settings ﬁle is named

Settings.properties

, and is located where you installed the extraction agent. The following is a sample settings ﬁle.

port=8888 vendor=ORACLE driver.jars=

<driver path>

/Install/Drivers/

ojdbc7.jar

location=

<output path>

/dmt/8888/out extractor.log.folder=

<log path>

/dmt/8888/log extractor.storage.folder=

<storage path>

/dmt/8888/storage extractor.start.fetch.size=20000 extractor.out.file.size=10485760 ssl.option=OFF

#ssl.option=ON

#ssl.keystore.path=

<key store path>

/dmt/8888/vault/keystore

#ssl.truststore.path=

<trust store path>

/dmt/8888/vault/truststore

Starting Extraction Agents

Use the following procedure to start extraction agents. Repeat this procedure on each computer that has an extraction agent installed.

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Extraction agents act as listeners. When you start an agent with this procedure, the agent starts listening for instructions. You send the agents instructions to extract data from your data warehouse in a later section.

To start your extraction agent

• On the computer that has the extraction agent installed, run the command listed following for your operating system.

Operating System

macOS

Microsoft Windows

RHEL

Ubuntu Linux

Start Command

Run the

StartAgent.command

ﬁle.

Double-click the

StartAgent.bat

batch ﬁle.

Run the following command in the path to the folder that you installed the agent: sudo initctl

start

sct-extractor

Run the following command in the path to the folder that you installed the agent. Use the command appropriate for your version of Ubuntu.

Ubuntu 14.04: sudo initctl

start

sct-extractor

Ubuntu 15.04 and later: sudo systemctl

start

sct-extractor

To check the status of the agent, run the same command but replace start

with status

To stop an agent, run the same command but replace start

with stop

Registering Extraction Agents

You manage your extraction agents by using AWS SCT. The extraction agents act as listeners. When they receive instructions from AWS SCT, they extract data from your data warehouse.

Use the following procedure to register extraction agents with your AWS SCT project.

To register an extraction agent

1. Start the AWS Schema Conversion Tool, and open a project.

a. Open an existing or create a new project. For more information, see Creating an AWS Schema

Conversion Tool Project (p. 12)

b. Connect to your source database. For more information, see Connecting to Your Source

Database (p. 13) .

Connect to your target database. For more information, see Connecting to Your Target

Database (p. 13) .

d. Convert your schema. For more information, see

Converting Data Warehouse Schema to

Amazon Redshift by Using the AWS Schema Conversion Tool (p. 87)

e. Apply your schema. For more information, see

Saving and Applying Your Converted Schema in the AWS Schema Conversion Tool (p. 104) .

2. Open the View menu, and then choose Data Migration View. The Agents tab appears. If you have previously registered agents, they appear in a grid at the top of the tab as shown following.

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3. Choose Register. The New Agent Registration dialog box appears.

Note

After you register an agent with an AWS SCT project, you can't register the same agent with a diﬀerent project. If you're no longer using an agent in an AWS SCT project, you can unregister it, and then register it with a diﬀerent project.

4. Enter your information in the New Agent Registration dialog box: a. For Description, type a description of the agent.

b. For Host Name, type the host name or IP address of the computer of the agent.

For Port, type the port number that the agent is listening on.

d. Choose

Register to register the agent with your AWS SCT project.

5. Repeat the previous steps to register multiple agents with your AWS SCT project.

Managing Extraction Tasks

Use the following procedures to create, run, and monitor data extraction tasks.

To assign tasks to agents and migrate data

1. In the AWS Schema Conversion Tool, after you have converted your schema, choose one or more tables from the left panel of your project. You can choose all tables, but we recommend against that for performance reasons. We recommend that you create multiple tasks for multiple tables based on the size of the tables in your data warehouse.

2. Open the context (right-click) menu for the tables, and then choose Create Task. The Create Local

Task dialog box opens.

a. For Task Name, type a name for the task.

b. For Migration Mode, choose one of the following:

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• Extract Only – extract your data, and save the date to your local working folders.

• Extract and Upload – extract your data, and upload your data to Amazon S3.

• Extract, Upload and Copy – extract your data, upload your data to Amazon S3, and copy it into your Amazon Redshift data warehouse.

Choose Test Task to verify that you can connect to your working folder, Amazon S3 bucket, and

Amazon Redshift data warehouse. The veriﬁcation depends on the migration mode you chose.

d. Choose Create to create the task.

3. Repeat the previous steps to create tasks for all the data that you want to migrate.

To run and monitor tasks

1. Open the View menu, and then choose Data Migration View. The Agents tab appears.

2. Choose the Tasks tab. Your tasks appear in the grid at the top as shown following.

3. Select a task in the top grid and expand it. Depending on the migration mode you chose, you see the task divided into Extract, Upload, and Copy.

4. Select a task in the top grid. You can see the status of the task in the top grid, and the status of its subtasks in the bottom grid.

5. To run a task, choose Start. You can monitor the status of your tasks while they work. The subtasks run in parallel. The extract, upload, and copy also run in parallel.

You can close AWS SCT and your agents and tasks continue to run. You can then reopen AWS SCT and check the status of your tasks.

Extraction Task Output

After your migration tasks complete, your data is ready. Use the following information to determine how to proceed based on the migration mode you chose and the location of your data.

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Migration

Mode

Extract,

Upload and

Copy

Extract and

Upload

Data Location

The data is already in your Amazon Redshift data warehouse. You can verify that the data is there, and start using it. For more information, see Connecting to Clusters

From Client Tools and Code .

The extraction agents saved your data as ﬁles in your Amazon S3 bucket. You can use the Amazon Redshift COPY command to load your data to Amazon Redshift.

For more information, see Loading Data from Amazon S3 in the Amazon Redshift documentation.

There are multiple folders in your Amazon S3 bucket, corresponding to the extraction tasks that you set up. When you load your data to Amazon Redshift, specify the name of the manifest ﬁle created by each task. The manifest ﬁle appears in the task folder in your S3 bucket as shown following.

Extract Only

The extraction agents saved your data as ﬁles in your working folder. Manually copy your data to your Amazon S3 bucket, and then proceed with the instructions for

Extract and Upload.

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Best Practices and Troubleshooting

The following are some best practices and troubleshooting suggestions for using extraction agents.

Issue

Performance is slow

Contention delays

Troubleshooting Suggestions

To improve performance, we recommend the following:

• Install multiple agents.

• Install agents on computers close to your data warehouse.

• Don't run all tables on a single agent task.

Avoid having too many agents accessing your data warehouse at the same time.

An agent goes down temporarily If an agent is down, the status of each of its tasks appears as failed in AWS SCT. If you wait, in some cases the agent can recover. In this case, the status of its tasks updates in AWS SCT.

An agent goes down permanently

If the computer running an agent goes down permanently, and that agent is running a task, you can substitute a new agent to continue the task. You can substitute a new agent only if the working folder of the original agent was not on the same computer as the original agent. To substitute a new agent, do the following:

• Install an agent on a new computer.

• Conﬁgure the new agent with the same settings, including port number and working folder, as the original agent.

• Start the agent. After the agent starts, the task discovers the new available agent and continues running on the new agent.

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Optimizing Amazon Redshift by Using the AWS

Schema Conversion Tool

You can use the AWS Schema Conversion Tool (AWS SCT) to optimize your Amazon Redshift database.

Using your Amazon Redshift database as a source, and a test Amazon Redshift database as the target,

AWS SCT recommends sort keys and distribution keys to optimize your database.

Before You Begin

Almost all work you do with AWS SCT starts with the same three steps. Complete the following steps before you optimize your Amazon Redshift database:

1. Create an AWS SCT project. For more information, see Creating an AWS Schema Conversion Tool

Project (p. 12)

2. Connect to your source database. For more information, see

Connecting to an Amazon Redshift

Source Database (p. 42)

3. Connect to your target database. For more information, see

Connecting to Your Target

Database (p. 13)

Important

Don't use the same cluster for both the source and target of your optimization.

Before you optimize your Amazon Redshift database, you should also choose your optimization strategies. For more information, see

Choosing Optimization Strategies and Rules for Use with the AWS

Schema Conversion Tool (p. 89)

Optimizing Your Amazon Redshift Database

Use the following procedure to optimize your Amazon Redshift database.

To optimize your Amazon Redshift database

1. Take a manual snapshot of your Amazon Redshift cluster as a backup. You can delete the snapshot after you are done optimizing your Amazon Redshift cluster and testing any changes that you make.

For more information, see Amazon Redshift Snapshots .

2. Choose a schema object to convert from the left panel of your project. Open the context (right-click) menu for the object, and then choose Collect Statistics.

AWS SCT uses the statistics to make suggestions for sort keys and distribution keys.

3. Choose a schema object to optimize from the left panel of your project. Open the context (rightclick) menu for the object, and then choose Run Optimization.

AWS SCT makes suggestions for sort keys and distribution keys.

4. To review the suggestions, expand the tables node under your schema in the left panel of your project, and then choose a table. Choose the Key Management tab as shown following.

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The left pane contains key suggestions, and includes the conﬁdence rating for each suggestion. You can choose one of the suggestions, or you can customize the key by editing it in the right pane.

5. You can create a report that contains the optimization suggestions. To create the report, do the following: a. Choose a schema object that you optimized from the left panel of your project. Open the context (right-click) menu for the object, and then choose Create Report.

The report opens in the main window, and the Summary tab appears. The number of objects with optimization suggestions appears in the report.

b. Choose the Action Items tab to see the key suggestions in a report format.

You can save a local copy of the optimization report as either a PDF file or a comma-separated values (CSV) file. The CSV file contains only action item information. The PDF file contains both the summary and action item information.

6. To apply suggested optimizations to your database, choose an object in the right panel of your project. Open the context (right-click) menu for the object, and then choose Apply to database.

Working with the AWS Database

Migration Service Using the AWS

Schema Conversion Tool

AWS Database Migration Service (AWS DMS) is a web service that you can use to migrate data to and from most widely used commercial and open-source databases. You can use the AWS Schema Conversion

Tool (AWS SCT) to create AWS DMS endpoints and tasks. You can run and monitor the tasks from AWS

SCT. For more information about AWS DMS, see What Is AWS Database Migration Service?

in the AWS

DMS User Guide..

Before You Begin

Almost all work you do with AWS SCT starts with the following three steps:

1. Create an AWS SCT project.

2. Connect to your source database.

3. Connect to your target database.

If you have not created an AWS SCT project yet, see

you can integrate with AWS DMS. To convert your database schema, see Converting Database Schema to

Because AWS DMS interacts with the target schema, you need to convert your database schema before

Amazon RDS by Using the AWS Schema Conversion Tool (p. 68) .

Credentials for Working with AWS DMS

To create AWS DMS tasks, AWS SCT must connect to AWS DMS with your credentials. You can use credentials that you previously stored in a proﬁle in the global application settings and associated

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Creating a Task with the project. For more information, see

Storing AWS Proﬁles in the AWS Schema Conversion

Tool (p. 131) .

Creating an AWS DMS Task

After you use AWS SCT to convert your database schema, you can create AWS DMS tasks. Use the following procedure to create an AWS DMS task.

To create an AWS DMS task

1. In the AWS Schema Conversion Tool, choose a database or a schema object from the left panel of your project. Open the context (right-click) menu for the object, and then choose Create DMS Task.

The Create DMS task dialog box appears.

2. For Task name, type a name for your task.

3. For Replication instance, choose the replication instance that you want to use. For more information, see Replication Instances for AWS Database Migration Service .

4. For Source endpoint, choose an existing endpoint. You can also choose Create new to create a new endpoint. When you choose Create new, a new endpoint is created for you by using the current connection information. You can verify the connection information and give the endpoint a name before it is created.

5. For Target endpoint, choose an existing endpoint. You can also choose Create new to create a new endpoint. When you choose Create new, a new endpoint is created for you by using the current connection information. You can verify the connection information and give the endpoint a name before it is created.

6. For Include LOB columns in replication, choose Don’t include LOB columns, Full LOB mode, or

Limited LOB mode. For more information, see LOB Support for Source Databases .

7. For LOB chunk size (kb), type the LOB chunk size in kilobytes.

8. Select Enable logging to turn on logging for the task.

9. Choose Preview JSON to see the JSON that is created for the task.

10. Choose Save JSON to save a copy of the JSON that is created for the task.

11. After you have conﬁgured your task, choose Create to save your task. You can also choose Close to cancel your changes.

Running and Monitoring an AWS DMS Task

After you create AWS DMS tasks, you can run and monitor them in the data migration view. Use the following procedure to run and monitor your AWS DMS tasks.

To run and monitor your AWS DMS tasks

1. Open the View menu, and then choose Data Migration View.

2. In the list of tasks, choose the task you want to run. Choose Start to run the task. The Status column shows the status of the task.

3. When you have a running task, you can choose the following actions:

• Choose Stop to stop a task.

• Choose Resume to resume a task.

4. Choose Delete to delete a task.

5. Choose Refresh to refresh the task list. The Status column shows the current status of all tasks.

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6. Choose Show Log to see the task log. If you selected Enable logging when you created the task, the task log shows log information.

Converting Application SQL by Using the AWS Schema Conversion Tool

When you convert your database schema from one engine to another, you also need to update the SQL code in your applications to interact with the new database engine instead of the old one. You can use the AWS Schema Conversion Tool (AWS SCT) to convert the SQL code in your C++, C#, Java, or other application code. You can view, analyze, edit, and save the converted SQL code.

Before You Begin

Almost all work you do with AWS SCT starts with the following three steps:

1. Create an AWS SCT project.

2. Connect to your source database.

3. Connect to your target database.

If you have not created an AWS SCT project yet, see

Converting Database Schema to Amazon RDS by Using the AWS Schema Conversion Tool (p. 68)

Because the SQL code in your application interacts with your database schema, you need to convert your database schema before you can convert your application SQL. To convert your database schema, use the procedures in one of the following topics:

•

•

Converting Data Warehouse Schema to Amazon Redshift by Using the AWS Schema Conversion

Tool (p. 87)

Overview of Converting Application SQL

To convert the SQL code in your application, you take the following high-level steps:

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Creating Application Conversion Projects

• Create an application conversion project – The application conversion project is a child of the database schema conversion project. Each database schema conversion project can have one or more child application conversion projects.

For more information, see

Creating Application Conversion Projects in the AWS Schema Conversion

Tool (p. 125) .

•

Analyze and convert your SQL code – AWS SCT analyzes your application, extracts the SQL code, and creates a local version of the converted SQL for you to review and edit. The tool doesn't change the code in your application until you are ready.

For more information, see

Analyzing and Converting Your SQL Code by Using the AWS Schema

Conversion Tool (p. 128)

• Create an application assessment report – The application assessment report provides important information about the conversion of the application SQL code from your source database schema to your target database schema.

For more information, see

Creating and Using the Assessment Report (p. 129)

• Edit, apply changes to, and save your converted SQL code – The assessment report includes a list of SQL code items that can't be converted automatically. For these items, you can edit the SQL code manually to perform the conversion.

For more information, see

Editing and Saving Your Converted SQL Code with the AWS Schema

Conversion Tool (p. 130)

Creating Application Conversion Projects in the

AWS Schema Conversion Tool

In the AWS Schema Conversion Tool (AWS SCT), the application conversion project is a child of the database schema conversion project. Each database schema conversion project can have one or more child application conversion projects. Use the following procedure to create an application conversion project.

To create an application conversion project

1. In the AWS Schema Conversion Tool, choose New Application from the Applications menu.

The New application conversion project dialog box appears.

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Creating Application Conversion Projects

2. Add the following project information.

For This Parameter

Application Project Name

Location

Project language

SQL parameter style for target database

Do This

Type a name for your application conversion project. Each database schema conversion project can have one or more child application conversion projects, so choose a name that makes sense if you add more projects later.

Type the location of the source code for your application.

Choose one of the following:

•

JAVA

•

C++

•

Any

Choose one of the following:

•

Same as in source

•

Positional (?)

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For This Parameter

Select source database schema

Do This

•

Indexed (:1)

•

Indexed ($1)

•

Named (@name)

•

Named (:name)

In the source tree, choose the schema used by your application code.

3. Choose OK to create your application conversion project.

The project window opens.

4. The ﬁrst time you create an application conversion project, the project window opens automatically.

To open an existing application conversion project, select the project node in the source tree, open the context (right-click) menu, and then choose

Manage application.

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Analyzing and Converting Your SQL Code

5. You can add additional application conversion projects by choosing New Application from the

Applications menu, or by selecting the Applications node in the source tree, opening the context

(right-click) menu, and then choosing Add application.

Analyzing and Converting Your SQL Code by Using the AWS Schema Conversion Tool

Use the following procedure to analyze and convert your SQL code by using the AWS Schema Conversion

Tool (AWS SCT).

To analyze and convert your SQL code

1. In the application conversion project, choose Analyze.

AWS SCT analyzes your application code and extracts the SQL code. A list of all extracted SQL code appears in the Parsed SQL Scripts pane at the bottom of the window. The selected item in the list also appears in the Extracted SQL script pane.

2. You can analyze each SQL code item in the list, and when you are ready, choose Convert to convert the SQL to SQL for your target database.

Note

You can edit the converted SQL code in a later procedure.

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Creating and Using the Assessment Report

The application assessment report provides important information about converting the application

SQL code from your source database schema to your target database schema. The report details all of the SQL extracted from the application, all of the SQL converted, and action items for SQL that can't be converted. The report also includes estimates of the amount of eﬀort that it will take to manually convert the SQL code that can't be converted automatically.

Creating an Application Assessment Report

Use the following procedure to create an application assessment report.

To create an application assessment report

1. In the application conversion project window, choose Create Report from the Actions menu.

The report is created and opens in the application conversion project window.

2. Review the Summary tab.

The Summary tab shown following, displays the summary information from the application assessment report. It shows the SQL code items that were converted automatically, and items that were not converted automatically.

3. Choose the SQL Conversion Actions tab and review the information.

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Editing and Saving Your Converted SQL Code

The SQL Conversion Actions tab contains a list of SQL code items that can't be converted automatically. There are also recommendations for how to manually convert the SQL code. You edit your converted SQL code in a later step. For more information, see

Editing and Saving Your

Converted SQL Code with the AWS Schema Conversion Tool (p. 130)

4. You can save a local copy of the application assessment report as either a PDF file or a commaseparated values (CSV) file. The PDF file contains both the summary and action item information.

The CSV ﬁle contains only action item information.

Editing and Saving Your Converted SQL Code with the AWS Schema Conversion Tool

The assessment report includes a list of SQL code items that can't be converted automatically. For each item that can't be converted, there is an action item on the

SQL Conversion Actions tab. For these items, you can edit the SQL code manually to perform the conversion.

Use the following procedure to edit your converted SQL code, apply the changes, and then save them.

To edit, apply changes to, and save your converted SQL code

1. Edit your converted SQL code directly in the Target SQL script pane. If there is no converted code shown, you can click in the pane and start typing.

2. After you are ﬁnished editing your converted SQL code, choose Apply. At this point, the changes are saved in memory, but not yet written to your ﬁle.

3. Choose Save to save your changes to your ﬁle.

Important

When you choose Save you overwrite your original ﬁle. Make a copy of your original ﬁle before saving so you have a record of your original application code.

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Storing AWS Credentials

Storing AWS Proﬁles in the AWS

Schema Conversion Tool

You can store your AWS credentials in the AWS Schema Conversion Tool (AWS SCT). AWS SCT uses your credentials when you use features that integrate with AWS services. For example, AWS SCT integrates with Amazon S3, AWS Lambda, and AWS Database Migration Service.

AWS SCT asks you for your AWS credentials when you access a feature that requires them. You can store your credentials in the global application settings. When AWS SCT asks for your credentials, you can select the stored credentials.

You can store different sets of AWS credentials in the global application settings. For example, you can store one set of credentials that you use in test scenarios, and a different set of credentials that you use in production scenarios. You can also store different credentials for different AWS regions.

Storing AWS Credentials

Use the following procedure to store AWS credentials globally.

To store AWS credentials

1. Start the AWS Schema Conversion Tool.

2. Open the Settings Menu, and then choose Global Settings. The Global settings dialog box appears.

Choose the AWS Service Proﬁles tab, as shown following.

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Setting the Default Proﬁle for a Project

3. Choose Add new AWS Service Proﬁle. A new row is added to the list of proﬁles.

4. Choose the edit icon to conﬁgure your proﬁle.

a. For Proﬁle name, type a name for your proﬁle.

b. For AWS Access Key, type your AWS access key.

For AWS Secret Key, type your AWS secret key.

d. For

Region, choose the region for your proﬁle.

e. For S3 Bucket, choose the S3 bucket for your proﬁle. You only need to specify a bucket if you are using a feature that connects to S3.

5. Choose Test Connection to verify that your credentials are correct and active.

6. After you have configured your profile, choose Save to save your profile. You can also choose Cancel to cancel your changes.

7. Choose

OK to close the Global Settings dialog box.

Setting the Default Proﬁle for a Project

You can set the default profile for an AWS SCT project. Doing this associates the AWS credentials stored in the profile with the project. With your project open, use the following procedure to set the default profile.

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Related Topics

To set the default proﬁle for a project

1. Start the AWS Schema Conversion Tool.

2. Open the Settings Menu, and then choose Project Settings. The Current project settings dialog box appears.

3. Choose the Project Environment tab.

4. For AWS Service Proﬁle, choose the proﬁle that you want to associate with the project.

5. Choose OK to close the Current project settings dialog box. You can also choose Cancel to cancel your changes.

Best Practices for the AWS Schema

Conversion Tool

Following, you can ﬁnd information on best practices and options for using the AWS Schema Conversion

Tool (AWS SCT).

General Memory Management and Performance

Options

You can conﬁgure the AWS Schema Conversion Tool with diﬀerent memory performance settings.

Increasing memory speeds up the performance of your conversion but uses more memory resources on your desktop.

To set your memory management option, choose Global Settings from the Settings menu, and choose the Performance and Memory tab. Choose one of the following options:

• Fast conversion, but large memory consumption – This option optimizes for speed of the conversion, but might require more memory for the object reference cache.

• Low memory consumption, but slower conversion – This option minimizes the amount of memory used, but results in a slower conversion. Use this option if your desktop has a limited amount of memory.

• Balance speed with memory consumption – This option optimizes provides a balance between memory use and conversion speed.

Conﬁguring Additional Memory

For converting large database schemas, for example a database with 3,500 stored procedures, you can conﬁgure the amount of memory available to the AWS Schema Conversion Tool.

To modify the amount of memory AWS SCT consumes

1. Locate the folder where the conﬁguration ﬁle is (C:\Program Files\AWS Schema Conversion Tool

\App).

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Related Topics

2. Open the conﬁguration ﬁle

AWS Schema Conversion Tool.cfg

with Notepad or your favorite text editor.

3. Edit the

JVMUserOptions

section to set the minimum and maximum memory available. The following example sets the minimum to 4 GB and the maximum to 40 GB.

[JVMUserOptions]

-Xmx48960m

-Xms4096m

Troubleshooting Issues with the AWS

Schema Conversion Tool

Following, you can ﬁnd information about troubleshooting issues with the AWS Schema Conversion Tool

(AWS SCT).

Cannot load objects from an Oracle source database

When you attempt to load schema from an Oracle database, you might encounter one of the following errors.

Cannot load objects tree.

ORA-00942: table or view does not exist

These errors occur because the user whose ID you used to connect to the Oracle database doesn't have suﬃcient permissions to read the schema, as required by AWS SCT.

You can resolve the issue by granting the user select_catalog_role

permission and also permission to any dictionary in the database. These permissions provide the read-only access to the views and system tables that is required by AWS SCT. The following example creates a user ID named min_privs and grants the user with this ID the minimum permissions required to convert schema from an Oracle source database.

create user min_privs identified by min_privs; grant connect to min_privs; grant select_catalog_role to min_privs; grant select any dictionary to min_privs;

Keyboard Shortcuts for the AWS

Schema Conversion Tool

The following are the keyboard shortcuts that you can use with the AWS Schema Conversion Tool (AWS

SCT).

Keyboard Shortcut

Ctrl+N

Ctrl+O

Ctrl+S

Ctrl+W

Ctrl+L

Ctrl+R

Description

Create a new project.

Open an existing project.

Save an open project.

Create a new project by using the wizard.

Connect to the source database.

Connect to the target database.

AWS Schema Conversion Tool

Reference

Following, you can ﬁnd reference material for the AWS Schema Conversion Tool (AWS SCT):

•

MySQL to PostgreSQL Supported Schema Conversion (p. 212)

•

Oracle to MySQL Supported Schema Conversion (p. 241)

•

Oracle to PostgreSQL Supported Schema Conversion (p. 270)

•

PostgreSQL to MySQL Supported Schema Conversion (p. 212)

•

Microsoft SQL Server to MySQL Supported Schema Conversion (p. 139)

•

Microsoft SQL Server to PostgreSQL Supported Schema Conversion (p. 159)

Microsoft SQL Server to MySQL Supported

Schema Conversion

The following sections list the schema elements from Microsoft SQL Server and whether they are supported for automatic conversion to MySQL using the AWS Schema Conversion Tool.

Topics

•

Statements (p. 140)

•

Procedures (p. 143)

•

Flow Control (p. 143)

•

Functions (p. 144)

•

Operators (p. 151)

•

Transactions (p. 154)

•

Data Types (p. 154)

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Statements

•

Data Deﬁnition Language (DDL) (p. 157)

•

Cursors (p. 158)

•

Statements

Topics

•

•

•

•

SELECT

Clause

WITH

UNION

EXCEPT | INTERSECT

ALL | DISTINCT

TOP

<select_list>

INTO

FROM

WHERE

GROUP BY

HAVING

ORDER BY

FOR

OPTION

Automatically

Converted

Details

No Try converting the WITH(query) expression to a subquery and use it in a SELECT query.

Yes

Partial MySQL doesn't support TOP with the PERCENT or WITH

TIES options. Try using the LIMIT option or perform a manual conversion.

Yes

Partial MySQL doesn't support the CONTAINS and FREETEXT predicates in the FROM clause search condition.

Yes

Partial MySQL doesn't support ORDER BY with the ROLLUP,

CUBE, and GROUPING SETS options. Try creating a stored procedure to replace the query.

Yes

Partial MySQL doesn't support ORDER BY with the OFFSET or

FETCH options. Try creating a stored procedure to replace the query.

MySQL doesn't support ORDER BY with the COLLATE option. You must use the collation settings that were assigned when the database was created.

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Statements

INSERT

Clause

WITH

INSERT

TOP

INTO table_name

WITH

(<Table_Hint_Limited>)

OUTPUT

Yes

Automatically

Converted

Details

No Try to convert the WITH query to a subquery, and then use the subquery in the INSERT query.

Yes

No Get a count of all rows, and then use the following expression, where count_of_all_rows is your row count: percent_expression * count_of_all_rows / 100

Yes

No Use MySQL methods of performance tuning.

No Create a trigger for INSERT statements for the table, and then save the inserted rows in a temporary table.

After the INSERT operation, you can make use of the rows saved in the temporary table. This logic can be placed in a stored procedure.

Create a temporary table, ﬁll it with the data to insert, and use the temporary table in the query.

VALUES derived_table execute_statement

<dml_table_source>

DEFAULT VALUES

UPDATE

Clause

WITH

TOP

WITH

(<Table_Hint_Limited>)

SET

OUTPUT

Automatically

Converted

Details

Partial

Try to convert the WITH query to a subquery, and then use the subquery in the UPDATE query.

MySQL doesn't support UPDATE with the PERCENT option. Get a count of all rows, and then use the following expression, where count_of_all_rows is your row count: percent_expression * count_of_all_rows / 100

Use MySQL methods of performance tuning.

No Create a trigger for UPDATE statements for the table, and then save the changed rows in a temporary table. After the UPDATE operation, you can make use of the rows

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Statements

Clause

FROM

WHERE

CURRENT OF

GLOBAL

OPTION

Automatically

Converted

Details

saved in the temporary table. This logic can be placed in a stored procedure.

Partial MySQL doesn't support a FROM clause. AWS Schema

Conversion Tool moves <table-source> to the UPDATE clause.

Yes

No Replace the CURRENT OF clause with an expression that consists of conditions that use unique key ﬁelds of the table.

Note

MySQL doesn't support FILESTREAM DATA. Perform a manual conversion to update the data in the ﬁle system ﬁle.

DELETE

Clause

WITH

TOP

FROM table_or_view_name rowset_function_limited

WITH

OUTPUT

WHERE

Yes

Automatically

Converted

Details

Partial

Try to convert the WITH query to a subquery, and then use the subquery in the DELETE query.

MySQL doesn't support the PERCENT option. A manual conversion is required. Get a count of all rows, and then use the following expression, where count_of_all_rows is your row count: percent_expression * count_of_all_rows /

100

Yes

MySQL doesn't support hints in DELETE statements, so the AWS Schema Conversion Tool skips options in the format WITH(Table_Hint_Limited). Use MySQL methods of performance tuning.

Create a trigger for DELETE statements for the table, and then save the deleted rows in a temporary table. After the DELETE operation, you can make use of the rows saved in the temporary table. This logic can be placed in a stored procedure.

Yes

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Procedures

Clause

CURRENT OF

GLOBAL

OPTION

Automatically

Converted

Details

No Replace the CURRENT OF clause with an expression that consists of conditions that use unique key ﬁelds of the table.

Procedures

Topics

•

CREATE PROCEDURE (p. 143)

CREATE PROCEDURE

Clause

@parameter

Automatically

Converted

Details

Yes MySQL doesn't support procedure arguments of the

CURSOR data type. Change the business logic to eliminate the need to send cursors through arguments to a stored procedure.

Partial VARYING

OUT

OUTPUT

READONLY

WITH

FOR REPLICATION

AS BEGIN … END

ENCRYPTION

RECOMPILE

EXECUTE AS

Yes

Partial

Flow Control

Clause

TRY…CATCH

THROW

Automatically

Converted

Details

No Try using the DECLARE HANDLER for the CATCH emulation block and the SIGNAL SQLSTATE operator to emulate the THROW operator.

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Functions

Clause

WAITFOR

DECLARE

GOTO

BREAK

CONTINUE

IF…ELSE

RETURN

WHILE

CASE

COALESCE

NULLIF

Yes

Automatically

Converted

Details

No Perform a manual conversion.

Perform a manual conversion.

Revise your code to eliminate GOTO operators, using

BEGIN...END blocks in combination with LEAVE, REPEAT,

UNTIL, and WHILE operators.

Yes

MySQL does not support returning a value from a procedure using the RETURN statement. To return a value, use the OUT parameter or a result set.

Functions

Topics

•

Aggregate Functions (p. 144)

•

Date and Time Functions (p. 145)

•

Mathematical Functions (p. 146)

•

String Functions (p. 147)

•

Conﬁguration Functions (p. 148)

•

Conversion Functions (p. 148)

•

Security Functions (p. 148)

•

System Functions (p. 149)

•

Logical Functions (p. 150)

•

CREATE FUNCTION (p. 151)

•

EXECUTE (p. 151)

In this section, you can ﬁnd a list of the Microsoft SQL Server built-in functions that indicates whether the AWS Schema Conversion Tool performs an automatic conversion. Where MySQL doesn't support a function, consider creating a user-deﬁned function.

Aggregate Functions

Function

AVG

Automatically

Converted

Details

Yes

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Functions

Function

COUNT

COUNT_BIG

MIN

MAX

SUM

CHECKSUM_AGG

STDEV

STDEVP

GROUPING

GROUPING_ID

VAR

VARP

Automatically

Converted

Details

Yes

Partial

Yes

Partial

MySQL doesn't support the STDEV function with the

DISTINCT clause.

MySQL doesn't support the STDEVP function with the

DISTINCT clause.

Partial

MySQL doesn't support the VAR function with the

DISTINCT clause.

MySQL doesn't support the VARP function with the

DISTINCT clause.

Date and Time Functions

Function

DATEADD

DATEDIFF

DATENAME

DATEPART

DAY

GETDATE

GETDATE + 1

GETUTCDATE

MONTH

YEAR

Partial

Automatically

Converted

Details

Partial MySQL doesn't support the DATEADD function with the nanosecond datepart.

Partial

MySQL doesn't support the DATEDIFF function with the week, millisecond, or nanosecond datepart.

MySQL doesn't support the DATENAME function with the millisecond, nanosecond, or TZoﬀset datepart.

MySQL doesn't support the DATEPART function with the millisecond, nanosecond, or TZoﬀset datepart.

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Functions

Function Automatically

Converted

Details

DATETIMEOFFSETFROMPARTSNo

ISDATE

SWITCHOFFSET

SYSDATETIMEOFFSET

TODATETIMEOFFSET

LOG10

LOG

POWER

RADIANS

RAND

ROUND

ABS

ACOS

ASIN

ATN2

ATAN

CEILING

COS

COT

DEGREES

EXP

FLOOR

Mathematical Functions

Function

SIGN

SIN

SQRT

Yes

Partial

Yes

Automatically

Converted

Details

Yes

Partial

Yes

MySQL doesn't support the ROUND function with the function argument.

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Functions

Function

SQUARE

TAN

Automatically

Converted

Details

Yes

PATINDEX

QUOTENAME

REPLACE

REPLICATE

REVERSE

RIGHT

RTRIM

SOUNDEX

SPACE

STR

STUFF

SUBSTRING

UNICODE

UPPER

ASCII

CHAR

CHARINDEX

CONCAT

DIFFERENCE

FORMAT

LEFT

LEN

LOWER

LTRIM

NCHAR

String Functions

Function

Yes

Partial

Yes

Partial

Yes

Partial

Automatically

Converted

Details

Yes

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Functions

Conﬁguration Functions

Function

@@DATEFIRST

@@DBTS

@@LANGID

@@LANGUAGE

@@LOCK_TIMEOUT

@@MAX_CONNECTIONS

@@MAX_PRECISION

@@NESTLEVEL

@@OPTIONS

@@REMSERVER

@@SERVERNAME

@@SERVICENAME

@@SPID

@@TEXTSIZE

@@VERSION

Yes

Automatically

Converted

Details

Yes

Conversion Functions

Function

CAST and CONVERT

PARSE

TRY_CAST

TRY_CONVERT

TRY_PARSE

Automatically

Converted

Details

Security Functions

Function

CERTENCODED

CERTPRIVATEKEY

Automatically

Converted

Details

Yes

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Functions

Function

CURRENT_USER

DATABASE_PRINCIPAL_ID

HAS_PERMS_BY_NAME

IS_MEMBER

IS_ROLEMEMBER

IS_SRVROLEMEMBER

ORIGINAL_LOGIN

PERMISSIONS

PWDCOMPARE

PWDENCRYPT

SCHEMA_ID

SCHEMA_NAME

SESSION_USER

SUSER_ID

SUSER_NAME

SUSER_SID

SUSER_SNAME sys.fn_builtin_permissions

Yes sys.fn_get_audit_ﬁle Yes sys.fn_my_permissions

Yes

SYSTEM_USER

USER_ID

USER_NAME

Yes

Automatically

Converted

Details

Yes

System Functions

Function

$PARTITION

@@ERROR

@@IDENTITY

@@PACK_RECEIVED

Automatically

Converted

Details

Yes

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Functions

Function

@@ROWCOUNT

@@TRANCOUNT

BINARY_CHECKSUM

CHECKSUM

CONNECTIONPROPERTY

CONTEXT_INFO

CURRENT_REQUEST_ID

ERROR_LINE

ERROR_MESSAGE

ERROR_NUMBER

ERROR_PROCEDURE

ERROR_SEVERITY

ERROR_STATE

FORMATMESSAGE

Yes

Automatically

Converted

Details

Yes

GETANSINULL

HOST_ID

Yes

HOST_NAME

ISNULL

MIN_ACTIVE_ROWVERSION Yes

NEWID

NEWSEQUENTIALID

PARSENAME

ROWCOUNT_BIG

XACT_STATE

Yes

Logical Functions

Function

CHOOSE

IIF

Automatically

Converted

Details

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Operators

CREATE FUNCTION

Clause

@parameter_name type_schema_name parameter_data_type

= default

READONLY No

RETURNS return_data_type No

WITH function_option Yes

BEGIN … END No

RETURN scalar_expression Yes

Automatically

Converted

Details

Yes

MySQL supports only functions that return a scalar value.

EXECUTE

Clause

@parameter_name type_schema_name parameter_data_type

= default

Yes

READONLY No

RETURNS return_data_type No

Automatically

Converted

Details

Yes

WITH function_option

BEGIN … END

Yes

RETURN scalar_expression Yes MySQL supports only functions that return a scalar value.

Operators

Topics

•

Arithmetic Operators (p. 152)

•

Assignment Operator (p. 152)

•

Bitwise Operators (p. 152)

•

Comparison Operators (p. 152)

•

Logical Operators (p. 153)

•

Set Operators (p. 153)

•

String Concatenation Operator (p. 154)

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Operators

•

Unary Operators (p. 154)

Arithmetic Operators

Clause

Yes

Automatically

Converted

Details

Yes

Assignment Operator

Clause

Automatically

Converted

Details

Yes

Bitwise Operators

Clause Automatically

Converted

Details

Yes

Comparison Operators

Clause Automatically

Converted

Details

Yes

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Operators

Clause

Automatically

Converted

Details

Yes

ALL

AND

ANY

BETWEEN

EXISTS

NOT

SOME

Logical Operators

Clause

Yes

Partial

Automatically

Converted

Details

Yes

The AWS Schema Conversion Tool converts SOME to ANY.

Set Operators

Clause

UNION

UNION ALL

EXCEPT

INTERSECT

Automatically

Converted

Details

Yes

Perform a manual conversion.

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Transactions

String Concatenation Operator

Clause

Automatically

Converted

Details

Yes

Unary Operators

Clause Automatically

Converted

Details

Yes

Transactions

Topics

•

BEGIN TRANSACTION (p. 154)

BEGIN TRANSACTION

Clause

DISTRIBUTED transaction_name

WITH MARK

SAVE

ROLLBACK transaction_name savepoint_name

COMMIT

DELAYED_DURABILITY

Automatically

Converted

Details

No MySQL doesn't support distributed transactions. Revise your architecture so that it doesn't use distributed transactions.

MySQL doesn't support named transactions. Revise your code to eliminate marked transactions.

MySQL doesn't support the WITH MARK option. Revise your code to eliminate marked transactions.

Partial

No MySQL doesn't support named transactions. Revise your code to eliminate named transactions.

Partial

Data Types

Topics

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Data Types bigint int smallint tinyint bit money smallmoney numeric decimal ﬂoat real

•

Numerics (p. 155)

•

Date and Time (p. 155)

•

Character Strings (p. 156)

•

Binary Strings (p. 156)

•

Special Types (p. 156)

Numerics

Data type

Yes

Automatically

Converted

Default Conversion

Yes bigint

Yes

Yes int smallint tinyint unsigned bit(1) numeric(19,4) numeric(10,4) numeric decimal double ﬂoat

Date and Time

Data type

date datetime2(7)

Automatically

Converted

Default Conversion

Partial date

Partial datetime datetime Partial datetime datetimeoﬀset(7) smalldatetime time(7)

Yes

Yes datetime time

Details

0001-01-01 through

9999-12-31

0001-01-01 through

9999-12-31 00:00:00 through 23:59:59.9999999

1753-01-01, through

9999-12-31 00:00:00 through 23:59:59.997

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Data Types

Character Strings

Data type

char(len)

Automatically

Converted

Default Conversion

Partial char varchar(len) varchar(max) text nchar(len) nvarchar(len) nvarchar(max) ntext

Yes

Yes len = 1 -

4000

Yes

Yes varchar longtext longtext char varchar longtext longtext

Binary Strings

Data type

binary(len) varbinary(len) varbinary(max) hierarchyid sql_variant table uniqueidentiﬁer xml geography geometry

Special Types

Data type

UNIQUEIDENTIFIER

DOUBLE PRECISION

IDENTITY

Yes

Automatically

Converted

Default Conversion

Yes

Yes blob blob longblob

Details

len= 1 - 255 (2^8 - 1) symbols (loss range) len= 1 - 255 (2^8 - 1) symbols (loss range)

Details

Automatically

Converted

Default Conversion

Partial

CHAR(38) OR BINARY(16)

FLOAT(53)

Partial AUTO_INCREMENT

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Data Deﬁnition Language (DDL)

Data type

SYSNAME

Automatically

Converted

Default Conversion

Partial NVARCHAR(128) NOT NULL

Details

Data Deﬁnition Language (DDL)

Topics

•

CREATE TABLE (p. 157)

•

CREATE INDEX (p. 157)

•

CREATE TRIGGER (p. 157)

•

CREATE VIEW (p. 157)

CREATE TABLE

CREATE TABLE statements are converted automatically except for the following clause.

Clause

SET DEFAULT

Automatically

Converted

Details

No MySQL doesn't support the SET DEFAULT option for

FOREIGN KEY.

CREATE INDEX

The AWS Schema Conversion Tool does not support automatic migration of data deﬁnition language

(DDL) code to create an index.

CREATE TRIGGER

CREATE TRIGGER statements are converted automatically except for the following clause.

Clause

FOR

Automatically

Converted

Details

No MySQL doesn't support a FOR clause in a CREATE

TRIGGER statement.

CREATE VIEW

CREATE VIEW statements are converted automatically except for the following clauses.

Clause

SCHEMABINDING

ENCRYPTION

VIEW_METADATA

Automatically

Converted

Details

AWS Schema Conversion Tool ignores this clause.

No AWS Schema Conversion Tool ignores this clause.

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Cursors

Topics

•

DECLARE CURSOR (p. 158)

DECLARE CURSOR

Clause

LOCAL

GLOBAL

FORWARD_ONLY

SCROLL

STATIC

KEYSET

DYNAMIC

FAST_FORWARD

READ_ONLY

SCROLL_LOCKS

OPTIMISTIC

TYPE_WARNING

Automatically

Converted

Details

Yes

Partial

Change the global cursor to a local cursor, or revise your code so it doesn't require global cursors.

Setting this option corresponds to the typical behavior of cursors in MySQL, so the AWS Schema Conversion Tool skips this option during conversion.

Revise your code to eliminate cursors with the SCROLL option.

Yes The membership and order of rows never changes for cursors in MySQL, so the AWS Schema Conversion Tool skips this option during conversion. Verify that the converted schema behavior is acceptable.

Partial

Yes

Partial

Revise your code to eliminate dynamic cursors.

Setting this option corresponds to the typical behavior of cursors in MySQL, so the AWS Schema Conversion Tool skips this option during conversion.

All MySQL cursors are read-only, so the AWS Schema

Conversion Tool skips this option during conversion.

MySQL doesn't support the option SCROLL_LOCKS, so the AWS Schema Conversion Tool ignores this option during conversion. Verify that the converted schema behavior is acceptable.

MySQL doesn't support the option OPTIMISTIC, so the

AWS Schema Conversion Tool ignores this option during conversion. Verify that the converted schema behavior is acceptable.

MySQL doesn't support the option TYPE_WARNING, so the AWS Schema Conversion Tool ignores this option during conversion. Verify that the converted schema behavior is acceptable.

Change the global cursor to a local cursor, or revise your code so it doesn't require global cursors.

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Related Topics

•

Getting Started with the AWS Schema Conversion Tool (p. 11)

•

•

Installing and Updating the AWS Schema Conversion Tool (p. 6)

Microsoft SQL Server to PostgreSQL Supported

Schema Conversion

The following sections list the schema elements from a Microsoft SQL Server database and whether they are supported for automatic conversion to PostgreSQL using the AWS Schema Conversion Tool.

Data Deﬁnition Language (DDL)

Naming Objects

Clause

Schemas

Tables, Columns

Automatically

Converted

Details

Yes

Statements

Clause

ALTER INDEX

ALTER PROCEDURE

ALTER TRIGGER

ALTER VIEW

CREATE FUNCTION

CREATE PROCEDURE

CREATE SEQUENCE

IDENTITY (x,y)

TRUNCATE TABLE

UPDATE STATISTICS

Yes

Automatically

Converted

Details

Partial Automatic migration of inline functions is not supported.

Default parameters speciﬁed for any function are skipped.

Yes

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Data Deﬁnition Language (DDL)

ALTER TABLE

Clause Automatically

Converted

Details

Yes ADD

ALTER COLUMN

DROP COLUMN

DROP CONSTRAINT

ENABLE/DISABLE TRIGGER Yes

CREATE INDEX

Clause

CLUSTER option

COLUMNSTORE index

INCLUDE clause

Other INDEX options

SPATIAL index

UNIQUE option

XML index

Automatically

Converted

Details

Partial

Yes

Partial

CREATE TABLE

Clause

Partitioned tables

Regular tables

Temporary tables

Wide tables

Automatically

Converted

Details

Yes

Partial

Yes

CREATE TRIGGER

Clause Automatically

Converted

Details

Partial FOR EACH STATEMENT

Triggers

INSTEAD OF Triggers Partial

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Data Manipulation Language (DML)

Clause

Trigger event (INSERT/

UPDATE/DELETE )

Trigger time (BEGORE/

AFTER)

CREATE VIEW

Clause

CREATE VIEW

Updatable Views

VIEW

Automatically

Converted

Details

Partial

Automatically

Converted

Details

Yes

DROP Statements

Clause

DROP TABLE

DROP VIEW

Other types of objects

Automatically

Converted

Details

Yes

Data Manipulation Language (DML)

Clause for Statements

Clause

Join Hints

Query Hints

Table Hint

WHERE

Automatically

Converted

Details

Yes

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Data Manipulation Language (DML)

Joins

Cross Joins

Clause

Cross join

Cross join with condition

Inner Joins

Clause

Inner Joins

Outer Joins

Automatically

Converted

Details

Yes

Automatically

Converted

Details

Yes

Clause

Full join

Full outer join

Left join

Left outer join

Right join

Right outer join

Yes

Automatically

Converted

Details

Yes

Predicates for Statements

Clause

Boolean conditions

Exists conditions

In conditions

Null conditions

Pattern matching conditions

Range conditions

Automatically

Converted

Details

Yes

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Data Manipulation Language (DML)

Comparison Conditions

Clause

=, <>, <, <=, >, >=

ANY, SOME, ALL

Automatically

Converted

Details

Yes

Partial

Statements

DELETE

Clause

CURRENT OF

FROM

OUTPUT

TOP

VALUES

WITH

Yes

Automatically

Converted

Details

Yes

Partial

INSERT

Clause

DEFAULT

DEFAULT VALUES

FROM

INTO

OUTPUT

TOP

VALUES

WITH

Yes

Automatically

Converted

Details

Yes

SELECT

Clause

GROUP BY clause with an expression

Automatically

Converted

Details

Yes

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Data Manipulation Language (DML)

Clause Automatically

Converted

Details

Yes GROUP BY clause with multiple tables

GROUP BY CUBE

Group By Grouping Sets

GROUP BY ROLLUP

Limiting the number of rows returned

Select all columns (using the * and aliases)

Select all columns (using the *)

Select subset of the columns

Yes

Select with calculations Yes

Select with column heading Yes

Select with constants Yes

Specifying a ascending order

Specifying a collation

Yes

Yes Specifying a conditional order

Specifying a descending order

Yes

Specifying a percentage

(argument 100 percent)

Specifying an alias as the sort column

Specifying an expression as the sort column

Specifying both ascending and descending order

TOP with a variable

Using ORDER BY and

OFFSET command

Yes

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Data Manipulation Language (DML)

Clause

Using ORDER BY in a ranking function

Using ORDER BY with

UNION

Using WITH TIES

WHERE with BETWEEN

WHERE with combination of predicates

Automatically

Converted

Details

Yes

WHERE with CONTAINS

WHERE with EXISTS subquery

Yes

WHERE with FREETEXT No

WHERE with IN custom list Yes

WHERE with IN subquery Yes

WHERE with LIKE

WHERE with negates a

Boolean input

WHERE with NULL

Partial

Yes

DISTINCT

Clause

DISTINCT

FROM

Clause

FROM

Automatically

Converted

Details

Yes

Automatically

Converted

Details

Yes

GROUP BY

Clause

GROUP BY

Automatically

Converted

Details

Yes

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HAVING

Clause

HAVING

ORDER BY

Clause

ORDER BY

TOP

Clause

TOP

WHERE

Clause

WHERE

UPDATE

Clause

CURRENT OF

DEFAULT

FILESTREAM Data

FROM

OUTPUT

TOP

VALUES

WITH

AWS Schema Conversion Tool User Guide

Data Manipulation Language (DML)

Automatically

Converted

Details

Yes

Automatically

Converted

Details

Yes

Automatically

Converted

Details

Yes

Automatically

Converted

Details

Yes

Automatically

Converted

Details

Yes

Partial

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Data Types

Clause

BIGINT

BINARY

BIT

CHAR, CHARACTER

DATETIME

DATETIMEOFFSET

DEC, DECIMAL

DOUBLE PRECISION

FLOAT

GEOGRAPHY

GEOMETRY

HIERARCHYID

IDENTITY

INT, INTEGER

MONEY

NCHAR

NTEXT

NUMERIC

NVARCHAR

REAL

ROWVERSION

SMALL MONEY

SMALLDATETIME

SMALLINT

SQL_VARIANT

SYSNAME

TABLE

TEXT

TIMESTAMP

Yes

Automatically

Converted

Details

Yes

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Database Mail

Clause

TINYINT

UNIQUEIDENTIFIER

VARBINARY

VARCHAR

XML

Yes

Automatically

Converted

Details

Yes

Yes Converted to a universally unique identiﬁer (UUID) if the

PostgreSQL instance has the uuid-ossp module installed.

The uuid-ossp module provides functions to generate

UUIDs using one of several standard algorithms.

Database Mail

Clause

Accounts and Proﬁles

Database Mail

Conﬁguration Objects

Database Mail Messaging

Objects

Database Mail Settings

Security sp_send_dbmail sysmail_add_account_sp

Yes

Automatically

Converted

Details

Yes

Yes sysmail_add_profile_sp No sysmail_add_profileaccount_spNo sysmail_allitems sysmail_configure_sp

No sysmail_delete_account_sp No sysmail_delete_log_sp No sysmail_delete_mailitems_sp No sysmail_delete_proﬁle_sp No sysmail_event_log No

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Functions

Clause

sysmail_faileditems sysmail_help_account_sp No sysmail_help_conﬁgure_sp No

Automatically

Converted

Details

No sysmail_help_proﬁle_sp No sysmail_help_queue_sp sysmail_help_status_sp sysmail_help_status_sp sysmail_mailattachments sysmail_sentitems sysmail_start_sp sysmail_start_sp sysmail_stop_sp sysmail_stop_sp sysmail_unsentitems

No sysmail_update_account_sp No

No sysmail_update_proﬁle_sp No

Yes System State

Functions

@@functions

Clause

@@CONNECTIONS

@@CPU_BUSY

@@CURSOR_ROWS

Automatically

Converted

Details

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Functions

Clause

@@DATEFIRST

@@DBTS

@@ERROR

@@FETCH_STATUS

@@IDENTITY

@@IDLE

@@IO_BUSY

@@LANGID

@@LANGUAGE

@@LOCK_TIMEOUT

@@MAX_CONNECTIONS

@@MAX_PRECISION

@@NESTLEVEL

@@OPTIONS

@@PACK_RECEIVED

@@PACK_SENT

@@PACKET_ERRORS

@@PROCID

@@REMSERVER

@@ROWCOUNT

@@SERVERNAME

@@SERVICENAME

@@SPID

@@TEXTSIZE

@@TIMETICKS

@@TOTAL_ERRORS

@@TOTAL_READ

@@TOTAL_WRITE

@@TRANCOUNT

@@VERSION

Yes

Automatically

Converted

Details

Yes

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Functions

Aggregate

Clause

AVG

CHECKSUM_AGG

COUNT

COUNT_BIG

GROUPING

GROUPING_ID

MAX

MIN

STDEV

STDEVP

SUM

VAR

VARP

Yes

Automatically

Converted

Details

Partial

Yes

Built-in Functions

Clause

Aggregate Functions

Cursor Functions

Metadata Functions

Security Functions

System Functions

System Statistical

Functions

Text and Image Functions

Automatically

Converted

Details

Yes

Conversion

Clause

CAST

Automatically

Converted

Details

Partial

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Functions

Clause

CONVERT

PARSE

TRY_CAST

TRY_CONVERT

TRY_PARSE

Automatically

Converted

Details

Partial

Date and Time

Clause

CURRENT_TIMESTAMP

DATEADD

DATEDIFF

DATEFROMPARTS

DATENAME

DATEPART

DATETIME2FROMPARTS

DATETIMEFROMPARTS

Partial

DATETIMEOFFSETFROMPARTSPartial

DAY Yes

EOMONTH Yes

Automatically

Converted

Details

Partial

Yes

Partial

GETDATE

GETUTCDATE

ISDATE

MONTH

SMALLDATETIMEFROMPARTS Yes

SWITCHOFFSET No

SYSDATETIME Yes

Yes

SYSDATETIMEOFFSET

SYSUTCDATETIME

TIMEFROMPARTS

TODATETIMEOFFSET

Yes

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Functions

Clause

YEAR

Automatically

Converted

Details

Yes

LOG10()

PI()

POWER()

RADIANS()

RAND()

RAND(seed)

ROUND()

SIGN()

SIN()

SQRT()

SQUARE()

TAN()

ABS()

ACOS()

ASIN()

ATAN()

ATN2 ()

CEILING()

COS()

COT()

DEGREES()

EXP()

FLOOR()

LOG()

Mathematical Functions

Clause

Yes

Partial

Yes

Partial

Yes

Automatically

Converted

Details

Yes

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Functions

Ranking Functions

Clause

DENSE_RANK

NTILE

RANK

ROW_NUMBER

Automatically

Converted

Details

Yes

Rowset Functions

Clause

CONTAINSTABLE

FREETEXTTABLE

OPENDATASOURCE

OPENQUERY

OPENROWSET

OPENXML

Automatically

Converted

Details

Scalar Functions

Clause

ABS()

ACOS()

ASCII

ASIN()

ATAN()

ATN2 ()

AVG

CEILING()

CHAR

CHARINDEX

CHECKSUM

CHECKSUM_AGG

Yes

Automatically

Converted

Details

Yes

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Functions

Clause

CHOOSE

CONCAT

COS()

COT()

COUNT

COUNT_BIG

CURRENT_TIMESTAMP

CURRENT_USER

DATABASE_PRINCIPAL_ID

DATEADD

DATEDIFF

DATEFROMPARTS

DATENAME

DATEPART

DATETIME2FROMPARTS

DATETIMEFROMPARTS

Yes

DATETIMEOFFSETFROMPARTSNo

Partial

Yes

Partial

DAY

DEGREES()

DIFFERENCE

EOMONTH

ERROR_LINE

ERROR_MESSAGE

Yes

ERROR_NUMBER

ERROR_PROCEDURE

ERROR_SEVERITY

ERROR_STATE

EXP()

FLOOR()

FORMAT

Yes

Partial

Automatically

Converted

Details

Yes

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Clause

FORMATMESSAGE

GETDATE

GETUTCDATE

GROUPING

GROUPING_ID

HOST_ID

HOST_NAME

IIF

ISDATE

ISNULL

ISNUMERIC

LEFT

LEN

LOG()

LOG10()

LOWER

LTRIM

MAX

MIN

MONTH

NCHAR

ORIGINAL_LOGIN

PARSENAME

PATINDEX

PI()

POWER()

QUOTENAME

RADIANS()

AWS Schema Conversion Tool User Guide

Functions

Yes

Partial

Yes

Implemented in Extension

Library

Yes

Automatically

Converted

Details

Yes

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Functions

Clause

RAND()

REPLACE

REPLICATE

REVERSE

RIGHT

ROUND()

RTRIM

SCHEMA_NAME

SESSION_USER

SIGN()

SIN() Yes

SMALLDATETIMEFROMPARTS Yes

SOUNDEX

SPACE

Yes

SQRT()

SQUARE()

STDEV

Yes

STDEVP

STR

STUFF

SUBSTRING

SUM

SWITCHOFFSET

Yes

SYSDATETIME

SYSDATETIMEOFFSET

SYSUTCDATETIME

TAN()

TIMEFROMPARTS

TODATETIMEOFFSET

UNICODE

Yes

Automatically

Converted

Details

Yes

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Clause

UPPER

VAR

VARP

YEAR

String

Clause

QUOTENAME

REPLACE

REPLICATE

REVERSE

RIGHT

RTRIM

SOUNDEX

SPACE

STR

STUFF

SUBSTRING

ASCII

CHAR

CHARINDEX

CONCAT

DIFFERENCE

FORMAT

LEFT

LEN

LOWER

LTRIM

NCHAR

PATINDEX

AWS Schema Conversion Tool User Guide

Functions

Automatically

Converted

Details

Yes

Partial

Yes

Automatically

Converted

Details

Yes

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Operators

Clause

UNICODE

UPPER

Automatically

Converted

Details

Yes

Operators

Arithmetic Operators

Clause

- (Subtract)

% (Modulo)

* (Multiply)

/ (Divide)

+ (Add)

Automatically

Converted

Details

Partial

Assignment Operator

Clause

Automatically

Converted

Details

Yes

Bitwise Operators

Clause

& (Bitwise AND)

^ (Bitwise Exclusive OR)

| (Bitwise OR)

Automatically

Converted

Details

Yes

Comparison Operators

Clause

Comparison Operators

Automatically

Converted

Details

Partial

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Other

Logical Operators

Clause

Logical Operators

Automatically

Converted

Details

Yes

Set Operators

Clause

EXCEPT

INTERSECT

UNION

UNION ALL

Automatically

Converted

Details

Yes

String Concatenation Operator

Clause

String Concatenation

Operator

Automatically

Converted

Details

Yes

Unary Operators

Clause

Unary Operators

Automatically

Converted

Details

Yes

Other

Clause

CHECKSUM

CHOOSE

CURRENT_USER

DATABASE_PRINCIPAL_ID

ERROR_LINE

ERROR_MESSAGE

ERROR_NUMBER

Automatically

Converted

Details

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Service Broker

Clause

ERROR_PROCEDURE

ERROR_SEVERITY

ERROR_STATE

FORMATMESSAGE

HOST_ID

HOST_NAME

IIF

ISNULL

ISNUMERIC

Logical Functions

NEWID

ORIGINAL_LOGIN

Other

SCHEMA_NAME

Security Functions

SESSION_USER

System Functions

Yes

Automatically

Converted

Details

Service Broker

Clause

ALTER QUEUE

ALTER SERVICE

BEGIN CONVERSATION

TIMER

BEGIN DIALOG

CONVERSATION

CREATE QUEUE

CREATE SERVICE

DROP QUEUE

Automatically

Converted

Details

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Service Broker

Clause

DROP SERVICE

END CONVERSATION

GET CONVERSATION

GROUP

GET

TRANSMISSION_STATUS

MOVE CONVERSATION

Queue management

RECEIVE

SEND

Service Broker Catalog

Views

Yes

Service Broker Related

Dynamic Management

Views

Yes

Service Broker Statements Yes

Yes

Automatically

Converted

Details

Service management Yes sys.conversation_endpoints No sys.conversation_groups

No sys.conversation_priorities

No sys.dm_broker_activated_tasksNo

sys.dm_broker_connections No sys.remote_service_bindings No sys.routes

No sys.service_contract_usages No sys.service_contracts

No sys.service_message_types

No sys.service_queue_usages

No sys.service_queues

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SQL Server Agent

Clause

sys.services

sys.transmission_queue

Automatically

Converted

Details

SQL Server Agent

Clause

sp_add_alert sp_add_category sp_add_job sp_add_jobschedule sp_add_jobserver sp_add_jobstep sp_add_notiﬁcation sp_add_operator sp_add_proxy sp_add_schedule

No sp_add_targetservergroup No

Automatically

Converted

Details

No sp_add_targetsvrgrp_memberNo sp_apply_job_to_targets No sp_attach_schedule No sp_cycle_agent_errorlog sp_cycle_errorlog sp_delete_alert sp_delete_category

No sp_delete_job sp_delete_jobschedule sp_delete_jobserver sp_delete_jobstep sp_delete_jobsteplog sp_delete_notiﬁcation sp_delete_operator

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SQL Server Agent

Clause

sp_delete_proxy sp_delete_schedule sp_delete_targetserver

No sp_delete_targetservergroup No

Automatically

Converted

Details

No sp_detach_schedule sp_enum_login_for_proxy

No sp_grant_login_to_proxy No sp_grant_proxy_to_subsystemNo sp_help_alert No sp_help_category sp_help_downloadlist

No sp_help_job sp_help_jobactivity sp_help_jobcount sp_help_jobhistory sp_help_jobs_in_schedule sp_help_jobschedule

No sp_help_jobserver sp_help_jobstep sp_help_jobsteplog sp_help_notiﬁcation sp_help_operator sp_help_proxy sp_help_schedule sp_help_targetserver No sp_help_targetservergroup No sp_manage_jobs_by_login No

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SQL Server Backup

Clause

sp_msx_defect sp_msx_enlist sp_msx_get_account sp_msx_set_account sp_notify_operator sp_post_msx_operation sp_purge_jobhistory sp_remove_job_from_targetssNo sp_resync_targetserver No sp_revoke_login_from_proxy No

Automatically

Converted

Details

No sp_start_job sp_stop_job sp_update_alert sp_update_category sp_update_job sp_update_jobschedule sp_update_jobstep sp_update_notiﬁcation sp_update_operator sp_update_proxy sp_update_schedule

No sp_update_targetservergroup No

SQL Server Backup

Clause

BACKUP

BACKUP CERTIFICATE

BACKUP MASTER KEY

Automatically

Converted

Details

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T-SQL

Clause

BACKUP SERVICE MASTER

KEY

RESTORE

RESTORE FILELISTONLY

RESTORE HEADERONLY

RESTORE LABELONLY

RESTORE MASTER KEY

RESTORE REWINDONLY

RESTORE SERVICE MASTER

KEY

RESTORE VERIFYONLY

Automatically

Converted

Details

T-SQL

BACKUP and RESTORE

Clause

BACKUP and RESTORE

Statements

Automatically

Converted

Details

Collation

Clause

Collation

Automatically

Converted

Details

Control-of-Flow Language

Clause

BEGIN...END

BREAK

CONTINUE

GOTO

IF...ELSE

Automatically

Converted

Details

Yes

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T-SQL

Clause

RETURN

THROW

TRY...CATCH

WAITFOR

WHILE

Cursors

DECLARE CURSOR

Clause

DECLARE CURSOR

CURSOR with option

GLOBAL

CURSOR with options

FORWARD_ONLY or

SCROLL

Automatically

Converted

Details

Yes

Partial

Yes

Automatically

Converted

Details

Yes

FETCH

Clause

FETCH

OPEN

Clause

OPEN

Automatically

Converted

Details

Yes

Automatically

Converted

Details

Yes

DUMP and LOAD Statements

Clause

DUMP and LOAD

Statements

Automatically

Converted

Details

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Microsoft SQL Server to PostgreSQL

Conversion Issue Reference

Microsoft SQL Server to PostgreSQL Conversion Issue

Reference

Use the following sections to get information on the types of issues you might encounter during a

Microsoft SQL Server to PostgreSQL conversion. Choose the link in the Issue column to get more detailed resolution information about the issue if it is available.

Arithmetic Operators

Item Issue

Arithmetic operators

Issue 7775: Check the data type conversion for possible loss of accuracy (p. 196)

Arithmetic operators and date types

Issue 7773: Unable to perform an automated migration of arithmetic operations with dates (p. 196)

Arithmetic operators and mixed types

Issue 7774: Unable to perform an automated migration of the arithmetic operations with mixed types of operands (p. 197)

Resolution

Cast values as the intended type.

Built-In Services

Item

Database Mail

Service Broker

SQL Server Agent

SQL Server Backup

Issue

Issue 7900: PostgreSQL does not have functionality similar to SQL Server Database

Mail (p. 197)

Issue 7901: PostgreSQL does not have functionality similar to SQL Server Service

Broker (p. 197)

Issue 7902: PostgreSQL does not have functionality similar to SQL Server

Agent (p. 197)

Issue 7903: PostgreSQL does not have functionality similar to SQL Server

Backup (p. 197)

Resolution

Try using the Amazon Simple

Notiﬁcation Service (Amazon

SNS).

Try using the Amazon Simple

Queue Service (Amazon SQS).

Try using the AWS Lambda service with Scheduled

Events.

Try using the Amazon Glacier storage service.

Built-In SQL Functions

Item

SOUNDEX

Issue

Issue 7811: PostgreSQL doesn't support the

SOUNDEX function (p. 198)

Resolution

Create a user-deﬁned function.

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Microsoft SQL Server to PostgreSQL

Conversion Issue Reference

Item

Cursors

DECLARE / DEFAULT

VALUE

GOTO

Procedures

Result sets

WAITFOR DELAY

WAITFOR TIME

Issue

Issue 7801: The table can be locked open cursor (p. 198)

Issue 7826: Check the default value for a

DateTime variable (p. 198)

Issue 7628: PostgreSQL doesn't support the

GOTO option. Automatic conversion can't be performed. (p. 198)

Issue 7802: A table that is created within the procedure, must be deleted before the end of the procedure (p. 198)

Issue 7800: PostgreSQL doesn't support result sets in the style of MSSQL (p. 198)

Issue 7821: Automatic conversion operator WAITFOR with a variable is not supported (p. 198)

Issue 7691: PostgreSQL doesn't support

WAITFOR TIME feature (p. 198)

Resolution

Review your transformed code and modify it if necessary.

Check the default value for a

DateTime variable.

Revise your code to eliminate

GOTO operators, using

BEGIN...END blocks in combination with EXIT,

REPEAT, UNTIL, and WHILE operators.

Review your transformed code and modify it if necessary.

Perform a manual conversion.

CREATE

Item

Encrypted objects

Issue

Issue 7696: Unable convert object due to %s not created (p. 199)

Issue 7813: Encrypted objects (p. 199)

Resolution

Review the %s object.

Decrypt the object before conversion.

CURSORS

Item

CURSOR with option

GLOBAL

Issue

Issue 7637: PostgreSQL doesn't support

GLOBAL CURSORS. Requires manual conversion. (p. 199)

CURSOR with options

STATIC or KEYSET or DYNAMIC or

FAST_FORWARD

Issue 7639: PostgreSQL doesn't support

DYNAMIC cursors (p. 199)

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Resolution

Change the global cursor to a local cursor, or revise your code so it doesn't require global cursors.

Revise your code to eliminate dynamic cursors.

Item

FAST_FORWARD option

FOR UPDATE

KEYSET option

OPTIMISTIC option

READ_ONLY option

TYPE_WARNING option

AWS Schema Conversion Tool User Guide

Microsoft SQL Server to PostgreSQL

Conversion Issue Reference

Issue

Issue 7701: Setting this option corresponds to the typical behavior of cursors in PostgreSQL, so this option is skipped (p. 199)

Issue 7803: PostgreSQL doesn't support the option FOR UPDATE, so this option is skipped (p. 199)

Issue 7700: The membership and order of rows never changes for cursors in PostgreSQL, so this option is skipped (p. 199)

Issue 7704: PostgreSQL doesn't support the option OPTIMISTIC, so this option is skipped (p. 199)

Issue 7702: All PostgreSQL cursors are readonly, so this option is skipped (p. 200)

Issue 7705: PostgreSQL doesn't support the option TYPE_WARNING, so this option is skipped (p. 200)

Resolution

Use cursors without this option.

Review your transformed code and modify it if necessary.

Use cursors without this option.

DATA TYPES

Item

BYTEA geography geometry hierarchyid rowversion sql_variant

Issue

Issue 7818: PostgreSQL doesn't support arithmetic operations with binary data types (p. 200)

Issue 7662: PostgreSQL doesn't support this type. A manual conversion is required. (p. 200)

Issue 7664: PostgreSQL doesn't support this type. A manual conversion is required. (p. 200)

Issue 7657: PostgreSQL doesn't support this type. A manual conversion is required. (p. 200)

Resolution

Perform a manual conversion.

To store data of this type in PostgreSQL, use a

PostgreSQL-compatible type or use a composite type.

To store data of this type in PostgreSQL, use a

PostgreSQL-compatible type or use a composite type.

To store data of this type in PostgreSQL, use a

PostgreSQL-compatible type or use a composite type.

Perform a manual conversion.

Issue 7706: PostgreSQL doesn't support this type (p. 200)

Issue 7658: PostgreSQL doesn't support this type. A manual conversion is required. (p. 200)

To store data of this type in PostgreSQL, use a

PostgreSQL-compatible type or use a composite type.

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Item

table

UDT

XML

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Issue

Issue 7659: The scope table-variables and temporary tables is diﬀerent. You must apply manual conversion, if you are using recursion. (p. 200)

Issue 7690: PostgreSQL doesn't support table types (p. 201)

Issue 7816: PostgreSQL doesn't support any methods for data type XML (p. 201)

Issue 7817: PostgreSQL doesn't support option [for xml path] in the SQL queries (p. 201)

Resolution

Perform a manual conversion.

DDL

Item

CREATE INDEX

Issue

Issue 7675: PostgreSQL doesn't support sorting options (ASC | DESC) for constraints (p. 201)

Issue 7681: PostgreSQL doesn't support clustered indexes (p. 201)

Issue 7682: PostgreSQL doesn't support the

INCLUDE option in indexes (p. 201)

Issue 7781: PostgreSQL doesn't support the

PAD_INDEX option in indexes (p. 201)

Issue 7782: PostgreSQL doesn't support the

SORT_IN_TEMPDB option in indexes (p. 202)

Issue 7783: PostgreSQL doesn't support the

IGNORE_DUP_KEY option in indexes (p. 202)

Issue 7784: PostgreSQL doesn't support the STATISTICS_NORECOMPUTE option in indexes (p. 202)

Issue 7785: PostgreSQL doesn't support the STATISTICS_INCREMENTAL option in indexes (p. 202)

Issue 7786: PostgreSQL doesn't support the

DROP_EXISTING option in indexes (p. 202)

Issue 7787: PostgreSQL doesn't support the

ONLINE option in indexes (p. 202)

Issue 7788: PostgreSQL doesn't support the ALLOW_ROW_LOCKS option in indexes (p. 202)

Resolution

Use indexes without this option.

Use nonclustered indexes.

Use index without this option.

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Item

CREATE INDEX

CREATE TABLE

Inline Function

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Conversion Issue Reference

Issue

Issue 7789: PostgreSQL doesn't support the ALLOW_PAGE_LOCKS option in indexes (p. 202)

Issue 7790: PostgreSQL doesn't support the

MAXDOP option in indexes (p. 202)

Issue 7791: PostgreSQL doesn't support the DATA_COMPRESSION option in indexes (p. 202)

Resolution

Use index without this option.

Issue 7679: PostgreSQL doesn't support computed columns (p. 202)

Issue 7680: PostgreSQL doesn't support global temporary tables (p. 202)

Issue 7812: Temporary table must be removed before the end of the function (p. 202)

Try using a trigger.

Use local temporary or regular tables.

Review your transformed code and modify it if necessary.

Issue 7825: The default value for a DateTime column removed (p. 203)

Issue 7776: Automatic migration of inline functions not supported (p. 203)

Review generated code and modify it if necessary.

Perform a manual conversion.

DELETE

Item

DELETE with Table

Hint Limited

TOP

Issue

Issue 7623: PostgreSQL doesn't support hints in DELETE statements. The conversion skips options in the format

WITH(Table_Hint_Limited). (p. 203)

Issue 7798: PostgreSQL doesn't support TOP option in the operator DELETE (p. 203)

Resolution

Use PostgreSQL methods for performance tuning.

Perform a manual conversion.

DML, FROM

Item

Table Hints

Issue

Issue 7823: PostgreSQL doesn't support table hints in DML statements (p. 203)

Resolution

Use PostgreSQL methods of performance tuning.

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EXECUTE

Item

EXECUTE a character string

Execute a passthrough command against a linked server

EXECUTE with execute options

[RECOMPILE]

Issue

Issue 7695: PostgreSQL doesn't support the execution of a procedure as a variable (p. 204)

Issue 7672: Automatic conversion of this command is not supported (p. 204)

Issue 7645: PostgreSQL doesn't support executing a pass-through command on a linked server (p. 204)

Issue 7640: The EXECUTE with RECOMPILE option is ignored (p. 204)

EXECUTE with execute options

Issue 7643: The EXECUTE with RESULT

SETS <result set deﬁnition> option is

[RESULT SETS

ignored (p. 204)

(<result_sets_deﬁnition>)]

EXECUTE with execute options

[RESULT SETS NONE]

EXECUTE with execute options

[RESULT SETS

UNDEFINED]

Issue 7642: The EXECUTE with RESULT SETS

NONE option is ignored (p. 204)

Issue 7641: The EXECUTE with RESULT SETS

UNDEFINED option is ignored (p. 204)

Resolution

Perform a manual conversion using dynamic SQL.

Perform a manual conversion.

Use other methods to execute statements on a remote server.

Use EXECUTE command without this option.

INSERT

Item

EXECUTE

TOP

Issue

Issue 7819: PostgreSQL doesn't support

INSERT...EXECUTE statements (p. 204)

Issue 7799: PostgreSQL doesn't support TOP option in the operator INSERT (p. 205)

Resolution

Perform a manual conversion.

Operators

Item

Bitwise Operators

Comparison

Operators

Comparison

Operators

Issue

Issue 7804: PostgreSQL doesn't support operator [Bitwise exclusive OR] (p. 205)

Issue 7805: PostgreSQL doesn't support operator [Not less than] (p. 205)

Issue 7806: PostgreSQL doesn't support operator [Not greater than] (p. 205)

Version 1.0

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Resolution

Perform a manual conversion.

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Parser Error

Item

Parser Error

SEQUENCE

Item

Speciﬁc data type

Issue

Issue 7663: Unable to resolve the object (p. 206)

SELECT

Item

GROUP BY CUBE

Group By Grouping

Sets

ORDER BY Specifying a collation search condition search condition search condition

TOP WITH TIES

Issue

Issue 7653: PostgreSQL doesn't support the option GROUP BY ROLLUP. Automatic conversion can't be performed. (p. 206)

Issue 7654: PostgreSQL doesn't support the option GROUP BY CUBE. Automatic conversion can't be performed. (p. 206)

Issue 7655: PostgreSQL doesn't support the option GROUP BY GROUPING

SETS. Automatic conversion can't be performed. (p. 206)

Issue 7646: PostgreSQL doesn't support the COLLATE option in the ORDER BY clause. Automatic conversion can't be performed. (p. 206)

Issue 7687: PostgreSQL doesn't support the

CONTAINS predicate (p. 206)

Issue 7688: PostgreSQL doesn't support the

FREETEXT predicate (p. 206)

Issue 7795: PostgreSQL is case sensitive.

Check the string comparison. (p. 206)

Issue 7605: PostgreSQL doesn't support the

WITH TIES option (p. 206)

Resolution

Try creating a stored procedure to replace the query.

You must use the COLLATION settings that were assigned when the database was created.

Perform a manual conversion.

Check the string comparison.

Perform a manual conversion.

Issue

Issue 7793: PostgreSQL doesn't support changing data type in sequences (p. 207)

Resolution

Verify if object <object name> is present in the database.

If it isn't, check the object name or add the object. If the object is present, transform the code manually.

Resolution

Review your transformed code and modify it if necessary.

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SYNONYMS

Item

CREATE

TRIGGERS

Item

Triggers

Issue

Issue 7792: PostgreSQL doesn't support synonyms (p. 207)

Issue

Issue 7809: In PostgreSQL there are no analogues of the tables 'inserted' and

'deleted' (p. 208)

Resolution

Replace a synonym with original database object. If original object is table or view you can try to create a view in one database that relies on a table or view in another database.

SYS objects

Item

SYS objects

Issue

Issue 7904: Unable to convert system object

Resolution

Perform a manual conversion.

TRANSACTION

Item

Transaction

Issue

Issue 7807: Transactions in functions

PostgreSQL doesn't support (p. 207)

Resolution

Perform a manual conversion.

Resolution

Perform a manual conversion.

Unknown

Item

Unknown Clause

Unparsed SQL

Issue

Issue 7627: This syntactic element conversion is not supported yet (p. 209)

Issue 7674: Automatic conversion of

<clause name> clause of <statement name> statement is not supported (p. 209)

Issue 7808: Unparsed SQL (p. 209)

Resolution

Perform a manual conversion.

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UPDATE

Item

TOP

UPDATE

Variable assignment

Issue

Issue 7796: PostgreSQL doesn't support TOP option in the operator UPDATE (p. 209)

Issue 7797: PostgreSQL doesn't have analog for option "OUTPUT" with using the implicit table "deleted" in the operator for

UPDATE (p. 210)

Issue 7829: Unable to convert variable assignment by UPDATE statement (p. 211)

Resolution

Perform a manual conversion.

This case requires manual conversion.

Perform a manual conversion.

User Types

Item

User-Deﬁned Data

Types

Issue

Issue 7794: PostgreSQL doesn't support userdeﬁned data types (p. 211)

Resolution

Perform a manual conversion.

Conversion Issues with Arithmetic Operators

Issue 7775: Check the data type conversion for possible loss of accuracy

To avoid loss of accuracy for types in arithmetic operations, cast values as the intended type, as in the example following.

BEGIN

SELECT

5.1E+1::REAL

INTO lBinaryFloat;

SELECT

- 5.2E-1::DOUBLE PRECISION

INTO lBinaryDouble;

var1 := (var_varchar1||var_varchar2)::INTEGER;

var2 := (var_varchar1||var_varchar3)::NUMERIC;

var3 := var_varchar1::NUMERIC + var_numeric2;

var4 := var_timestamp2 + (var_numeric1::NUMERIC || 'day')::INTERVAL;

END;

Issue 7773: Unable to perform an automated migration of arithmetic operations with dates

The Schema Conversion Tool cannot automatically migrate arithmetic operations that use date types.

Cast values as the intended type, as in the example following.

BEGIN

var3 := var_varchar1::NUMERIC + var_numeric2;

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var4 := var_timestamp2 + (var_numeric1::NUMERIC || 'day')::INTERVAL;

END;

Issue 7774: Unable to perform an automated migration of the arithmetic operations with mixed types of operands

The Schema Conversion Tool cannot automatically migrate arithmetic operations that mix types. For example, multiplying a variable of type FLOAT with a variable of type INT. Cast values as the intended type before performing any arithmetic operations, as in the example following.

BEGIN

var1 := (var_varchar1||var_varchar2)::INTEGER;

var2 := (var_varchar1||var_varchar3)::NUMERIC;

END;

Related Topics

•

Microsoft SQL Server to PostgreSQL Conversion Issue Reference (p. 188)

•

•

Microsoft SQL Server to PostgreSQL Conversion Issue Reference (p. 188)

Conversion Issues with BUILT-IN SERVICES

Issue 7900: PostgreSQL does not have functionality similar to SQL Server

Database Mail

Try using the Amazon Simple Queue Service (Amazon SQS). For more information, see What is Amazon

Simple Queue Service?

Issue 7901: PostgreSQL does not have functionality similar to SQL Server

Service Broker

Try using the Amazon Simple Queue Service (SQS). For more information, see What is Amazon Simple

Queue Service?

in the Amazon SQS documentation.

Issue 7902: PostgreSQL does not have functionality similar to SQL Server Agent

Try using the AWS Lambda service with Scheduled Events. For more information, see What Is AWS

Lambda?

in the AWS Lambda Developer Guide.

Issue 7903: PostgreSQL does not have functionality similar to SQL Server

Backup

Try using the Amazon Glacier storage service. For more information, see What Is Amazon Glacier?

in the

Amazon Glacier Developer Guide.

Related Topics

•

•

•

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Conversion Issues with BUILT-IN SQL FUNCTIONS

Issue 7811: PostgreSQL doesn't support the SOUNDEX function

Create a user-deﬁned function.

Related Topics

•

•

•

Microsoft SQL Server to PostgreSQL Conversion Issue Reference (p. 188)

Conversion Issues with CONTROL FLOW

Issue 7800: PostgreSQL doesn't support result sets in the style of MSSQL

Review your transformed code and modify it if necessary.

Issue 7801: The table can be locked open cursor

In Microsoft SQL Server, a local temporary table created in a stored procedure is dropped automatically when the stored procedure completes. Temporary tables in PostgreSQL are automatically dropped at the end of a session. The conversion uses the DROP TABLE IF EXISTS statement to emulate this behavior and remove the temporary table before the end of the function that created it. In some cases though, this statement might fail because the temporary table is locked due to an open cursor. In this case, the DROP

TABLE statement must be commented out. Review your transformed code and modify it if necessary.

Issue 7802: A table that is created within the procedure, must be deleted before the end of the procedure

Review your transformed code and modify it if necessary.

Issue 7826: Check the default value for a DateTime variable

Check the default value for a DateTime variable.

Issue 7628: PostgreSQL doesn't support the GOTO option. Automatic conversion can't be performed.

Revise your code to eliminate GOTO operators, using BEGIN...END blocks in combination with EXIT,

REPEAT, UNTIL, and WHILE operators.

Issue 7821: Automatic conversion operator WAITFOR with a variable is not supported

You must perform a manual conversion in cases where you have a WAITFOR DELAY statement that uses a variable, for example

WAITFOR DELAY @time;

, instead of a literal value, for example

WAITFOR DELAY

'00:00:05';

Issue 7691: PostgreSQL doesn't support WAITFOR TIME feature

Perform a manual conversion.

Related Topics

•

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•

•

Microsoft SQL Server to PostgreSQL Conversion Issue Reference (p. 188)

Conversion Issues with CREATE

Issue 7696: Unable convert object due to %s not created

Review the <object name> object.

Issue 7813: Encrypted objects

Decrypt the object before conversion.

Related Topics

•

•

•

Microsoft SQL Server to PostgreSQL Conversion Issue Reference (p. 188)

Conversion Issues with CURSORS

Issue 7637: PostgreSQL doesn't support GLOBAL CURSORS. Requires manual conversion.

Change the global cursor to a local cursor, or revise your code so it doesn't require global cursors.

Issue 7639: PostgreSQL doesn't support DYNAMIC cursors

Revise your code to remove the DYNAMIC option from any cursors.

Issue 7701: Setting this option corresponds to the typical behavior of cursors in

PostgreSQL, so this option is skipped

The FAST_FORWARD option is skipped during conversion, because PostgreSQL cursors provide the same behavior as the FAST_FORWARD option by default. Review your transformed code and modify it if necessary.

Issue 7803: PostgreSQL doesn't support the option FOR UPDATE, so this option is skipped

The FOR_UPDATE option is skipped during conversion because PostgreSQL doesn't support it. Review your transformed code and modify it if necessary.

Issue 7700: The membership and order of rows never changes for cursors in

PostgreSQL, so this option is skipped

Use cursors without this option.

Issue 7704: PostgreSQL doesn't support the option OPTIMISTIC, so this option is skipped

Use cursors without this option.

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Issue 7702: All PostgreSQL cursors are read-only, so this option is skipped

Use cursors without this option.

Issue 7705: PostgreSQL doesn't support the option TYPE_WARNING, so this option is skipped

Use cursors without this option.

Related Topics

•

•

•

Microsoft SQL Server to PostgreSQL Conversion Issue Reference (p. 188)

Conversion Issues with DATA TYPES

Issue 7818: PostgreSQL doesn't support arithmetic operations with binary data types

Perform a manual conversion.

Issue 7662: PostgreSQL doesn't support this type. A manual conversion is required.

PostgreSQL doesn't support the geography data type. To store data of this type in PostgreSQL, use a

PostgreSQL-compatible type or use a composite type.

Issue 7664: PostgreSQL doesn't support this type. A manual conversion is required.

PostgreSQL doesn't support the geometry data type. To store data of this type in PostgreSQL, use a

PostgreSQL-compatible type or use a composite type.

Issue 7657: PostgreSQL doesn't support this type. A manual conversion is required.

PostgreSQL doesn't support the hierarchyid data type. To store data of this type in PostgreSQL, use a

PostgreSQL-compatible type or use a composite type.

Issue 7706: PostgreSQL doesn't support this type

PostgreSQL doesn't support the rowversion data type. To store data of this type in PostgreSQL, use a

PostgreSQL-compatible type.

Issue 7658: PostgreSQL doesn't support this type. A manual conversion is required.

PostgreSQL doesn't support the sql_variant data type. To store data of this type in PostgreSQL, use a

PostgreSQL-compatible type or use a composite type.

Issue 7659: The scope table-variables and temporary tables is diﬀerent. You must apply manual conversion, if you are using recursion.

Perform a manual conversion.

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Issue 7690: PostgreSQL doesn't support table types

PostgreSQL doesn’t support table parameters in CREATE PROCEDURE statements, as in the example following.

CREATE TYPE Employee2Client AS TABLE(

EmployeeID int,

EmployeeName varchar(160),

ClientID int,

ClientName varchar(160)

) go

CREATE PROCEDURE [dbo].[PROC_CREATE_PROC_005]

@p_E2C Employee2Client READONLY

BEGIN

select * from @p_E2C where upper(ClientName) like concat('%', upper('bank'), '%') ;

Convert to temporary tables or row variables (for example, name table_name%ROWTYPE;

Issue 7816: PostgreSQL doesn't support any methods for data type XML

Microsoft SQL Server provides methods for the xml data type that you can use to read and manipulate

XML data, but PostgreSQL's xml data type does not oﬀer parallel functionality. Perform a manual conversion to use PostgreSQL XML handling functionality instead.

Issue 7817: PostgreSQL doesn't support option [for xml path] in the SQL queries

PostgreSQL doesn't support using the FOR XML clause in PATH mode for DML statements. Perform a manual conversion to use PostgreSQL XML handling functionality instead.

Related Topics

•

•

•

Microsoft SQL Server to PostgreSQL Conversion Issue Reference (p. 188)

Conversion Issues with DDL

Issue 7675: PostgreSQL doesn't support sorting options (ASC | DESC) for constraints

Remove these options from indexes and constraints.

Issue 7681: PostgreSQL doesn't support clustered indexes

Use nonclustered indexes.

Issue 7682: PostgreSQL doesn't support the INCLUDE option in indexes

Use the index without this option.

Issue 7781: PostgreSQL doesn't support the PAD_INDEX option in indexes

Use the index without this option.

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Issue 7782: PostgreSQL doesn't support the SORT_IN_TEMPDB option in indexes

Use the index without this option.

Issue 7783: PostgreSQL doesn't support the IGNORE_DUP_KEY option in indexes

Use the index without this option.

Issue 7784: PostgreSQL doesn't support the STATISTICS_NORECOMPUTE option in indexes

Use the index without this option.

Issue 7785: PostgreSQL doesn't support the STATISTICS_INCREMENTAL option in indexes

Use the index without this option.

Issue 7786: PostgreSQL doesn't support the DROP_EXISTING option in indexes

Use the index without this option.

Issue 7787: PostgreSQL doesn't support the ONLINE option in indexes

Use the index without this option.

Issue 7788: PostgreSQL doesn't support the ALLOW_ROW_LOCKS option in indexes

Use index without this option.

Issue 7789: PostgreSQL doesn't support the ALLOW_PAGE_LOCKS option in indexes

Use index without this option.

Issue 7790: PostgreSQL doesn't support the MAXDOP option in indexes

Use index without this option.

Issue 7791: PostgreSQL doesn't support the DATA_COMPRESSION option in indexes

Use index without this option.

Issue 7679: PostgreSQL doesn't support computed columns

Try using a trigger instead.

Issue 7680: PostgreSQL doesn't support global temporary tables

Use local temporary or regular tables.

Issue 7812: Temporary table must be removed before the end of the function

Review your transformed code and modify it if necessary.

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Issue 7825: The default value for a DateTime column removed

Review generated code and modify it if necessary.

Issue 7776: Automatic migration of inline functions not supported

Perform a manual conversion.

Related Topics

•

•

•

Microsoft SQL Server to PostgreSQL Conversion Issue Reference (p. 188)

Conversion Issues with DELETE

Issue 7623: PostgreSQL doesn't support hints in DELETE statements. The conversion skips options in the format WITH(Table_Hint_Limited).

PostgreSQL doesn't support usings hints (for example, WITH FORCESCAN) to override the default behavior of the query optimizer when executing Data Manipulation Language (DML) statements. Use

PostgreSQL methods for performance tuning instead.

Issue 7798: PostgreSQL doesn't support TOP option in the operator DELETE

Perform a manual conversion for any DELETE statements that contain a TOP argument, as in the example following.

delete top (<expression >)[PERCENT] from <table-name>;

In PostgreSQL, you can use a subquery in the WHERE clause to identify the rows you want to delete.

Related Topics

•

•

•

Microsoft SQL Server to PostgreSQL Conversion Issue Reference (p. 188)

Conversion Issues with DML, FROM

Issue 7823: PostgreSQL doesn't support table hints in DML statements

PostgreSQL doesn't support usings hints (for example, WITH FORCESCAN) to override the default behavior of the query optimizer when executing Data Manipulation Language (DML) statements. Use

PostgreSQL methods of performance tuning instead.

Related Topics

•

•

•

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Conversion Issues with EXECUTE

Issue 7695: PostgreSQL doesn't support the execution of a procedure as a variable

Perform a manual conversion (one possibility is to use dynamic SQL). This issue occurs when you pass in the name of a procedure to an EXECUTE statement by using a variable, as in the example following.

ALTER PROCEDURE [dbo].[PROC_EXECUTE_009]

SET NOCOUNT ON

BEGIN

declare @v_ID int;

declare @v_ProcName varchar(20) = '[dbo].[PROC_DML_015]';

exec @v_ProcName

@v_ID output

Issue 7672: Automatic conversion of this command is not supported

This issue is often caused by an EXECUTE statement that executes a string or variable, for example

EXEC('select * from Customer');

EXEC(@variable);

. Convert each of these statements to a pair of

PREPARE and EXECUTE statements in PostgreSQL.

Issue 7645: PostgreSQL doesn't support executing a pass-through command on a linked server

Use other methods to execute statements on a remote server.

Issue 7640: The EXECUTE with RECOMPILE option is ignored

Use the EXECUTE command without this option.

Issue 7643: The EXECUTE with RESULT SETS <result set deﬁnition> option is ignored

Use the EXECUTE command without this option.

Issue 7642: The EXECUTE with RESULT SETS NONE option is ignored

Use the EXECUTE command without this option.

Issue 7641: The EXECUTE with RESULT SETS UNDEFINED option is ignored

Use the EXECUTE command without this option.

Related Topics

•

•

•

Microsoft SQL Server to PostgreSQL Conversion Issue Reference (p. 188)

Conversion Issues with INSERT

Issue 7819: PostgreSQL doesn't support INSERT...EXECUTE statements

Perform a manual conversion. PostgreSQL doesn't support using EXECUTE within an INSERT statement to insert the results of a stored procedure into a table.

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Issue 7799: PostgreSQL doesn't support TOP option in the operator INSERT

Perform a manual conversion for any INSERT statements that contain a TOP argument, as in the example following.

insert TOP(2) percent into Customer(

,sname

,name

,typeid

,taxcode

,stateid

,opendate

,closedate

)select

id+1000

,name

,61+id

,getdate()

,null from

employees e where

name not in(select name from Customer)

and exists(select 1 from Employees where ManagerId = e.id)

In PostgreSQL, you can use the row_number() window function in the FROM clause or a subquery in the

WHERE clause of the SELECT statement you use to select the data to be inserted to identify the rows you want to insert.

Related Topics

•

•

•

Microsoft SQL Server to PostgreSQL Conversion Issue Reference (p. 188)

Conversion Issues with Operators

Issue 7804: PostgreSQL doesn't support operator [Bitwise exclusive OR]

Perform a manual conversion.

Issue 7805: PostgreSQL doesn't support operator [Not less than]

Perform a manual conversion.

Issue 7806: PostgreSQL doesn't support operator [Not greater than]

Perform a manual conversion.

Related Topics

•

•

•

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Conversion Issue Reference

Conversion Issues with Parser Error

Issue 7663: Unable to resolve the object

Verify if object <object name> is present in the database. If it isn't, check the object name or add the object. If the object is present, transform the code manually.

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Microsoft SQL Server to PostgreSQL Conversion Issue Reference (p. 188)

Conversion Issues with SELECT

Issue 7653: PostgreSQL doesn't support the option GROUP BY ROLLUP.

Automatic conversion can't be performed.

Try creating a stored procedure to replace the query.

Issue 7654: PostgreSQL doesn't support the option GROUP BY CUBE. Automatic conversion can't be performed.

Try creating a stored procedure to replace the query.

Issue 7655: PostgreSQL doesn't support the option GROUP BY GROUPING SETS.

Automatic conversion can't be performed.

Try creating a stored procedure to replace the query.

Issue 7646: PostgreSQL doesn't support the COLLATE option in the ORDER BY clause. Automatic conversion can't be performed.

You must use the collation settings that were assigned when the database was created.

Issue 7687: PostgreSQL doesn't support the CONTAINS predicate

Perform a manual conversion by re-writing the SELECT statement to use PostgreSQL full-text search functionality instead. For more information about full-text search in PostgreSQL, see Tables and Indexes in the PostgreSQL documentation.

Issue 7688: PostgreSQL doesn't support the FREETEXT predicate

Issue 7795: PostgreSQL is case sensitive. Check the string comparison.

Check string comparisons in the WHERE clauses of statements, for example

WHERE [Name] LIKE

'%BLOCKED%';

. All strings used in comparisons must be lowercase.

Issue 7605: PostgreSQL doesn't support the WITH TIES option

Perform a manual conversion of any TOP statements that use the WITH TIES clause. You can use the rank() window function in PostgreSQL to provide similar results.

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Microsoft SQL Server to PostgreSQL Conversion Issue Reference (p. 188)

Conversion Issues with SEQUENCE

Issue 7793: PostgreSQL doesn't support changing data type in sequences

PostgreSQL doesn't support setting a sequence's data type by using the AS clause of the CREATE

SEQUENCE statement. Review your transformed code and modify it if necessary.

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Microsoft SQL Server to PostgreSQL Conversion Issue Reference (p. 188)

Conversion Issues with SYNONYMS

Issue 7792: PostgreSQL doesn't support synonyms

PostgreSQL doesn't support the CREATE SYNONYM statement. To convert, replace the synonym in any statement with the original database object. If the original object is a table or view, you can try to create a view in one database that relies on a table or view in another database.

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Microsoft SQL Server to PostgreSQL Conversion Issue Reference (p. 188)

Conversion Issues with SYS objects

Issue 7904: Unable to convert system object <object name>

Perform a manual conversion.

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Microsoft SQL Server to PostgreSQL Conversion Issue Reference (p. 188)

Conversion Issues with TRANSACTION

Issue 7807: Transactions in functions PostgreSQL doesn't support

Perform a manual conversion to correct this issue.

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PostgreSQL supports local transactions within a given client session. You must manually convert

Microsoft SQL Server transactions to use the PostgreSQL transaction management statements instead.

PostgreSQL doesn't support named or distributed transactions, marking transactions, or transaction management within functions. For more information about using transactions in PostgreSQL, see

TRANSACTIONS in the PostgreSQL documentation.

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Microsoft SQL Server to PostgreSQL Conversion Issue Reference (p. 188)

Conversion Issues with TRIGGERS

Issue 7809: In PostgreSQL there are no analogues of the tables 'inserted' and

'deleted'

PostgreSQL doesn't support the inserted or deleted virtual tables. To manually convert a trigger that uses these tables from Microsoft SQL Server to PostgreSQL, perform the following steps:

1. Create a trigger function. The trigger function must be declared as a function taking no arguments and returning type trigger. The returned value must be NEW, OLD or NULL, depending on the type of a trigger. The function’s body must be PostgreSQL-supported SQL to replace the body of the

Microsoft SQL Server trigger without using the virtual tables. The name of the function should be formed as

schema_name.fn_<%trigger_name%>()

2. Create a trigger with CREATE TRIGGER that executes the trigger function.

For example, consider the following Microsoft SQL Server trigger.

CREATE TRIGGER [dbo].[tr_customerStateExt_aiu]

ON [dbo].[CustomerStateExt]

AFTER INSERT, UPDATE

BEGIN

IF EXISTS (SELECT *

FROM inserted

WHERE LEN(Name) < 5)

BEGIN

RAISERROR ('The name must be longer than five characters.', 16, 1);

ROLLBACK TRANSACTION;

RETURN

END;

END

Using the approach described, this trigger is converted into the following PostgreSQL trigger.

CREATE OR REPLACE FUNCTION mydb_dbo.fn_tr_customerStateExt_aiu()

RETURNS trigger

$BODY$

BEGIN

END;

$BODY$

LANGUAGE plpgsql;

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CREATE TRIGGER tr_customerStateExt_aiu

AFTER INSERT OR UPDATE

ON mydb_dbo.CustomerStateExt

FOR EACH STATEMENT

EXECUTE PROCEDURE mydb_dbo.fn_tr_customerStateExt_aiu();

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Microsoft SQL Server to PostgreSQL Conversion Issue Reference (p. 188)

Conversion Issues with Unknown

Issue 7627: This syntactic element conversion is not supported yet

Perform a manual conversion.

Issue 7674: Automatic conversion of <clause name> clause of <statement name> statement is not supported

Perform a manual conversion to correct this issue.

A common cause of this issue is SET statements in Microsoft SQL Server that aﬀect current session handling (a complete list of these SET statements is available at SET Statements (Transact-SQL) ).

These statements are not supported in PostgreSQL, so you need to perform a manual conversion to a

PostgreSQL SET statement. For more information about using a SET statement in PostgreSQL, see SET in the PostgreSQL documentation.

Issue 7808: Unparsed SQL

Perform a manual conversion.

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Microsoft SQL Server to PostgreSQL Conversion Issue Reference (p. 188)

Conversion Issues with UPDATE

Issue 7796: PostgreSQL doesn't support TOP option in the operator UPDATE

Perform a manual conversion for any UPDATE statements that contain a TOP argument, as in the example following.

update top(10)

Account set

AccountBalance = AccountBalance - 1 where

AccountBalance > 15723

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; or: update top(5) percent

Account set

AccountBalance = AccountBalance - 1 where

AccountBalance > 15723

;

In PostgreSQL, you can use the row_number() window function in the FROM clause or a subquery in the

WHERE clause of the UPDATE statement to identify the rows you want to modify.

Issue 7797: PostgreSQL doesn't have analog for option "OUTPUT" with using the implicit table "deleted" in the operator for UPDATE

Perform a manual conversion for any UPDATE statements that uses the OUTPUT clause and references the deleted virtual table, as in the example following.

update Customer set

name = 'Mister ' + name output

deleted.id,

deleted.name,

inserted.id,

inserted.name

where

TypeID = 4

In PostgreSQL, use a subquery in the RETURNING clause to return the information about the deleted table. This approach requires the table to have a primary key ﬁeld.

update mydb_dbo.Customer c set

name = 'Mister ' || name where

TypeID = 4 returning

(select id from mydb_dbo.Customer where id = c.id)

,(select name from mydb_dbo.Customer where id = c.id)

,id

,name

If the primary key is composed of multiple ﬁelds, you must reference all of those ﬁelds in the subquery.

For example, take the following statement in SQL Server where id1 and id2 are the primary key ﬁelds for the TestMultiPK table.

UPDATE [TestMultiPK]

SET [Description] = 'Test' output

deleted.id1,

deleted.id2,

deleted.Description,

inserted.id1,

inserted.id2,

inserted.Description where ID = 0

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The PostgreSQL conversion is as follows.

UPDATE [TestMultiPK] t

SET [Description] = 'Test'

WHERE ID = 0 returning

select (id1 from TestMultiPK where id1 = t.id1 and id2 = t.id2)

, select (id2 from TestMultiPK where id1 = t.id1 and id2 = t.id2)

, select (Description from TestMultiPK where id1 = t.id1 and id2 = t.id2)

, id1

, id2

, Description

Issue 7829: Unable to convert variable assignment by UPDATE statement

Perform a manual conversion. This issue occurs when you use an UPDATE statement to change the value of a variable, as in the example following.

CREATE PROCEDURE [dbo].[PROC_DML_UPDATE_FROM_3]

BEGIN

DECLARE @AccountBalance FLOAT = 400;

UPDATE bank

SET @AccountBalance = 500

FROM bank

WHERE id = 50005;

END

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Microsoft SQL Server to PostgreSQL Conversion Issue Reference (p. 188)

Conversion Issues with User Types

Issue 7794: PostgreSQL doesn't support user-deﬁned data types

To correct this issue, perform a manual conversion of each sp_ addtype or CREATE TYPE statement in

Microsoft SQL Server to a CREATE TYPE statement in PostgreSQL. For more information about creating a user-deﬁned data type in PostgreSQL, see CREATE TYPE in the PostgreSQL documentation.

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Issue 8824: ALGORITHM option is not supported (p. 241)

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MySQL to PostgreSQL Supported Schema Conversion

MySQL to PostgreSQL Supported Schema

Conversion

The following sections list the schema elements from a MySQL database and whether they are supported for automatic conversion to PostgreSQL using the AWS Schema Conversion Tool.

DDL

Alter Statements

ALTER TABLE

Clause

ADD CONSTRAINT

ADD INDEX

Automatically

Converted

Details

Yes

Create Statements

CREATE INDEX

Clause

INDEX

UNIQUE index

Automatically

Converted

Details

Yes

CREATE PROCEDURE

Clause Automatically

Converted

Details

PARAMETERS: IN, OUT,

INOUT

With any output parameters

Yes

Without output parameters Yes

CREATE TABLE

Clause

Regular tables

Temporary tables

Automatically

Converted

Details

Yes

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DML

CREATE TRIGGER

Clause

FOR EACH ROW Triggers

Trigger event (Insert /

Update / Delete )

Trigger time (Before /

After)

Automatically

Converted

Details

Yes

CREATE VIEW

Clause Automatically

Converted

Details

With ALGORITHM OPTION Partial

With CHECK OPTION Yes

Naming Objects

Clause

Schemas

Tables, Columns

Automatically

Converted

Details

Yes

DML

Clauses

FROM

Clause

CROSS JOIN

INNER JOIN join_condition: ...ON

conditional_expr join_condition: … USING

(column_list)

LEFT JOIN

LEFT OUTER JOIN

Automatically

Converted

Details

Yes

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DML

Clause

NATURAL LEFT JOIN

NATURAL LEFT OUTER

JOIN

NATURAL RIGHT JOIN

NATURAL RIGHT OUTER

JOIN

RIGHT JOIN

RIGHT OUTER JOIN

STRAIGHT_JOIN

Subqueries in the FROM

Clause tables_list

Yes

Automatically

Converted

Details

Yes

Statements

DELETE

Clause

IGNORE

LIMIT

LOW_PRIORITY

Multiple-Table Syntax

Multiple-Table Syntax with

USING

ORDER BY

QUICK

Automatically

Converted

Details

Partial

Issue 8831: PostgreSQL doesn't have an option similar to

IGNORE for DML statements (p. 237)

Yes

Partial

Issue 8830: PostgreSQL doesn't have an option similar to

LOW_PRIORITY for DML statements (p. 237)

Issue 8834: PostgreSQL can't delete from several tables at the same time (p. 238)

Yes

Partial

Issue 8832: PostgreSQL doesn't have an option similar to

QUICK for DML statements (p. 237)

INSERT

Clause

IGNORE

Automatically

Converted

Details

Partial

Issue 8831: PostgreSQL doesn't have an option similar to

IGNORE for DML statements (p. 237)

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DML

Clause

LOW_PRIORITY | DELAYED |

HIGH_PRIORITY

ON DUPLICATE KEY

UPDATE

SELECT-statement for insert

SET col1=expr1,..

VALUES(,…,)|VALUE(,…,)

Automatically

Converted

Details

Partial

Issue 8830: PostgreSQL doesn't have an option similar to

LOW_PRIORITY for DML statements (p. 237)

Issue 8829: PostgreSQL doesn't have an analog of clause

ON DUPLICATE KEY UPDATE (p. 237)

Yes

SELECT

Clause

DISTINCT

GROUP BY ASC, DESC

GROUP BY col_name,…

GROUP BY expression

GROUP BY mixed options

GROUP BY position,…

GROUP BY WITH ROLLUP

HAVING

HIGH_PRIORITY

LIMIT oﬀset, row_count

LIMIT row_count OFFSET oﬀset

MAX_STATEMENT_TIME =

ORDER BY col_name,…

ORDER BY expression

ORDER BY mixed options

ORDER BY position,…

SQL_BIG_RESULT

Partial

Yes

Partial

Yes

Automatically

Converted

Details

Yes

Issue 8653: PostgreSQL doesn't support the option

GROUP BY ROLLUP (p. 240)

Yes

Partial

Issue 8836: PostgreSQL doesn't have an option similar to

Issue 8836: PostgreSQL doesn't have an option similar to

Yes

Issue 8836: PostgreSQL doesn't have an option similar to

Issue 8836: PostgreSQL doesn't have an option similar to

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DML

Clause

SQL_BUFFER_RESULT

SQL_CACHE

Automatically

Converted

Details

Partial

Issue 8836: PostgreSQL doesn't have an option similar to

Issue 8836: PostgreSQL doesn't have an option similar to

SQL_CALC_FOUND_ROWS Partial

SQL_NO_CACHE

SQL_SMALL_RESULT

Partial

Issue 8836: PostgreSQL doesn't have an option similar to

Issue 8836: PostgreSQL doesn't have an option similar to

Issue 8836: PostgreSQL doesn't have an option similar to

STRAIGHT_JOIN Partial

Issue 8831: PostgreSQL doesn't have an option similar to

Select all columns (using * and aliases)

Yes

Select all columns (using *) Yes

Select subset of the columns

Yes

Select with calculations Yes

Select with column heading Yes

Select with constants Yes

Subquery as scalar operand Yes

UPDATE

Clause

DEFAULT VALUES

IGNORE

LIMIT

LOW_PRIORITY

Multiple-table syntax

ORDER BY

Automatically

Converted

Details

Yes

Partial

IGNORE for DML statements (p. 237)

Yes

Partial

Issue 8830: PostgreSQL doesn't have an option similar to

LOW_PRIORITY for DML statements (p. 237)

Yes

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Functions

Aggregate

Clause

AVG()

BIT_AND()

BIT_OR()

BIT_XOR()

COUNT()

COUNT(DISTINCT)

GROUP_CONCAT()

MAX()

MIN()

STD()

STDDEV()

STDDEV_POP()

STDDEV_SAMP()

SUM()

VAR_POP()

VAR_SAMP()

VARIANCE()

Bit

Clause

BIT_COUNT()

Control Flow

Clause

CASE

Yes

Automatically

Converted

Details

Yes

Automatically

Converted

Details

Yes

Automatically

Converted

Details

Yes

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Clause

IF()

IFNULL()

NULLIF()

Conversion

Clause

BINARY

CAST()

CONVERT()

Date and Time

Clause

ADDDATE()

ADDTIME()

CONVERT_TZ()

CURDATE()

AWS Schema Conversion Tool User Guide

Functions

Automatically

Converted

Details

Yes

Automatically

Converted

Details

Yes

Automatically

Converted

Details

Yes

CURTIME()

DATE()

DATE_ADD()

DATE_FORMAT()

DATE_SUB()

DATEDIFF()

DAY()

DAYNAME()

DAYOFMONTH()

Yes

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MAKEDATE()

MAKETIME()

MICROSECOND()

MINUTE()

MONTH()

MONTHNAME()

NOW()

PERIOD_ADD()

PERIOD_DIFF()

QUARTER()

SEC_TO_TIME()

SECOND()

STR_TO_DATE()

SUBDATE()

SUBTIME()

SYSDATE()

TIME()

TIME_FORMAT()

TIME_TO_SEC()

TIMEDIFF()

AWS Schema Conversion Tool User Guide

Functions

Clause

DAYOFWEEK()

DAYOFYEAR()

EXTRACT()

FROM_DAYS()

FROM_UNIXTIME()

GET_FORMAT()

HOUR()

LAST_DAY

LOCALTIME(), LOCALTIME

Yes

Automatically

Converted

Details

Yes

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Functions

Clause

TIMESTAMP()

TIMESTAMPADD()

TIMESTAMPDIFF()

TO_DAYS()

TO_SECONDS()

UNIX_TIMESTAMP()

UTC_DATE()

UTC_TIME()

UTC_TIMESTAMP()

WEEK()

WEEKDAY()

WEEKOFYEAR()

YEAR()

YEARWEEK()

Yes

Automatically

Converted

Details

Yes

Encryption and Compression

Clause Automatically

Converted

Details

AES_DECRYPT()

AES_ENCRYPT()

COMPRESS()

DECODE() No

DES_DECRYPT() (deprecated

5.7.6)

DES_ENCRYPT() (deprecated

5.7.6)

ENCODE()

ENCRYPT() (deprecated

5.7.6)

MD5()

OLD_PASSWORD()

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Functions

Clause

PASSWORD() (deprecated

5.7.6)

RANDOM_BYTES()

SHA1(), SHA()

SHA2()

UNCOMPRESS()

UNCOMPRESSED_LENGTH() No

Automatically

Converted

Details

Information

Clause

BENCHMARK()

CHARSET()

COERCIBILITY()

COLLATION()

CONNECTION_ID()

DATABASE()

FOUND_ROWS()

LAST_INSERT_ID()

ROW_COUNT()

SCHEMA()

SESSION_USER()

SYSTEM_USER()

USER()

VERSION()

Automatically

Converted

Details

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Functions

Mathematical

Clause

ABS()

ACOS()

ASIN()

ATAN()

ATAN2()

CEIL()

CEILING()

CONV()

POW()

POWER()

RADIANS()

RAND()

ROUND(X)

SIGN()

SIN()

SQRT()

COS()

COT()

CRC32()

DEGREES()

EXP()

FLOOR()

LN()

LOG()

LOG10()

LOG2()

MOD()

PI()

Yes

Automatically

Converted

Details

Yes

Issue 8811: PostgreSQL doesn't support the %s function (p. 234)

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Clause

TAN()

TRUNCATE()

String

Clause

ASCII()

BIN()

BIT_LENGTH()

CHAR()

CHAR_LENGTH()

CHARACTER_LENGTH()

CONCAT()

CONCAT_WS()

ELT()

EXPORT_SET()

FIELD()

FIND_IN_SET()

FORMAT()

FROM_BASE64()

HEX()

INSERT()

INSTR()

LCASE()

LEFT()

LENGTH()

LOAD_FILE()

LOCATE()

AWS Schema Conversion Tool User Guide

Functions

Automatically

Converted

Details

Yes

Automatically

Converted

Details

Yes

Issue 8811: PostgreSQL doesn't support the %s function (p. 234)

Yes

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Clause

LOWER()

LPAD()

LTRIM()

MAKE_SET()

MATCH

MID()

NOT REGEXP

NOT RLIKE

OCT()

OCTET_LENGTH()

ORD()

POSITION()

QUOTE()

REGEXP

REPEAT()

REPLACE()

REVERSE()

RIGHT()

RLIKE

RPAD()

RTRIM()

SOUNDEX()

SOUNDS LIKE

SPACE()

STRCMP()

SUBSTR()

SUBSTRING()

SUBSTRING_INDEX()

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Functions

Yes

Automatically

Converted

Details

Yes

Issue 8811: PostgreSQL doesn't support the %s function (p. 234)

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Clause

TO_BASE64()

TRIM()

UCASE()

UNHEX()

UPPER()

WEIGHT_STRING()

AWS Schema Conversion Tool User Guide

Data Types

Yes

Automatically

Converted

Details

Issue 8811: PostgreSQL doesn't support the %s function (p. 234)

Yes

Issue 8811: PostgreSQL doesn't support the %s function (p. 234)

XML

Clause

ExtractValue()

UpdateXML()

Automatically

Converted

Details

Issue 8811: PostgreSQL doesn't support the %s function (p. 234)

Data Types

Date and Time

Data type

DATE

DATETIME

TIME

TIMESTAMP

YEAR

YEAR (M)

Automatically

Converted to

date

Details

timestamp without time zone time timestamp without time zone smallint smallint

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Data Types

JSON

Data type

JSON

Automatically

Converted to

Details

Issue 8706: PostgreSQL doesn't support %s type (p. 236)

Numeric

Integer Types

Data type

BIGINT [SIGNED]

BIGINT UNSIGNED

BOOL

BOOLEAN

INT [INTEGER] [SIGNED]

INT [INTEGER] UNSIGNED

MEDIUMINT [SIGNED]

MEDIUMINT UNSIGNED

SMALLINT [SIGNED]

SMALLINT UNSIGNED

TINYINT [SIGNED]

TINYINT UNSIGNED

Automatically

Converted to

Details

bigint numeric boolean boolean

Issue 8848: In MySQL the BOOLEAN type is a synonym for TINYINT (p. 236)

integer bigint integer integer smallint integer smallint smallint

Bit

Data type

BIT

Automatically

Converted to

Details

bit

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Data Types

Fixed-Point

Data type

DEC

DEC (p)

DEC (p,s)

DECIMAL

DECIMAL (p)

DECIMAL (p,s)

NUMERIC

NUMERIC (p)

NUMERIC (p,s)

Automatically

Converted to

Details

numeric numeric numeric numeric numeric numeric numeric numeric numeric

Floating-Point

Data type

DOUBLE

DOUBLE PRECISION

DOUBLE PRECISION (p)

DOUBLE PRECISION (p,s)

DOUBLE(p)

DOUBLE(p,s)

FLOAT

FLOAT(p)

FLOAT(p,s)

Automatically

Converted to

Details

double precision double precision double precision double precision double precision double precision real precision from 1-24: real precision >

24: double precision double precision

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Data Types

Data type

REAL

REAL(p)

REAL(p,s)

Spatial Data Types

Data type

GEOMETRY

GEOMETRYCOLLECTION

LINESTRING

MULTILINESTRING

MULTIPOINT

MULTIPOLYGON

POINT

POLYGON

Automatically

Converted to

Details

Issue 8706: PostgreSQL doesn't support %s type (p. 236)

String

Automatically

Converted to

Details

double precision double precision double precision

Data type

BINARY

BLOB

Automatically

Converted to

Details

bytea bytea

Issue 8706: PostgreSQL doesn't support %s type (p. 236)

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MySQL to PostgreSQL Conversion Reference

LONGBLOB

LONGTEXT

MEDIUMBLOB

MEDIUMTEXT

SET

TEXT

TINYBLOB

TINYTEXT

VARBINARY(len)

VARCHAR(len)

Data type

CHAR

CHAR(len)

ENUM

Automatically

Converted to

Details

char char

CREATE

ENUM user type bytea

Issue 8706: PostgreSQL doesn't support %s type (p. 236)

text bytea

Issue 8706: PostgreSQL doesn't support %s type (p. 236)

text

Issue 8706: PostgreSQL doesn't support %s type (p. 236)

text bytea

Issue 8706: PostgreSQL doesn't support %s type (p. 236)

text bytea

Issue 8706: PostgreSQL doesn't support %s type (p. 236)

varchar

MySQL to PostgreSQL Conversion Reference

BUILT-IN SQL FUNCTIONS

Item

Function

Issue

Issue 8811: PostgreSQL doesn't support the

%s function (p. 234)

Issue 8849: PostgreSQL doesn't support the %s function with parameter values

%s (p. 234)

Issue 8850: Some parameter values for the function %s aren't supported (p. 234)

Issue 8851: PostgreSQL doesn't support using aggregate functions in the SELECT list without a GROUP BY clause (p. 234)

Resolution

Create a user-deﬁned function.

You need to check the result of the conversion

Perform a manual conversion.

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Item

Function

Issue

Issue 8854: PostgreSQL doesn't support the

%s function with parameters (p. 234)

Resolution

Perform a manual conversion.

CONTROL FLOW

Item

CURSORS

DECLARE / DEFAULT

VALUE

DECLARE / DEFAULT

VALUE error handling error handling error handling

LABEL

PROCESS_LIST

REPLICATION

SLEEP

Issue

Issue 8845: Rows count functionality is not supported behind the "open cursor" statement (p. 234)

Issue 8826: Check the default value for a Date or DateTime variable (p. 234)

Issue 8828: User-deﬁned variables are not supported in PostgreSQL (p. 235)

Issue 8844: Error codes are not the same (p. 235)

Issue 8846: PostgreSQL doesn't support the statement option %s (p. 235)

Issue 8847: PostgreSQL isn't able to return to a call point after error handling (p. 235)

Issue 8827: Statement Label Syntax for

BEGIN...END blocks is not supported in

PostgreSQL (p. 235)

Issue 8856: The information of the server processes is diﬀerent on diﬀerent servers (p. 236)

Issue 8857: Automatic conversion for replication commands is not supported (p. 236)

Issue 8853: Perform a manual conversion if using SLEEP() with other expressions (p. 236)

Resolution

Perform a manual conversion.

Review generated code and modify it if necessary.

Perform a manual conversion.

You need to check the result of the conversion

Perform a manual conversion.

Check your conversion result.

Perform a manual conversion.

CREATE

Item Issue

Issue 8654: Unable to convert object due to

%s not created (p. 236)

Resolution

Review the %s object.

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DATATYPES

Item

BOOLEAN

DATATYPES

Issue

Issue 8848: In MySQL the BOOLEAN type is a synonym for TINYINT (p. 236)

Issue 8706: PostgreSQL doesn't support %s type (p. 236)

Resolution

Check it when you insert data from a BOOLEAN variables into the database.

To store data of this type in PostgreSQL, use a

PostgreSQL-compatible type or use a composite type.

DDL

Item

CREATE TABLE

DROP TABLE

Issue

Issue 8825: Check the default value for a Date or DateTime column (p. 236)

Issue 8801: The table can be locked open cursor (p. 237)

Resolution

Review generated code and modify it if necessary.

Review your transformed code and modify it if necessary.

DML

Item

DML

SELECT

Issue

Issue 8829: PostgreSQL doesn't have an analog of clause ON DUPLICATE KEY

UPDATE (p. 237)

Issue 8830: PostgreSQL doesn't have an option similar to LOW_PRIORITY for DML statements (p. 237)

Issue 8831: PostgreSQL doesn't have an option similar to IGNORE for DML statements (p. 237)

Issue 8832: PostgreSQL doesn't have an option similar to QUICK for DML statements (p. 237)

Issue 8833: PostgreSQL can't make updates to several tables at the same time (p. 238)

Issue 8834: PostgreSQL can't delete from several tables at the same time (p. 238)

Issue 8835: PostgreSQL doesn't have an option similar to DELAYED for DML statements (p. 238)

Resolution

Perform a manual conversion.

Use DML statement without this option.

Perform a manual conversion.

Use DML statement without this option.

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SELECT

WHERE

Item

SELECT

Issue

Issue 8836: PostgreSQL doesn't have an option similar to %s for DML statements (p. 238)

Issue 8837: PostgreSQL doesn't support clause STRAIGHT_JOIN (p. 238)

Issue 8838: PostgreSQL doesn't support clause SQL_SMALL_RESULT (p. 238)

Issue 8839: PostgreSQL doesn't support clause SQL_BIG_RESULT (p. 238)

Issue 8840: PostgreSQL doesn't support clause SQL_BUFFER_RESULT (p. 238)

Issue 8841: PostgreSQL doesn't support clause SQL_CACHE (p. 238)

Issue 8842: PostgreSQL doesn't support clause SQL_NO_CACHE (p. 238)

Issue 8843: PostgreSQL doesn't support clause SQL_CALC_FOUND_ROWS (p. 238)

Issue 8795: PostgreSQL is case sensitive.

Check the string comparison. (p. 238)

Resolution

Use DML statement without this option.

Use DML statement without this option

Check the string comparison.

EVENTS

Item

EVENTS

Issue

Issue 8855: Automatic conversion of EVENT syntax is not supported (p. 239)

Resolution

Perform a manual conversion.

EXECUTE

Item

EXECUTE a character string

Issue

Issue 8672: Automatic conversion of this command is not supported (p. 239)

Resolution

Perform a manual conversion.

Operators

Item Issue

Arithmetic operators

Issue 8773: The tool can not currently perform automated migration of arithmetic operations with dates (p. 239)

Resolution

Perform a manual conversion.

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Item Issue

Arithmetic operators

Issue 8774: The tool can not currently perform automated migration of arithmetic operations with mixed types of operands (p. 239)

Parser Error

Item

Parser Error

Issue

Issue 8663: Unable to resolve the object (p. 239)

Resolution

Perform a manual conversion.

Resolution

Verify if object %s is present in the database. If it isn't, check the object name or add the object. If the object is present, transform the code manually.

SELECT

Item

GROUP BY

Issue

Issue 8653: PostgreSQL doesn't support the option GROUP BY ROLLUP (p. 240)

Resolution

Perform a manual conversion.

TRANSACTION

Item

TRANSACTION

Issue

Issue 8807: PostgreSQL doesn't support transactions in functions (p. 240)

Unknown

Item

Unknown Clause

Resolution

Perform a manual conversion.

Issue

Issue 8655: This syntactic element conversion is not supported yet (p. 240)

Issue 8674: Automatic conversion of %s clause of %s statement is not supported (p. 240)

Resolution

Perform a manual conversion.

VIEW

Item

CREATE VIEV

Issue

Issue 8824: ALGORITHM option is not supported (p. 241)

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Resolution

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Conversion Issues with BUILT-IN SQL FUNCTIONS

Issue 8811: PostgreSQL doesn't support the %s function

Create a user-deﬁned function.

Issue 8849: PostgreSQL doesn't support the %s function with parameter values

Create a user-deﬁned function.

Issue 8850: Some parameter values for the function %s aren't supported

Review the transformed code, and correct it if necessary.

Issue 8851: PostgreSQL doesn't support using aggregate functions in the

SELECT list without a GROUP BY clause

In MySQL, it is possible to use an aggregate function on a field in the SELECT list without adding the other fields in the SELECT list to a GROUP BY clause. In PostgreSQL, adding these fields to a GROUP BY clause is required. Perform a manual conversion in this case.

Issue 8854: PostgreSQL doesn't support the %s function with parameters

Perform a manual conversion.

Related Topics

•

•

•

Conversion Issues with CONTROL FLOW

Issue 8845: Rows count functionality is not supported behind the "open cursor" statement

In PostgreSQL, the FOUND_ROWS() function can't be called within a cursor. Perform a manual conversion instead.

Issue 8826: Check the default value for a Date or DateTime variable

When converting default values for Date, Time, or DateTime variables, they are explicitly cast to the data type of the target variable. For example, the following MySQL code:

DECLARE ValueDate1 DATE DEFAULT '2000-01-01';

Is converted to the following PostgreSQL code:

ValueDate1 DATE DEFAULT '2000-01-01'::DATE;

If the default value is of the form '0000-00-00' or similar ('0000-00-00', '0000-00-00 00:00:00',

'0000-00-00 00:00:00.000000'), it is converted to the literal 'epoch'. For example, the following MySQL code:

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DECLARE ValueDate2 DATE DEFAULT '0000-00-00';

Is converted to the following PostgreSQL code:

ValueDate2 DATE DEFAULT 'epoch'::DATE;

In these cases, the default value must be manually updated. Review the generated code and modify it if necessary.

Issue 8828: User-deﬁned variables are not supported in PostgreSQL

Perform a manual conversion.

Issue 8844: Error codes are not the same

Some exit handler conditions require manual conversion. MySQL code with any of the following exit handler statements must be converted to use PostgreSQL error handling with OTHERS or SQLSTATE conditions instead:

DECLARE EXIT HANDLER FOR SQLWARNING, SQLEXCEPTION, NOT FOUND

DECLARE EXIT HANDLER FOR SQLWARNING

DECLARE EXIT HANDLER FOR SQLEXCEPTION

DECLARE EXIT HANDLER FOR NOT FOUND

DECLARE EXIT HANDLER FOR SQLWARNING, NOT FOUND

DECLARE EXIT HANDLER FOR <mysql_error_code>

DECLARE EXIT HANDLER FOR SQLSTATE <sqlstate_value>

Review the transformed code, and correct it if necessary.

Issue 8846: PostgreSQL doesn't support the statement option %s

Some of the condition information items that are used with the DECLARE CONDITION and GET

DIAGNOSTICS CONDITION statements in MySQL are not supported by PostgreSQL. These include:

• CLASS_ORIGIN

• SUBCLASS_ORIGIN

• MYSQL_ERRNO

• CONSTRAINT_CATALOG

• CONSTRAINT_SCHEMA

• CATALOG_NAME

• CURSOR_NAME

Manually convert the code wherever you use these condition information items.

Issue 8847: PostgreSQL isn't able to return to a call point after error handling

If an error occurs in a BEGIN...END block, PostgreSQL exits the block without executing any further statements in that block. Check your error handling logic and perform a manual conversion instead.

Issue 8827: Statement Label Syntax for BEGIN...END blocks is not supported in

PostgreSQL

Perform a manual conversion.

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Check your conversion result.

Issue 8857: Automatic conversion for replication commands is not supported

Perform a manual conversion for all replication-related code.

Issue 8853: Perform a manual conversion if using SLEEP() with other expressions

If you are using SLEEP() in a SELECT statement along with other expressions, for example

SELECT NOW(),

SLEEP(2), AccountNo FROM Account

, you must manually convert that code.

Related Topics

•

•

•

Conversion Issues with CREATE

Issue 8654: Unable to convert object due to %s not created

Review the %s object.

Related Topics

•

•

•

Conversion Issues with DATATYPES

Issue 8848: In MySQL the BOOLEAN type is a synonym for TINYINT

Check your code wherever you insert data from a BOOLEAN variable into the database.

Issue 8706: PostgreSQL doesn't support %s type

To store data of this type in PostgreSQL, use a PostgreSQL-compatible type or use a composite type.

Related Topics

•

•

•

Conversion Issues with DDL

Issue 8825: Check the default value for a Date or DateTime column

When converting default values for Date, Time, or DateTime variables, they are explicitly cast to the data type of the target variable. For example, the following MySQL code:

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DECLARE ValueDate1 DATE DEFAULT '2000-01-01';

Is converted to the following PostgreSQL code:

ValueDate1 DATE DEFAULT '2000-01-01'::DATE;

If the default value is of the form '0000-00-00' or similar ('0000-00-00', '0000-00-00 00:00:00',

'0000-00-00 00:00:00.000000'), it is converted to the literal 'epoch'. For example, the following MySQL code:

DECLARE ValueDate2 DATE DEFAULT '0000-00-00';

Is converted to the following PostgreSQL code:

ValueDate2 DATE DEFAULT 'epoch'::DATE;

In these cases, the default value must be manually updated. Review the generated code and modify it if necessary.

Issue 8801: The table can be locked open cursor

The conversion uses the DROP TABLE IF EXISTS statement to remove a temporary table before the end of the function in which it was created. In some cases though, this statement might fail because the temporary table is locked due to an open cursor. In this case, the DROP TABLE statement must be commented out. Review your transformed code and modify it if necessary.

Related Topics

•

•

•

Conversion Issues with DML

Issue 8829: PostgreSQL doesn't have an analog of clause ON DUPLICATE KEY

UPDATE

Perform a manual conversion.

Issue 8830: PostgreSQL doesn't have an option similar to LOW_PRIORITY for

DML statements

Use the DML statement without this option.

Issue 8831: PostgreSQL doesn't have an option similar to IGNORE for DML statements

Use the DML statement without this option.

Issue 8832: PostgreSQL doesn't have an option similar to QUICK for DML statements

Use the DML statement without this option.

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Issue 8833: PostgreSQL can't make updates to several tables at the same time

PostgreSQL doesn't support using an UPDATE statement to update several tables at once, for example update Account, Customer set Account.AccountBalance = Account.AccountBalance + 100,

Customer.SName = 'Sofan Hubert'

. Perform a manual conversion in this case.

Issue 8834: PostgreSQL can't delete from several tables at the same time

PostgreSQL doesn't support using a DELETE statement to delete several tables at once, for example delete table1, table3

. Perform a manual conversion in this case.

Issue 8835: PostgreSQL doesn't have an option similar to DELAYED for DML statements

Use the DML statement without this option.

Issue 8836: PostgreSQL doesn't have an option similar to %s for DML statements

Use the DML statement without this option.

Issue 8837: PostgreSQL doesn't support clause STRAIGHT_JOIN

Use the DML statement without this option

Issue 8838: PostgreSQL doesn't support clause SQL_SMALL_RESULT

Use the DML statement without this option

Issue 8839: PostgreSQL doesn't support clause SQL_BIG_RESULT

Use the DML statement without this option

Issue 8840: PostgreSQL doesn't support clause SQL_BUFFER_RESULT

Use the DML statement without this option

Issue 8841: PostgreSQL doesn't support clause SQL_CACHE

Use the DML statement without this option

Issue 8842: PostgreSQL doesn't support clause SQL_NO_CACHE

Use the DML statement without this option

Issue 8843: PostgreSQL doesn't support clause SQL_CALC_FOUND_ROWS

Use the DML statement without this option

Issue 8795: PostgreSQL is case sensitive. Check the string comparison.

Check string comparisons in the WHERE clauses of statements, for example

WHERE [Name] LIKE

'%BLOCKED%';

. All strings used in comparisons must be lowercase.

Related Topics

•

•

•

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Conversion Issues with EVENTS

Issue 8855: Automatic conversion of EVENT syntax is not supported

Event-related statements like CREATE EVENT or DROP EVENT are not supported in PostgreSQL. Perform a manual conversion of this code.

Related Topics

•

•

•

Conversion Issues with EXECUTE

Issue 8672: Automatic conversion of this command is not supported

Code that uses the PREPARE...EXECUTE...DEALLOCATE PREPARE statements can't be automatically converted. Perform a manual conversion instead.

Related Topics

•

•

•

Conversion Issues with Operators

Issue 8773: The tool can not currently perform automated migration of arithmetic operations with dates

Perform a manual conversion.

Issue 8774: The tool can not currently perform automated migration of arithmetic operations with mixed types of operands

Code that uses an arithmetic operator and has one operand that has a DATE, TIME or TIMESTAMP data type can't be automatically converted. For example, set d = now() + 1;

. Perform a manual conversion instead.

Related Topics

•

•

•

Conversion Issues with Parser Error

Issue 8663: Unable to resolve the object

Verify if object %s is present in the database. If it isn't, check the object name or add the object. If the object is present, transform the code manually.

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Related Topics

•

•

•

Conversion Issues with SELECT

Issue 8653: PostgreSQL doesn't support the option GROUP BY ROLLUP

PostgreSQL doesn't support the GROUP BY <ﬁeld_name> WITH ROLLUP clause for the SELECT statement. Perform a manual conversion of this code.

Related Topics

•

•

•

Conversion Issues with TRANSACTION

Issue 8807: PostgreSQL doesn't support transactions in functions

Code that uses transaction management statements such as START TRANSACTION or COMMIT within a function or stored procedure can't be automatically converted. Perform a manual conversion instead.

Related Topics

•

•

•

Conversion Issues with Unknown

Issue 8655: This syntactic element conversion is not supported yet

Perform a manual conversion.

Issue 8674: Automatic conversion of %s clause of %s statement is not supported

This error is typically raised by code that sets transaction options or replication-related variables that aren't supported in PostgreSQL. Such code must be manually converted. Statements that raise this error include the following:

• SET TRANSACTION ISOLATION LEVEL SERIALIZABLE;

• SET TRANSACTION READ ONLY;

• SET SESSION TRANSACTION READ WRITE;

• SET SESSION TRANSACTION ISOLATION LEVEL REPEATABLE READ;

• SET TRANSACTION ISOLATION LEVEL READ COMMITTED;

• SET TRANSACTION ISOLATION LEVEL READ UNCOMMITTED;

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• SET GLOBAL TRANSACTION READ WRITE;

• SET GLOBAL tx_isolation=<isolation_level>;

• SET SQL_LOG_BIN=<value>;

• SET GLOBAL sql_slave_skip_counter=<value>;

Related Topics

•

•

•

Conversion Issues with VIEW

Issue 8824: ALGORITHM option is not supported

PostgreSQL doesn't support the ALGORITHM clause for the CREATE VIEW or ALTER VIEW statements.

Perform a manual conversion in this case.

Related Topics

•

•

•

Related Topics

•

•

Data Deﬁnition Language (DDL) (p. 262)

Oracle to MySQL Supported Schema Conversion

The following sections list the schema elements from an Oracle database and whether they are supported for automatic conversion to MySQL using the AWS Schema Conversion Tool.

Topics

•

Statements (p. 242)

•

Procedures (p. 246)

•

Flow Control (p. 246)

•

•

•

•

•

•

Cursors (p. 266)

•

Hints (p. 266)

•

Exceptions (p. 269)

•

Procedures

Item

LOCK TABLE dbms_output.put_line

dbms_output.put

Automatically

Converted

Details

Automatically

Converted

Details

MySQL doesn't support the LOCK TABLE statement inside a stored procedure.

Try using INSERT in the log table. To do this, you must add code into AWS_ORACLE_EXT.PUT_LINE.

Try using INSERT in the log table. To do this, you must add code into AWS_ORACLE_EXT.PUT.

Flow Control

Clause

GOTO

FORALL

EXECUTE IMMEDIATE

BULK COLLECT

Automatically

Converted

Details

Try using a WHILE DO statement.

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Packages

Clause

RETURNING BULK COLLECT

INTO

LABEL No

Automatically

Converted

Details

Try rewriting variables without using labels.

Packages

Item

Initialization block, BEGIN

… END

User type

Global cursor

Global user exception

Automatically

Converted

Details

Partial MySQL doesn't support EXCEPTION BLOCK in initialization blocks in packages. Try using CONTINUE

HANDLER.

Functions

Topics

•

Aggregate Functions (p. 248)

•

Date and Time Functions (p. 249)

•

Mathematical Functions (p. 250)

•

Character (String) Functions (p. 251)

•

Conversion Functions (p. 253)

•

General Comparison Functions (p. 254)

•

Encoding and Decoding Functions (p. 254)

•

Email (p. 255)

•

HTTP (p. 255)

•

SMS (p. 255)

•

NULL Functions (p. 255)

•

User-Deﬁned Functions (p. 255)

•

Large Object Functions (p. 256)

•

Hierarchical Functions (p. 256)

•

Analytic Functions (p. 257)

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Functions

AVG

COLLECT

CORR

CORR_*

COUNT

COVAR_POP

COVAR_SAMP

CUME_DIST

DENSE_RANK

FIRST

GROUP_ID

GROUPING

GROUPING_ID

LAST

MAX

MEDIAN

MIN

PERCENTILE_CONT

PERCENTILE_DISC

PERCENT_RANK

RANK

REGR_ (Linear Regression)

Functions

STATS_BINOMIAL_TEST

STATS_CROSSTAB

STATS_F_TEST

STATS_KS_TEST

STATS_MODE

STATS_MW_TEST

STATS_ONE_WAY_ANOVA

Aggregate Functions

Function

Yes

Automatically

Converted

Details

Yes

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Functions

Function

STATS_T_TEST_*

STATS_WSR_TEST

STDDEV

STDDEV_POP

STDDEV_SAMP

SUM

TRUNC

VAR_POP

VAR_SAMP

VARIANCE

Yes

Automatically

Converted

Details

Yes

Converts to: TRUNCATE()

Date and Time Functions

Function Automatically

Converted

Details

ADD_MONTHS(date, num) Partial

CURRENT_DATE Partial

CURRENT_TIMESTAMP Partial

Converts to: TIMESTAMPADD(MONTH, num, date)

Converts to: NOW()

DBTIMEZONE No

EXTRACT(YEAR FROM date) Partial

EXTRACT(MONTH FROM date)

Partial

EXTRACT(DAY FROM date) Partial

Partial EXTRACT(HOUR FROM time)

EXTRACT(MINUTE FROM time)

EXTRACT(SECOND FROM time)

FROM_TZ

LAST_DAY(date)

LOCALTIMESTAMP

Partial

Yes

Converts to: YEAR(date)

Converts to: MONTH(date)

Converts to: DAY(date)

Converts to: HOUR(time)

Converts to: MINUTE(time)

Converts to: SECOND(time)

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Functions

Function

LOCALTIMESTAMP(prec)

MONTHS_BETWEEN(date1, date2)

NEW_TIME

NEXT_DAY

NUMTODSINTERVAL

NUMTOYMINTERVAL

ROUND (date)

SESSIONTIMEZONE

SYS_EXTRACT_UTC

SYSDATE

SYSTIMESTAMP

TO_CHAR (datetime, format)

Automatically

Converted

Details

Partial The maximum precision for the MySQL

LOCALTIMESTAMP function is 6. If you need greater precision, create a user-deﬁned function.

Partial

Converts to: SYSDATE()

Converts to: CURRENT_TIMESTAMP

Converts to: DATE_FORMAT()

Note that the TO_CHAR and DATE_FORMAT format strings are diﬀerent.

TO_TIMESTAMP(exp)

TO_TIMESTAMP_TZ

TO_DSINTERVAL

TO_YMINTERVAL

TRUNC (datetime)

TZ_OFFSET

Partial

Converts to: DATE(datetime)

Mathematical Functions

Function

ABS(num)

ACOS(num)

ASIN(num)

ATAN(num)

ATAN2(x,y)

Automatically

Converted

Details

Yes

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Functions

Function

BITAND(exp1, exp2)

CEIL(num)

COS(num)

COSH(num)

EXP(n)

FLOOR(num)

LN(num)

LOG(num1, num2)

MOD(dividend, divisor)

NANVL(n2, n1)

POWER(value, n)

REMAINDER(n1, n2)

ROUND (num, integer)

SIGN(exp)

SIN(num)

SINH(num)

SQRT(num)

TAN(num)

TANH(num)

TRUNC (number)

TRUNC(num, num2)

VALUE(variable)

WIDTH_BUCKET

Yes

Partial

Yes

Partial

Yes

Automatically

Converted

Details

Partial Converts to: (exp1 & exp2)

Yes

Partial Converts to: (EXP(num) + EXP(-num)) / 2

Converts to: (n1 - n2*ROUND(n1/n2))

Converts to: TRUNCATE(num, 0)

Character (String) Functions

Function

ASCII(str)

CHR(num)

CONCAT(char1, char2)

INITCAP(string)

Automatically

Converted

Details

Yes

Partial

Yes

Converts to: CHAR(num USING ASCII)

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Functions

NLS_INITCAP

NLS_LOWER

NLS_UPPER

NLSSORT

REGEXP_INSTR

REGEXP_REPLACE

REGEXP_SUBSTR

REPLACE(str, search)

REPLACE(str, search, replace)

RPAD(string, len)

RPAD(string, len, pad)

RTRIM(string)

RTRIM(string, set)

SOUNDEX(string)

SUBSTR(string, pos, len)

TRANSLATE(string, from, to)

TREAT

TRIM([type trim FROM] string)

Function

INSTR(str, substr)

INSTR(str, substr, pos)

INSTR(str, substr, pos, num) No

LENGTH(string) Partial

LOWER(string)

LPAD(string, len)

Yes

Partial

LPAD(string, len, pad)

LTRIM(string)

LTRIM(string, set)

Yes

Partial

Automatically

Converted

Details

Yes

Partial Converts to: LOCATE (substr, str, pos)

This function is the same as the two-argument form of INSTR(), except that the order of the arguments is reversed.

Converts to: LENGTH (string)

Converts to: LPAD(string, len, ' ')

Converts to: TRIM(LEADING set FROM string)

Partial

Yes

Converts to: REPLACE(str, search, '')

Partial

Yes

Partial

Yes

Converts to: RPAD(string, len, ' ')

Converts to: TRIM(TRAILING set FROM string)

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Functions

Function

UPPER(string)

Automatically

Converted

Details

Yes

Conversion Functions

Function

ASCIISTR(string)

Automatically

Converted

Details

BIN_TO_NUM(bit1, bit2, …) No

CAST Yes

CHARTOROWID No

COMPOSE

CONVERT(string, charset)

DECOMPOSE

HEXTORAW

NUMTODSINTERVAL

NUMTOYMINTERVAL

RAWTOHEX

Partial

Converts to: CONVERT(string USING charset)

RAWTONHEX

ROWIDTOCHAR

ROWIDTONCHAR

SCN_TO_TIMESTAMP

TIMESTAMP_TO_SCN

TO_BINARY_DOUBLE

TO_BINARY_FLOAT

TO_CHAR (character)

TO_CHAR (datetime, format)

Partial

TO_CHAR (number, format) Partial

Converts to: DATE_FORMAT(datetime, format)

Note that the TO_CHAR and DATE_FORMAT format strings are diﬀerent.

Converts to: FORMAT(number, decimal_digits)

In MySQL, you can use FORMAT function as well as other string functions and expressions.

TO_CLOB

TO_DATE

Partial

Partial Converts to: STR_TO_DATE(string, format)

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Functions

Function

TO_DSINTERVAL

TO_LOB

TO_MULTI_BYTE

TO_NCHAR (character)

TO_NCHAR (datetime)

TO_NCHAR (number)

TO_NCLOB

TO_NUMBER

TO_DSINTERVAL

TO_SINGLE_BYTE

TO_TIMESTAMP

TO_TIMESTAMP_TZ

TO_YMINTERVAL

TRANSLATE ... USING

UNISTR

Automatically

Converted

Details

Note that the TO_DATE and STR_TO_DATE format strings are diﬀerent.

Partial Converts to: CHAR(string USING UCS2)

General Comparison Functions

Function

GREATEST(exp, exp2, …)

LEAST(exp, exp2, …)

Automatically

Converted

Details

Yes

Encoding and Decoding Functions

Function Automatically

Converted

Details

Partial Converts to: CASE expression DECODE(exp, when, then, ...)

DUMP

ORA_HASH

VSIZE

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Functions

MySQL doesn’t support sending e-mail. To send email, use Amazon Simple Email Service (Amazon SES).

HTTP

MySQL doesn't support sending messages to HTTP endpoints. To send messages to HTTP and HTTPS endpoints, you can use the Amazon Simple Notiﬁcation Service (Amazon SNS).

SMS

MySQL doesn't support sending notifications by using SMS. To send and receive SMS notifications, you can use the Amazon Simple Notification Service (Amazon SNS).

NULL Functions

Function

COALESCE(exp1, exp2, …)

LNNVL

NULLIF(exp1, exp2)

NVL(exp, replacement)

NVL2(exp1, exp2, exp3)

Automatically

Converted

Details

Yes

Partial

Converts to: NULLIF(exp1, exp2)

Converts to: IFNULL(exp, replacement)

Converts to: CASE expression

User-Deﬁned Functions

Return

In MySQL, you can use statements that return a result set within a stored procedure but not within a stored function.

Statement

RETURN resultset

RETURN record-type

TYPE .. IS TABLE OF ..

INDEX BY

TYPE .. IS TABLE OF

TYPE .. IS VARRAY(..) OF

RETURN .. PIPELINED

Automatically

Converted

Details

No Try changing the function to a stored procedure and use a table to store the results.

Try changing the function to a stored procedure and change record-type items to separate parameters.

Try changing the function to a stored procedure and use a table to store the results.

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Functions

Statement

TYPE ... IS REF CURSOR object-type

Collections

Item

TYPE .. IS TABLE OF… collection_name.First, collection_name.Last, collection_name.Count, collection_name.Next

:= collection_type(...)

Automatically

Converted

Details

No Try changing the function to a stored procedure and use a table to store the results.

Automatically

Converted

Details

MySQL doesn't support table type variables. Try using a table.

MySQL doesn't support table type collection methods.

Try using a table.

No MySQL doesn't support the constructor for the collection type. Try using a table.

Arguments

Item

UDT record-type

UDT collection-type

UDT object-type

Automatically

Converted

Details

Large Object Functions

Function

BFILENAME

EMPTY_BLOB

EMPTY_CLOB

Automatically

Converted

Details

Partial

Converts to an empty string.

Hierarchical Functions

Function

SYS_CONNECT_BY_PATH

Automatically

Converted

Details

No Try creating a user-deﬁned function.

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Operators

Analytic Functions

MySQL doesn't support analytic functions. Try creating a user-deﬁned function.

Operators

Topics

•

Arithmetic Operators (p. 257)

•

Assignment Operator (p. 257)

•

Comparison Operators (p. 257)

•

Logical Operators (p. 258)

•

String Concatenation Operator (p. 258)

•

Date and time format speciﬁers (p. 258)

Arithmetic Operators

Clause

+ -

* /

Automatically

Converted

Details

Yes

Partial MySQL handles date and time arithmetic diﬀerently.

Verify that the converted schema is accurate.

Yes

Assignment Operator

Clause

Automatically

Converted

Details

Yes

Comparison Operators

Clause

Yes

Automatically

Converted

Details

Yes

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Operators

Clause

Automatically

Converted

Details

Yes

NOT IN

ANY

SOME

ALL

BETWEEN x

EXISTS

IS NULL

NOT

AND

Logical Operators

Clause

Yes

Automatically

Converted

Details

Yes

String Concatenation Operator

Clause

Automatically

Converted

Details

Yes

YEAR

YYYY

YYY

Date and time format speciﬁers

Clause Automatically

Converted

Default Conversion

Partial

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Operators

Clause

HH24

SSSSS

AM, PM

A.M., P.M.

AD or A.D

IYY

IYYY

RRRR

MON

MONTH

DAY

DDD

HH12

Day of the week (1=Sunday,

7=Saturday)

Partial

Automatically

Converted

Default Conversion

%y Partial

Partial %Y

Partial

Day of the week (0=Sunday, 6=Saturday)

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Clause

BC or B.C.

TZD

TZH

TZM

TZR

Data Types

Data type

BFILE

AWS Schema Conversion Tool User Guide

Data Types

Automatically

Converted

Default Conversion

Automatically

Converted

Default Conversion

Partial VARCHAR(255)

BINARY_FLOAT

BINARY_DOUBLE

BLOB

CHAR

CHAR(n), CHARACTER(n)

CLOB

DATE

DECIMAL, DEC

DECIMAL(p,s), DEC(p,s)

DOUBLE PRECISION

FLOAT

FLOAT(p)

INTEGER, INT

Yes

INTERVAL YEAR TO MONTH Yes

Yes

FLOAT

DOUBLE

LONGBLOB

TEXT

CHAR(n), CHARACTER(n)

VARCHAR(n)

LONGTEXT

DATETIME

DOUBLE

DECIMAL(p,s), DEC(p,s)

DOUBLE PRECISION

DOUBLE

DECIMAL(38)

DOUBLE

Details

Contains the ﬁle path to the BFILE. MySQL does not support the BFILE. Because

BFILE data is made up of the path to a file, you can either store a filename and create a routine that gets the file from the file system, or store the file contents as a LONGBLOB.

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Data Types

Data type Automatically

Converted

Default Conversion

VARCHAR(30) INTERVAL YEAR(p) TO

MONTH

Yes

INTERVAL DAY TO SECOND Yes VARCHAR(30)

INTERVAL DAY(p) TO

SECOND(s)

LONG

Yes

VARCHAR(30)

LONGTEXT

LONG RAW

NCHAR

NCHAR(n)

NCHAR VARYING

NCHAR VARYING(n)

Yes

LONGBLOB

TEXT

NCHAR(n)

NVARCHAR(n)

TEXT

NCHAR VARYING(n)

NCLOB

NUMBER(p,0), NUMBER(p) Yes

NUMBER(p,s)

NUMBER,

NUMBER(*),NUMERIC

NUMERIC(p,s)

NVARCHAR2

NVARCHAR2(n)

RAW

RAW(n)

REAL

ROWID

SMALLINT

TIMESTAMP

TIMESTAMP(p)

Yes

Partial

LONGTEXT

DECIMAL(p,0), DECIMAL(p)

DECIMAL(p,s)

DOUBLE

NUMERIC(p,s)

TEXT

NVARCHAR(n)

VARBINARY(2000)

BINARY(n)

VARBINARY(n)

DOUBLE

CHAR(10)

DECIMAL(38)

DATETIME

DATETIME(p)

Details

MySQL expands fractional seconds support for

TIME, DATETIME, and

TIMESTAMP values, with up to microseconds (6 digits) precision.

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Data Deﬁnition Language (DDL)

Data type

TIMESTAMP(p) WITH TIME

ZONE

Automatically

Converted

Default Conversion

Partial DATETIME

Details

There is not a data type in MySQL that can store time zone information.

DATETIME data type stores timestamps in the MySQL server time zone.

UROWID

UROWID(n)

VARCHAR

VARCHAR(n)

VARCHAR2

VARCHAR2(n)

XMLTYPE

Yes

TEXT

VARCHAR(n)

TEXT

VARCHAR(n)

TEXT

VARCHAR(n)

LONGTEXT

Data Deﬁnition Language (DDL)

Topics

•

CREATE TABLE (p. 262)

•

CREATE INDEX (p. 263)

•

CREATE TRIGGER (p. 263)

•

CREATE VIEW (p. 265)

•

CREATE CONSTRAINT (p. 265)

•

CREATE SEQUENCE (p. 266)

CREATE TABLE

CREATE TABLE statements are converted automatically except for the following.

Clause

OBJECT TABLE

CLUSTERED TABLE

EXTERNAL TABLE

GLOBAL TEMPORARY

TABLE

Automatically converted

Details

MySQL doesn't support OBJECT TABLE. Revise your code to avoid OBJECT TABLE.

MySQL doesn't support CLUSTERED TABLE. Try using a table with triggers.

MySQL doesn't support EXTERNAL TABLE. Try using a table.

MySQL doesn't support GLOBAL TEMPORARY TABLE. Try using a temporary table.

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Data Deﬁnition Language (DDL)

Clause

Partitioned tables

Virtual columns

Automatically converted

Details

MySQL doesn't support all partition types. Perform a manual conversion for the partition types that aren't supported.

MySQL doesn't support virtual columns. Represent virtual columns using a view.

Functions as default values No

NESTED TABLE columns

COLUMN(TABLE)

MySQL doesn't support functions as default values. Try using a trigger.

MySQL doesn't support tables with NESTED TABLE columns. Revise any tables with NESTED TABLE columns to avoid these columns.

MySQL doesn't support the objects column. Create a user-deﬁned function.

CREATE INDEX

CREATE INDEX statements are converted automatically except that MySQL does not support bitmap, function-based, or domain indexes.

CREATE TRIGGER

CREATE TRIGGER statements are converted automatically except for the following.

Clause

COMPOUND

INSTEAD OF

Automatically converted

Details

MySQL doesn't support compound triggers. Create a single trigger for each part of the compound trigger.

MySQL doesn't support INSTEAD OF. Try using a BEFORE trigger.

MySQL doesn’t support conditional predicates.

INSERTING | UPDATING |

DELETING without FOR EACH ROW No

FOLLOWS | PRECEDES

UPDATE OF

REFERENCING NEW AS |

OLD AS

WHEN(condition)

MySQL doesn't support statement triggers. Try including

FOR EACH ROW.

MySQL doesn't support the FOLLOWS | PRECEDES clause.

Try using a FOR EACH ROW trigger.

MySQL doesn't support the UPDATE OF clause. Try using a FOR EACH ROW trigger.

MySQL doesn't support the REFERENCING clauses. Modify references to pseudorows to use OLD and NEW instead.

MySQL doesn't support WHEN(condition) triggers. Apply the condition for WHEN in the trigger body.

ON NESTED TABLE No

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Data Deﬁnition Language (DDL)

Clause

trigger-status=DISABLED create-date modify-date status description

Automatically converted

Details

MySQL doesn't support the DISABLED clause. Drop the trigger instead.

MySQL doesn't support create-date for triggers. Try using a FOR EACH ROW trigger.

MySQL doesn't support modify-date for triggers. Try using a FOR EACH ROW trigger.

MySQL doesn't support trigger status values. Try using a

FOR EACH ROW trigger.

MySQL doesn't support descriptions for triggers.

In MySQL, you can get a trigger description using

INFORMATION_SCHEMA.TRIGGERS. MySQL doesn't support the REFERENCING clause. The following are the corresponding values between Oracle(USER_TRIGGERS) and MySQL(INFORMATION_SCHEMA.TRIGGERS):

• TABLE_OWNER corresponds to TRIGGER_SCHEMA

• TRIGGER_NAME corresponds to TRIGGER_NAME

• TRIGGER_TYPE corresponds to ACTION_TIMING

• TRIGGERING_EVENT corresponds to

EVENT_MANIPULATION

• TABLE_NAME corresponds to EVENT_OBJECT_TABLE

• REFERENCING_NAMES corresponds to

ACTION_REFERENCE_NEW_ROW(always is NEW),

ACTION_REFERENCE_OLD_ROW(always is OLD) triggeringevent=ddl_events triggeringevent=database_events

No base-object-type=VIEW No base-object-type=SCHEMA No

No base-objecttype=DATABASE action-type=CALL or PL/

SQL

No crossedition=FORWARD/

REVERSE ﬁre-once=YES apply-server-only=YES

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Data Deﬁnition Language (DDL)

Clause

referencingnames=PARENT

Automatically converted

Details

CREATE VIEW

CREATE VIEW statements are converted automatically except for the following.

Clause

FORCE

NOFORCE

WITH READ ONLY create-date modify-date status oid-text view-type-owner view-type superview-name editioning-view encrypted-view

CAST

Automatically converted

Details

No NOFORCE is the default behavior for MySQL. You don't need to specify this option.

MySQL doesn’t support views with nested table columns.

CREATE CONSTRAINT

CREATE CONSTRAINT statements are converted automatically except for the following.

Clause Automatically converted

Details

DISABLE, status=DISABLED No

Foreign keys of diﬀerent types constraint-type

My SQL doesn't support constraints with the status

DISABLE. Drop the constraint.

MySQL doesn't support foreign keys with diﬀerent types of columns and referenced columns. Modify the column types using an equivalent of the column data types in the original database.

MySQL doesn't support the constraint check option on a view. Try using a trigger.

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Cursors

CREATE SEQUENCE

MySQL doesn't support sequences. Try developing a system for sequences in your application.

Cursors

Cursors are converted automatically except for the following.

Clause

SQLAttribute

REF CURSOR

SYS_REFCURSOR

CURSOR

REF_CURSOR variable

Automatically converted

Details

Partial

MySQL doesn't support the cursor attribute

SQL%ISOPEN

MySQL doesn't support the cursor attribute

SQL

%BULK_ROWCOUNT

. To calculate processed rows, use a variable.

MySQL doesn't support the REF CURSOR object. Perform a manual conversion.

Partial

MySQL doesn't support a variable of SYS_REFCURSOR type. Perform a manual conversion.

The AWS Schema Conversion Tool cannot automatically transform the SELECT statement for an implicit cursor.

Try rewriting the SELECT statement.

The SELECT statement for the REF_CURSOR variable cannot be transformed. Try rewriting the SELECT statement.

Hints

MySQL doesn't support hints. Try using MySQL performance tuning methods or perform a manual conversion.

Clause

/*+ ALL_ROWS */

/*+ AND_EQUAL(table index...) */

/*+ APPEND */

/*+ CACHE(table) */

/*+ CHOOSE */

/*+ CLUSTER(table) */

/*+

CURSOR_SHARING_EXACT

/*+ DRIVING_SITE(table) */ No

Automatically converted

Details

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Hints

Clause Automatically converted

Details

/*+ DYNAMIC_SAMPLING */ No

No /*+

EXPAND_GSET_TO_UNION

/*+ FACT(table) */

/*+ FIRST_ROWS(n) */

/*+ FULL(table) */

/*+ HASH */

/*+ HASH_SJ */

/*+ INDEX(table index) */

/*+ INDEX_ASC(table index)

/*+ INDEX_COMBINE(table index) */

/*+ INDEX_DESC(table index) */

/*+ INDEX_FFS(table index)

/*+ LEADING(table) */

/*+ MERGE(table) */

/*+ MERGE_SJ */

/*+ NL_SJ */

/*+ NO_EXPAND */

/*+ NO_INDEX(table index)

/*+ NO_MERGE(table) */ No

/*+ NO_PARALLEL(table) */ No

No /*+

NO_PARALLEL_INDEX(table index) */

/*+

NO_PUSH_PRED(subquery)

/*+

NO_PUSH_SUBQ(subquery)

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Hints

Clause

/*+ NO_REWRITE */

/*+ NO_UNNEST */

/*+ NOAPPEND */

/*+ NOCACHE(table) */

/*+ NOFACT(table) */

/*+ ORDERED */

/*+ ORDERED_PREDICATES

/*+ PARALLEL(table server_num) */

/*+ PARALLEL_INDEX(table index server_num) */

/*+ PQ_DISTRIBUTE(table out_distr in_distr) */

/*+ PUSH_PRED(subquery)

/*+ PUSH_SUBQ(subquery)

/*+ REWRITE */

/*+ ROWID(table) */

/*+ RULE */

/*+ STAR */

/*+

STAR_TRANSFORMATION

/*+ UNNEST */

/*+ USE_CONCAT */

/*+ USE_HASH(table1 table2) */

/*+ USE_MERGE(table1 table2) */

Automatically converted

Details

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Exceptions

Item

RAISE

EXCEPTION

PRAGMA EXCEPTION_INIT

Automatically converted

Details

MySQL doesn't support the RAISE command. Review the exception, and if possible convert it to an exception using the SIGNAL or RESIGNAL statement.

MySQL doesn't support the %s exception. Review the exception, and if possible convert it to an exception using the SIGNAL or RESIGNAL statement.

MySQL doesn't support the EXCEPTION declaration. Use the DECLARE ... CONDITION statement.

MySQL doesn't support the PRAGMA EXCEPTION_INIT declaration. Use the DECLARE ... CONDITION statement.

MySQL doesn't support the

PROC_RAISE_APPLICATION_ERROR statement. Use the

DECLARE ... CONDITION statement. Try using the SIGNAL or RESIGNAL statement.

Built-In Exceptions

Exception

INVALID_NUMBER

TIMEOUT_ON_RESOURCE No

TRANSACTION_BACKED_OUT No

INVALID_CURSOR No

Automatically converted

Details

No Try creating a user exception.

Try creating a user exception.

You can use one of several handlers for invalid cursors.

Choose the correct handler based on the issue.

Try creating a user exception.

NOT_LOGGED_ON

LOGIN_DENIED

STORAGE_ERROR

PROGRAM_ERROR

Try creating a user exception.

You can use one of several handlers for invalid cursors.

Choose the correct handler based on the issue.

Try using the handler "1815 - Internal Error."

Oracle to PostgreSQL Supported Schema

Conversion

The following sections list the schema elements from an Oracle database and whether they are supported for automatic conversion to PostgreSQL using the AWS Schema Conversion Tool.

DDL

Statements

Clause

ALTER CLUSTER

ALTER DATABASE

ALTER DIMENSION

ALTER DISKGROUP

ALTER FLASHBACK

DML

Built-in SQL Functions

Aggregate Functions

Clause

AVG

COLLECT

CORR

CORR_*

COUNT

COVAR_POP

COVAR_SAMP

CUME_DIST

DENSE_RANK

FIRST

GROUP_ID

GROUPING

GROUPING_ID

LAST

Automatically

Converted

Details

Yes

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

Yes

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

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DML

Clause

MAX

MEDIAN

MIN

PERCENT_RANK

PERCENTILE_CONT

PERCENTILE_DISC

RANK

REGR_ (Linear Regression)

Functions

STATS_BINOMIAL_TEST

STATS_CROSSTAB

STATS_F_TEST

STATS_KS_TEST

STATS_MODE

STATS_MW_TEST

STATS_ONE_WAY_ANOVA

STATS_T_TEST_*

STATS_WSR_TEST

STDDEV

STDDEV_POP

STDDEV_SAMP

Automatically

Converted

Details

Yes

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

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Clause

SUM

VAR_POP

VAR_SAMP

VARIANCE

AWS Schema Conversion Tool User Guide

DML

Automatically

Converted

Details

Yes

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

Analytic Functions

Clause

AVG *

CORR *

COUNT *

COVAR_POP *

COVAR_SAMP *

CUME_DIST

DENSE_RANK

FIRST

FIRST_VALUE *

LAG

LAST

LAST_VALUE *

LEAD

MAX *

MIN *

NTILE

PERCENT_RANK

PERCENTILE_CONT

PERCENTILE_DISC

Yes

Automatically

Converted

Details

Yes

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

Yes

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

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DML

Clause

RANK

RATIO_TO_REPORT

REGR_ (Linear Regression)

Functions *

ROW_NUMBER

STDDEV *

STDDEV_POP *

STDDEV_SAMP *

SUM *

VAR_POP *

VAR_SAMP *

VARIANCE *

Yes

Automatically

Converted

Details

Yes

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

Yes

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

Yes

Character Functions Returning Character Values

Clause

CHR(num)

CONCAT(char1, char2)

INITCAP(string)

LOWER(string)

LPAD(string, len)

LPAD(string, len, pad)

LTRIM(string)

NLS_INITCAP

NLS_LOWER

NLS_UPPER

NLSSORT

Yes

Automatically

Converted

Details

Yes

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

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DML

Clause

REGEXP_REPLACE

REGEXP_SUBSTR

REPLACE(str, search)

REPLACE(str, search, replace)

RPAD(string, len)

RTRIM(string)

RTRIM(string, set)

SOUNDEX(string)

SUBSTR(string, pos, len)

TRANSLATE(string, from, to)

TREAT

TRIM([type trim FROM] string)

UPPER(string)

Yes

Automatically

Converted

Details

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

Yes

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

Yes

Character Functions Returning Number Values

Clause

ASCII(str)

INSTR(str, substr)

INSTR(str, substr, pos)

Automatically

Converted

Details

Yes

Implemented in Extension

Library

INSTR(str, substr, pos, num) Implemented in Extension

Library

LENGTH(string)

REGEXP_INSTR

Yes

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

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DML

Collection Functions

Clause

CARDINALITY

COLLECT

SET

Automatically

Converted

Details

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

Conversion Functions

Clause

ASCIISTR(string)

BIN_TO_NUM(bit1, bit2, …) Yes

CAST Yes

CHARTOROWID No

Automatically

Converted

Details

Implemented in Extension

Library

COMPOSE

CONVERT(string, charset)

DECOMPOSE

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

HEXTORAW

NUMTODSINTERVAL

Yes

NUMTOYMINTERVAL No

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

RAWTOHEX

RAWTONHEX

Yes

ROWIDTOCHAR

ROWIDTONCHAR

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

SCN_TO_TIMESTAMP

TIMESTAMP_TO_SCN

Yes

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DML

Clause

TO_BINARY_DOUBLE

TO_BINARY_FLOAT

TO_CHAR (character)

Yes

TO_CHAR (datetime, format)

Yes

TO_CHAR (number, format) Implemented in Extension

Library

TO_CLOB

TO_DATE

Automatically

Converted

Details

Yes

TO_DSINTERVAL

TO_LOB

TO_MULTI_BYTE

TO_NCHAR (character)

TO_NCHAR (datetime)

Yes

Implemented in Extension

Library

Yes

TO_NCHAR (number)

TO_NCLOB

TO_NUMBER

TO_SINGLE_BYTE

TRANSLATE ... USING

UNISTR

Implemented in Extension

Library

Implemented in Extension

Library

Implemented in Extension

Library

Implemented in Extension

Library

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

Implemented in Extension

Library

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DML

Data Mining Functions

Clause

CLUSTER_ID

CLUSTER_PROBABILITY

CLUSTER_SET

FEATURE_ID

FEATURE_SET

FEATURE_VALUE

PREDICTION

PREDICTION_COST

PREDICTION_DETAILS

PREDICTION_PROBABILITY

PREDICTION_SET

Automatically

Converted

Details

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

Datetime Functions

Clause Automatically

Converted

Details

ADD_MONTHS(date, num) Implemented in Extension

Library

CURRENT_DATE

CURRENT_TIMESTAMP

DBTIMEZONE

Yes

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

EXTRACT(DAY FROM date) Yes

EXTRACT(HOUR FROM time)

Yes

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DML

Clause Automatically

Converted

Details

Yes EXTRACT(MINUTE FROM time)

EXTRACT(MONTH FROM date)

Yes

EXTRACT(SECOND FROM time)

Yes

EXTRACT(YEAR FROM date) Yes

FROM_TZ Implemented in Extension

Library

LAST_DAY(date)

LOCALTIMESTAMP

LOCALTIMESTAMP([prec])

MONTHS_BETWEEN(date1, date2)

NEW_TIME

Implemented in Extension

Library

Yes

NEXT_DAY

NUMTODSINTERVAL

NUMTOYMINTERVAL

ROUND (date)

Implemented in Extension

Library

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

SESSIONTIMEZONE

SYS_EXTRACT_UTC

Yes

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

SYSDATE

SYSTIMESTAMP

TO_CHAR (datetime, format)

TO_DSINTERVAL

Yes

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

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DML

Clause

TO_TIMESTAMP(exp)

TO_TIMESTAMP_TZ

TO_YMINTERVAL

TRUNC (datetime)

TZ_OFFSET

Automatically

Converted

Details

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

dbms_output

Clause

dbms_output.put() dbms_output.put_line()

Automatically

Converted

Details

Yes

Encoding and Decoding Functions

Clause Automatically

Converted

Details

Yes DECODE(exp, when, then,

…)

DUMP No

ORA_HASH

VSIZE

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

Environment and Identiﬁer Functions

Clause

SYS_CONTEXT

SYS_GUID

Automatically

Converted

Details

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

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DML

Clause

SYS_TYPEID

UID

USER

USERENV('parameter')

Automatically

Converted

Details

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

Yes

General Comparison Functions

Clause

GREATEST(exp, exp2, …)

LEAST(exp, exp2, …)

Automatically

Converted

Details

Yes

Hierarchical Functions

Clause

SYS_CONNECT_BY_PATH

Automatically

Converted

Details

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

Large Object Functions

Clause

BFILENAME

EMPTY_BLOB,

EMPTY_CLOB

Automatically

Converted

Details

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

Model Functions

Clause

ITERATION_NUMBER

PRESENTNNV

Automatically

Converted

Details

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

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DML

Clause

PRESENTV

Automatically

Converted

Details

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

NLS Character Functions

Clause

NLS_CHARSET_DECL_LEN

NLS_CHARSET_ID

NLS_CHARSET_NAME

Automatically

Converted

Details

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

NULL-Related Functions

Clause

COALESCE(exp1, exp2, …)

Automatically

Converted

Details

Yes

LNNVL No

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

NULLIF(exp1, exp2)

NVL(exp, replacement)

NVL2(exp1, exp2, exp3)

Yes

Numeric Functions

Clause

ABS(num)

ACOS(num)

ASIN(num)

ATAN(num)

ATAN2(x,y)

BITAND(exp1, exp2)

CEIL(num)

Yes

Automatically

Converted

Details

Yes

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DML

Clause

COS(num)

COSH(num)

EXP(n)

FLOOR(num)

LN(num)

LOG(num1, num2)

MOD(dividend, divisor)

NANVL(n2, n1)

POWER(value, n)

REMAINDER(n1, n2)

ROUND (num, integer)

SIGN(exp)

SIN(num)

SINH(num)

SQRT(num)

TAN(num)

TANH(num)

TRUNC (number)

WIDTH_BUCKET

Yes

Automatically

Converted

Details

Yes

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

Object Reference Functions

Clause

DEREF

MAKE_REF

REF

REFTOHEX

Automatically

Converted

Details

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

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Clause

VALUE

XML Functions

Clause

APPENDCHILDXML

DELETEXML

DEPTH

EXISTSNODE

EXTRACT (XML)

EXTRACTVALUE

INSERTCHILDXML

INSERTXMLBEFORE

PATH

SYS_DBURIGEN

SYS_XMLAGG

SYS_XMLGEN

UPDATEXML

XMLAGG

XMLCDATA

XMLCOLATTVAL

AWS Schema Conversion Tool User Guide

DML

Automatically

Converted

Details

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

Automatically

Converted

Details

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

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Clause

XMLCOMMENT

XMLCONCAT

XMLFOREST

XMLPARSE

XMLPI

XMLQUERY

XMLROOT

XMLSEQUENCE

XMLSERIALIZE

XMLTABLE

XMLTRANSFORM

Hints

Clause

Index and Cluster

Join Order

Joins

Optimizer Mode

Parallel Execution

Query Transformation

AWS Schema Conversion Tool User Guide

DML

Automatically

Converted

Details

Issue 5340: PostgreSQL doesn't support the %s function (p. 311)

Automatically

Converted

Details

Issue 5103: PostgreSQL doesn't support the %s hint (p. 319)

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DML

Clause

Other

Automatically

Converted

Details

Issue 5103: PostgreSQL doesn't support the %s hint (p. 319)

Joins

Clause

Cross Joins

Inner Joins

Outer Joins

Automatically

Converted

Details

Yes

Operators and Date Functions

Clause

Arithmetic operators

Concatenation operators

Automatically

Converted

Details

Yes

Predicates

Clause

Boolean conditions

Comparison conditions: '=,

<>, <, <=, >, >=, ANY, SOME,

ALL

Exists conditions

In conditions

Null conditions

Pattern matching conditions

Range conditions

Yes

Automatically

Converted

Details

Yes

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DML

Set operators

Concatenation operators

Clause

INTERSECT, EXCEPT

MINUS

UNION, UNION ALL

Automatically

Converted

Details

Yes

Statements

DELETE

Clause Automatically

Converted

Details

DELETE FROM

MATERIALIZED VIEW

DELETE FROM SUBQUERY No

Issue 5095: PostgreSQL doesn't support using a materialized VIEW (p. 318)

Issue 5068: PostgreSQL doesn't support the DELETE statement for a subquery (p. 316)

DELETE FROM TABLE

DELETE FROM VIEW

DELETE with Error Logging clause

DELETE with RETURNING clause

Yes

Issue 5067: PostgreSQL doesn't support the DELETE statement with the ERROR LOG option (p. 315)

HIERARCHICAL QUERY AND HIERARCHICAL QUERY PSEUDOCOLUMNS

Clause

CONNECT BY CLAUSE

CONNECT BY NOCYCLE

Automatically

Converted

Details

Yes

Issue 5586: Automatic conversion for queries with

NOCYCLE clause not supported (p. 320)

Yes CONNECT_BY_ISLEAF pseudocolumn

LEVEL PSEUDOCOLUMN

ORDER SIBLINGS BY

START WITH CLAUSE

SYS_CONNECT_BY_PATH

Yes

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DML

Hierarchical query operators

Clause

CONNECT_BY_ROOT

PRIOR

Automatically

Converted

Details

Yes

INSERT

Clause

ALL

DEFAULT

ELSE

FIRST

INSERT from clause

"SUBQUERY"

INSERT from clause

"VALUES(...)"

INSERT INTO SUBQUERY No

INSERT INTO TABLE

INSERT INTO VIEW

INSERT with partition_extension_clause

Inserting Into a Table with

Error Logging clause

RETURNING INTO

WHEN

Yes

Automatically

Converted

Details

Yes

Issue 5071: PostgreSQL doesn't support the INSERT statement for a subquery (p. 318)

Issue 5024: PostgreSQL doesn't support the INSERT statement with partition_extension_clause (p. 318)

Issue 5070: PostgreSQL doesn't support the INSERT statement with the ERROR LOG option (p. 318)

LOCK TABLE

Clause

Locking table in exclusive mode

Locking table in share mode

Locking without waiting

Automatically

Converted

Details

Yes

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DML

SELECT

Clause

Add or subtract operators

BULK COLLECT INTO

CUBE

FOR UPDATE

GROUP BY

GROUPING SETS

HAVING

INTERSECT

INTO

MINUS

MODEL

ORDER BY

PIVOT clause

ROLLUP

ROWNUM pseudocolumn

SELECT ALL

SELECT DISTINCT

SELECT LIST

SELECT UNIQUE

UNION

UNION ALL

UNPIVOT clause

WHERE( ﬁeld_name1,

…,ﬁeldnameN) IN

Yes

(subquery_with_multiple_ﬁelds)

Yes

Automatically

Converted

Details

Yes

Issue 5140: PostgreSQL doesn't support BULK COLLECT

INTO (p. 320)

Issue 5557: PostgreSQL doesn't support GROUPING SETS,

CUBE, and ROLLUP functions (p. 321)

Issue 5139: PostgreSQL doesn't support FOR UPDATE

SKIP LOCKED (p. 320)

Yes

Issue 5557: PostgreSQL doesn't support GROUPING SETS,

CUBE, and ROLLUP functions (p. 321)

Issue 5126: PostgreSQL doesn't support the MODEL statement (p. 320)

Yes

Issue 5077: PostgreSQL doesn't support the PIVOT clause for the SELECT statement (p. 326)

Issue 5557: PostgreSQL doesn't support GROUPING SETS,

CUBE, and ROLLUP functions (p. 321)

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DML

Clause

WHERE comparison_condition

(=;<>;!

=;<;>;>=;<=;ANY;SOME;ALL)

Yes

WHERE Yes compound_condition_with_or_and_not

Yes WHERE ﬁeld_name

BETWEEN arg1 AND arg2

WHERE ﬁeld_name IN

(const1,...,constN)

Yes

WHERE ﬁeld_name IN

(subquery)

WHERE like_condition

(operator LIKE)

Automatically

Converted

Details

Yes

WITH Yes

UPDATE

Clause

UPDATE (subquery)

UPDATE MATERIALIZED

VIEW

UPDATE TABLE

UPDATE VIEW

UPDATE with Error Logging clause

UPDATE with partition extension clause

UPDATE with RETURNING…

INTO clause

UPDATE with subqueries into SET-clause

UPDATE-operator which based on data from others tables

Yes

Automatically

Converted

Details

Issue 5065: PostgreSQL doesn't support the UPDATE statement for a subquery (p. 325)

Issue 5095: PostgreSQL doesn't support using a materialized VIEW (p. 318)

Issue 5064: PostgreSQL doesn't support the UPDATE statement with the ERROR LOG option (p. 325)

Issue 5558: PostgreSQL doesn't support the UPDATE statement for a PARTITION (p. 325)

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PLSQL

Clause

MERGE

TRUNCATE TABLE

Automatically

Converted

Details

Issue 5102: PostgreSQL doesn't support the MERGE statement (p. 319)

Yes

PLSQL

Arguments of functions and procedures

Clause Automatically

Converted

Details

Yes Built-in datatype scalar arguments

Cursor-type arguments

Default clause in declaration of arguments

IN, OUT, IN OUT type of arguments

Yes

Ref cursor-type arguments Yes

UDT collection-type arguments

Yes

UDT object-type arguments Yes

UDT record-type Yes

Functions

Clause

Functions with DML

Functions without DML

Return pipelined table

Return ref cursor

Return scalar

Return table

Yes

Return UDT collection-type Yes

Return UDT object-type Yes

Automatically

Converted

Details

Yes

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PLSQL

Clause

Return UDT record-type

Packages

Automatically

Converted

Details

Yes

Clause

Global cursor declaration

Global user exception declaration

Initialization block BEGIN

… END in packages

Package functions

Package procedures

Package variables

User type declaration

Yes

Automatically

Converted

Details

Issue 5569: PostgreSQL only supports session variables using SQL standard date and time types (p. 319)

Yes

PL SQL constructions

Clause

block EXCEPTION when exception_name then…

CASE_NOT_FOUND case when conditions then…else… end case; close cursor_variable

COMMIT

CURSOR_ALREADY_OPEN

DUP_VAL_ON_INDEX execute immediate

SQL_string_variable into variables_list use variables_list fetch cursor_variable into variables_list

Automatically

Converted

Details

Yes

Issue 5334: PostgreSQL doesn't support the dynamic SQL statement (p. 316)

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PLSQL

Clause

FORALL -cycle for I in(begN..endN) loop… end loop for I in(cursor_name) loop… end loop for I in(select_statement) loop… end loop

FOR i IN REVERSE begN..endN LOOP… END

LOOP; goto label;

Yes

Automatically

Converted

Details

Issue 5121: PostgreSQL doesn't support the FORALL statement (p. 324)

Yes

Issue 5335: PostgreSQL doesn't support the GOTO operator (p. 321)

if conditions then…else if conditions then… end if;

Yes if conditions then… end if; Yes

INVALID_CURSOR Yes

INVALID_NUMBER

LOGIN_DENIED

LOOP…exit when conditions; END LOOP;

NO_DATA_FOUND

NOT_LOGGED_ON

Yes

NULL Statement open cursor_variable

Yes

Yes open cursor_variable for Yes select_statemet_string_variable others Yes

PRAGMA No

AUTONOMOUS_TRANSACTION

Issue 5350: The function can't use statements that explicitly or implicitly begin or end a transaction, such as

START TRANSACTION, COMMIT, or ROLLBACK (p. 318)

PROGRAM_ERROR Yes raise_application_error(exept_code, message)

Yes raise exeption_name Yes

ROLLBACK Yes

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PLSQL

Clause

select…bulk collect into table_variable from table_name

SQL%BULK_ROWCOUNT

SQL%FOUND

SQL%ISOPEN

SQL%NOTFOUND

SQL%ROWCOUNT

STORAGE_ERROR

TIMEOUT_ON_RESOURCE

TOO_MANY_ROWS Yes

TRANSACTION_BACKED_OUT Yes

VALUE_ERROR Yes while conditions loop… end loop;

ZERO_DIVIDE

Yes

Automatically

Converted

Details

Issue 5140: PostgreSQL doesn't support BULK COLLECT

INTO (p. 320)

Issue 5084: PostgreSQL doesn't support the cursor attribute %ISOPEN (p. 315)

PL SQL declaration block

Clause Automatically

Converted

Details

Declare built-in scalar variable

Yes

Declare ref-cursor variable Yes

Declare static cursor

Declare UDT collection variable

Yes

Declare UDT object variable Yes

Declare UDT record variable Yes

Declare UDT array types Yes

Declare user-exception

Declare with %rowtype option

Yes

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Data Types

Clause Automatically

Converted

Details

Declare with %type option Yes

Procedures

Clause

CREATE PROCEDURE statement

Automatically

Converted

Details

Yes

Triggers

Clause

BEFORE, AFTER - options

FOR EACH ROW -option

INSTEAD OF - options

NESTED TABLE - clause

REFERENCING - clause

Statement-trigger trigger on TABLE

Trigger on VIEW

WHEN(condition)- option

Yes

Automatically

Converted

Details

Yes

Issue 5240: PostgreSQL doesn't support triggers on nested table columns in views (p. 323)

Issue 5238: PostgreSQL doesn't support the

REFERENCING clauses (p. 323)

Data Types

Data type

BFILE

BINARY_FLOAT

BINARY_DOUBLE

BLOB

CHAR(n)

Automatically

Converted to

character varying real double precision bytea character

Details

Issue 5212: PostgreSQL doesn't have a data type

BFILE (p. 312)

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Data type

CHARACTER(n)

CLOB

DATE

DECIMAL(p,s)

DEC(p,s)

FLOAT

INTEGER

INT

INTERVAL YEAR(p) TO

MONTH

INTERVAL DAY(p) TO

SECOND(s)

LONG

LONG RAW

NCHAR(n)

NCHAR VARYING(n)

NCLOB

NUMBER(p)

NUMBER(p,0)

NUMBER(*,0)

NUMBER(p,s)

NUMBER(*)

NUMBER

NVARCHAR2(n)

RAW(n)

ROWID

AWS Schema Conversion Tool User Guide

Data Types bytea character character varying text numeric numeric numeric numeric double precision double precision character varying bytea character

Automatically

Converted to

character

Details

text timestamp(0) without time zone numeric numeric double precision numeric numeric interval year to month interval day to second(s) text

Issue 5550: PostgreSQL doesn't have a data type

ROWID (p. 313)

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Data type

TIMESTAMP(p)

TIMESTAMP(p) WITH TIME

ZONE

TIMESTAMP(p) WITH TIME

ZONE

TIMESTAMP(p) WITH

LOCAL TIME ZONE

TIMESTAMP(p) WITH

LOCAL TIME ZONE

UROWID

VARCHAR

VARCHAR2

XMLTYPE timestamp(6) with time zone timestamp(p) without time zone timestamp(6) without time zone character varying character varying character varying xml

Automatically

Converted to

timestamp(p) without time zone timestamp(6) without time zone timestamp(p) with time zone

Details

Issue 5213: PostgreSQL expands fractional seconds support for TIME, DATETIME, and TIMESTAMP values, with up to microseconds (6 digits) of precision (p. 314)

Issue 5552: PostgreSQL expands fractional seconds support for TIME, DATETIME, and TIMESTAMP values, with up to microseconds (6 digits) of precision (p. 314)

Issue 5553: PostgreSQL expands fractional seconds support for TIME, DATETIME, and TIMESTAMP values, with up to microseconds (6 digits) of precision (p. 314)

Issue 5551: PostgreSQL doesn't have a data type

UROWID (p. 314)

Oracle to PostgreSQL Conversion Reference

Use the following sections to get information on the types of issues you might encounter during an

Oracle to PostgreSQL conversion. Choose the link in the Issue column to get more detailed resolution information about the issue if it is available.

Build_in_services

Item

UTL_SMTP

DBMS_JOB

Issue

Issue 5590: The function was converted as procedure (p. 310)

Resolution

Can't return a reply because this functionality is asynchronous.

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Built-In SQL Functions

Item

DateTime function

Issue

Issue 5584: The function %s depends on the time zone setting (p. 311)

FUNCTION

GREATEST(exp, exp2, ...)

LEAST(exp, exp2, ...)

Issue 5340: PostgreSQL doesn't support the

%s function (p. 311)

Issue 5271: The Oracle GREATEST function and PostgreSQL GREATEST function might give diﬀerent results (p. 311)

Issue 5272: The Oracle LEAST function and

PostgreSQL LEAST function might give diﬀerent results (p. 311)

TO_CHAR, TO_DATE,

TO_NUMBER

Issue 5579: The second parameter of %s function can be processed incorrectly (p. 311)

Resolution

Review the transformed code, and set time zone manually if necessary.

Use suitable function or create user deﬁned function.

Review your transformed code and modify it if necessary. Change an argument's type if necessary.

Check converted code and make manual corrections if it's necessary.

CREATE

Item

Encrypted Objects

Issue

Issue 5099: Unable convert object due to %s not created (p. 311)

Issue 5332: The object has references on the object in %s schema (p. 311)

Issue 5582: Encrypted Objects (p. 312)

Resolution

Review the %s object.

Convert the object in %s schema also.

Decrypt the object before conversion.

CREATE CONSTRAINT

Item

status=DISABLED

Issue

Issue 5326: PostgreSQL doesn't support constraints with the status

DISABLED (p. 312)

CREATE INDEX

Item

Creating a Domain

Index

Issue

Issue 5208: PostgreSQL doesn't support domain indexes (p. 312)

Resolution

Drop the constraint.

Resolution

Revise your code and try to use simple index.

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Item

Creating a Function-

Based Index

Creating an BITMAP

Index

Issue

Issue 5555: PostgreSQL doesn't support functional indexes that aren't singlecolumn (p. 312)

Issue 5206: PostgreSQL doesn't support bitmap indexes (p. 312)

Resolution

Revise your code and try to use simple index.

CREATE TABLE

Item

BFILE Data Type

CREATING A

PARTITIONED TABLE

Issue

Issue 5212: PostgreSQL doesn't have a data type BFILE (p. 312)

Issue 5201: PostgreSQL doesn't support all partition types (p. 313)

Resolution

Either store a named file with the data and create a routine that gets that file from the file system, or store the data blob inside your database.

Perform a manual conversion for the partition types that aren't supported.

Try using a table with triggers.

Try using a table.

CREATING

CLUSTERED TABLE

CREATING EXTERNAL

TABLES

CREATING GLOBAL

TEMPORARY TABLE

CREATING OBJECT

TABLES

Issue 5199: PostgreSQL doesn't support

CLUSTERED TABLE (p. 313)

Issue 5200: PostgreSQL doesn't support

EXTERNAL TABLES (p. 313)

Issue 5198: PostgreSQL doesn't support

GLOBAL TEMPORARY TABLE (p. 313)

Issue 5196: PostgreSQL doesn't support

OBJECT TABLE (p. 313)

Index-organized table

Issue 5581: PostgreSQL doesn't support index-organized table (p. 313)

NESTED TABLE

ROWID data type

Issue 5348: PostgreSQL doesn't support

NESTED TABLES (p. 313)

Issue 5550: PostgreSQL doesn't have a data type ROWID (p. 313)

TABLE WITH VIRTUAL

COLUMNS

TIMESTAMP(n>6)

Data Type

TIMESTAMP(n>6)

WITH TIME ZONE data type

Issue 5554: PostgreSQL doesn't support virtual columns (p. 313)

Issue 5213: PostgreSQL expands fractional seconds support for TIME, DATETIME, and

TIMESTAMP values, with up to microseconds

(6 digits) of precision (p. 314)

Issue 5552: PostgreSQL expands fractional seconds support for TIME, DATETIME, and

TIMESTAMP values, with up to microseconds

(6 digits) of precision (p. 314)

Try using a local temporary table.

Revise your code to avoid

OBJECT TABLE.

Revise your architecture with a custom solution for the table type.

Revise your code to avoid

NESTED TABLE.

Review your transformed code and modify it if necessary.

They were emulated by a trigger.

Review your transformed code and modify it if necessary to avoid a loss of accuracy.

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Item

TIMESTAMP(n>6)

WITH LOCAL TIME

ZONE data type

UROWID data type

Issue

Issue 5553: PostgreSQL expands fractional seconds support for TIME, DATETIME, and

TIMESTAMP values, with up to microseconds

(6 digits) of precision (p. 314)

Issue 5551: PostgreSQL doesn't have a data type UROWID (p. 314)

Resolution

Review your transformed code and modify it if necessary to avoid a loss of accuracy.

Review your transformed code and modify it if necessary.

CREATE TYPE

Item

OBJECT TYPE

Issue

Issue 5572: PostgreSQL doesn't support object type methods (p. 315)

Resolution

Revise your architecture with a custom solution for the user type.

CURSOR

Item

Cursor attributes

TYPE .. IS REF

CURSOR

PARTITION

Issue

Issue 5084: PostgreSQL doesn't support the cursor attribute %ISOPEN (p. 315)

Issue 5226: PostgreSQL doesn't support

TYPE ... IS REF CURSOR (p. 315)

Resolution

Revise how you are using this attribute in your code.

Change the function to a stored procedure, and try using a table to store results.

Datetime Expressions

Item

at local at time zone

Issue

Issue 5594: PostgreSQL doesn't support %s datetime expression. The loss of precision and/or accuracy of data is possible (p. 315)

Resolution

Check, if the data violates these restrictions. If so, perform a manual migration.

DELETE

Item

ERROR LOG

Issue

Issue 5067: PostgreSQL doesn't support the DELETE statement with the ERROR LOG option (p. 315)

Issue 5098: PostgreSQL doesn't support the

DELETE statement for a PARTITION (p. 316)

Version 1.0

302

Resolution

You can add error records by inserting them into the log in the exception block.

Iterate through the errors in the exception block, add them to the log, and use the EXIT command when ﬁnished.

Either insert data into the overlying partition, or

AWS Schema Conversion Tool User Guide

Oracle to PostgreSQL Conversion Reference

Item

QUERY

Issue

Issue 5068: PostgreSQL doesn't support the

DELETE statement for a subquery (p. 316)

Resolution

perform a manual conversion using the DELETE statement.

Perform this operation on the underlying tables instead.

DYNAMIC SQL

Item

BULK COLLECT

Issue

Issue 5088: PostgreSQL doesn't support the

EXECUTE IMMEDIATE statement with BULK

COLLECT (p. 316)

EXECUTE IMMEDIATE

Issue 5334: PostgreSQL doesn't support the dynamic SQL statement (p. 316)

RETURNING BULK

COLLECT INTO

Issue 5087: PostgreSQL doesn't support the RETURNING BULK COLLECT INTO clause (p. 316)

Resolution

Perform a manual conversion.

Review and modify the execution string.

Perform a manual conversion.

EXCEPTION

Item Issue

ACCESS_INTO_NULL

Issue 5561: PostgreSQL doesn't support the

ACCESS_INTO_NULL exception (p. 316)

COLLECTION_IS_NULL

EMPTY_BLOCK

EXCEPTION

NO_DATA_NEEDED

PROGRAM_ERROR

ROWTYPE_MISMATCH

Issue 5562: PostgreSQL doesn't support the

COLLECTION_IS_NULL exception (p. 316)

Issue 5580: The exception block was emptied after conversion (p. 316)

Issue 5570: PostgreSQL doesn't support exception name declaration (p. 317)

Issue 5563: PostgreSQL doesn't support the

NO_DATA_NEEDED exception (p. 317)

Issue 5560: PostgreSQL doesn't support the

PROGRAM_ERROR exception (p. 317)

Issue 5564: PostgreSQL doesn't support the

ROWTYPE_MISMATCH exception (p. 317)

Resolution

Review the exception used, and if possible convert it to another condition.

Check converted code and make manual corrections if it is necessary.

Review the exception used, and if possible convert it to another condition.

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Item

SELF_IS_NULL

Issue

Issue 5565: PostgreSQL doesn't support the

SELF_IS_NULL exception (p. 317)

Issue 5566: PostgreSQL doesn't support the SUBSCRIPT_BEYOND_COUNT exception (p. 317)

Issue 5567: PostgreSQL doesn't support the SUBSCRIPT_OUTSIDE_LIMIT exception (p. 317)

SYS_INVALID_ROWID

Issue 5568: PostgreSQL doesn't support the

SYS_INVALID_ROWID exception (p. 317)

Resolution

Review the exception used, and if possible convert it to another condition.

EXPLICIT CURSORS

Item

RETURN

Issue

Issue 5559: PostgreSQL doesn't support the

RETURN TYPE for the cursor (p. 317)

Resolution

Use cursor declaration without this statement.

FUNCTION

Item

FUNCTIONS WITH

DML (START

TRANSACTION,

COMMIT, or

ROLLBACK.)

Issue

Issue 5350: The function can't use statements that explicitly or implicitly begin or end a transaction, such as START TRANSACTION,

COMMIT, or ROLLBACK (p. 318)

Resolution

Revise you code to implement a transaction control at application side.

INSERT

Item

ERROR LOG

Issue

Issue 5070: PostgreSQL doesn't support the INSERT statement with the ERROR LOG option (p. 318)

INSERT with

Issue 5024: PostgreSQL doesn't support the INSERT statement with partition_extension_clause (p. 318)

QUERY

Issue 5071: PostgreSQL doesn't support the

INSERT statement for a subquery (p. 318)

Version 1.0

304

Resolution

You can add error records by inserting them into the log in the exception block.

Iterate through the errors in the exception block, add them to the log, and use the EXIT command when ﬁnished.

Perform a manual conversion for the partition types that aren't supported.

Perform this operation on the underlying tables instead.

AWS Schema Conversion Tool User Guide

Oracle to PostgreSQL Conversion Reference

Item

SUBPARTITION

Issue

Issue 5090: PostgreSQL doesn't support the INSERT statement for a

SUBPARTITION (p. 318)

Resolution

Either insert data into the overlying partition, or perform a manual conversion using the INSERT statement.

MATERIALIZED VIEW

Item

CREATE

Issue

Issue 5094: PostgreSQL doesn't support a materialized VIEW (p. 318)

USING MATERIALIZED

VIEW

Issue 5095: PostgreSQL doesn't support using a materialized VIEW (p. 318)

Resolution

Revise your code to replace materialized VIEW with another solution.

MERGE

Item

MERGE

Issue

Issue 5102: PostgreSQL doesn't support the

MERGE statement (p. 319)

Resolution

To achieve the eﬀect of a MERGE statement, use separate INSERT, DELETE, and

UPDATE statements.

Optimizer Hints

Item

HINT

Issue

Issue 5103: PostgreSQL doesn't support the

%s hint (p. 319)

Resolution

Use PostgreSQL methods for performance tuning.

PACKAGES

Item Issue

Package global cursor

Issue 5330: PostgreSQL doesn't support global cursors (p. 319)

Package global user

EXCEPTION

Package user type declaration

Issue 5331: PostgreSQL doesn't support a global user exception (p. 319)

Issue 5569: PostgreSQL only supports session variables using SQL standard date and time types (p. 319)

Resolution

Use another method for this functionality.

Revise your architecture with a custom solution for the user type.

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Parser Error

Item

Parser Error

Issue

Issue 5293: Unable to resolve the object (p. 320)

Resolution

Verify if object %s is present in the database. If it isn't, check the object name or add the object. If the object is present, transform the code manually.

PRAGMA

Item

PRAGMA

Issue

Issue 5571: PostgreSQL doesn't support

PRAGMA options (p. 320)

Resolution

Review the exception used, and if possible convert it to another condition.

SELECT

Item

FOR UPDATE SKIP

LOCKED

FOR UPDATE WAIT

Hierarchical queries

MODEL

OUTER JOIN

ROLLUP

Unsupported statement

Issue

BULK COLLECT INTO

Issue 5140: PostgreSQL doesn't support BULK

COLLECT INTO (p. 320)

Issue 5139: PostgreSQL doesn't support FOR

UPDATE SKIP LOCKED (p. 320)

Issue 5144: PostgreSQL doesn't support FOR

UPDATE WAIT clauses (p. 320)

Resolution

You can try to include all of the ﬁelds from your table in an INTO clause.

Try using FOR UPDATE without SKIP LOCKED.

Try using FOR UPDATE without WAIT.

Issue 5586: Automatic conversion for queries with NOCYCLE clause not supported (p. 320)

Issue 5126: PostgreSQL doesn't support the

MODEL statement (p. 320)

Perform a manual conversion.

Revise your code and try using user procedures and temporary tables.

Perform a manual conversion.

Issue 5585: Automatic conversion of an outer join into a correlation query is not supported (p. 320)

Issue 5557: PostgreSQL doesn't support

GROUPING SETS, CUBE, and ROLLUP functions (p. 321)

Issue 5578: Unable to automatically transform the SELECT statement (p. 321)

It can be emulated using

CTE expressions. GROUPING

SETS, CUBE, and ROLLUP ara available in PostgreSQL database v.9.5 or higher.

Try rewriting the statement.

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SEQUENCE

Item

STATUS=INVALID

Issue

Issue 5574: PostgreSQL doesn't support the sequence's status (p. 321)

Resolution

Check the original sequence for errors, and perform the conversion again.

Statements

Item

GOTO

Issue

Issue 5335: PostgreSQL doesn't support the

GOTO operator (p. 321)

Resolution

Perform a manual conversion.

Synonym

Item

private synonym public synonym public synonym

Issue

Issue 5333: This object uses a private synonym (p. 321)

Issue 5592: This object uses a public synonym which references a table, a view, or a function (p. 322)

Issue 5593: This object uses a public synonym which doesn't reference any other objects (p. 322)

Resolution

Check that a referenced object created after synonym conversion exists.

System Package

Item

APEX_UTIL package

DBMS_DATAPUMP

DBMS_JOB module

Issue

Issue 5503: MySQL does not have functionality similar to %s module (p. 322)

Issue 5502: MySQL does not have functionality similar to %s module (p. 322)

Issue 5501: MySQL does not have functionality similar to %s module (p. 322)

UTL_MAIL module

Issue 5500: MySQL does not have functionality similar to %s module (p. 322)

Resolution

Try using the Amazon Simple

Workﬂow (Amazon SWF).

Try using the AWS Import/

Export Snowball.

Try using the AWS Lambda

Service with Scheduled

Events.

Try using the Amazon Simple

Notiﬁcation Service (Amazon

SNS).

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TRIGGERS

Item

action-type=CALL or

PL/SQL base-objecttype=DATABASE

Issue

Issue 5313: PostgreSQL doesn't support the action-type clause (p. 322)

Issue 5415: PostgreSQL doesn't support system triggers (p. 322)

base-objecttype=SCHEMA

Issue 5311: PostgreSQL doesn't support system triggers (p. 323)

COMPOUND TRIGGER

Issue 5242: PostgreSQL doesn't support

COMPOUND TRIGGER (p. 323)

FOLLOWS |

PRECEDES

ON NESTED TABLE

Issue 5241: PostgreSQL doesn't support the

FOLLOWS | PRECEDES clause (p. 323)

Issue 5240: PostgreSQL doesn't support triggers on nested table columns in views (p. 323)

Issue 5238: PostgreSQL doesn't support the

REFERENCING clauses (p. 323)

REFERENCING NEW

AS .. OLD AS ..

referencingnames=PARENT status=invalid

Issue 5317: PostgreSQL doesn't support the

PARENT referencing clause (p. 323)

Issue 5306: Transformation from invalid trigger (p. 323)

Issue 5556: PostgreSQL doesn't support conditional predicates (p. 323)

Resolution

Use another method for this functionality.

Revise your code to replace system triggers with another solution.

Create a single trigger for each part of the compound trigger.

Try using the FOR EACH ROW trigger.

Revise your code to replace nested table with another solution.

Modify references to pseudorows to use OLD and NEW instead.

Use another method for this functionality.

Check the original trigger for errors, and perform the conversion again.

Revise your code and try using simple triggers.

TRUNCATE TABLE

Item

DROP STORAGE

PRESERVE

MATERIALIZED VIEW

LOG

PURGE

MATERIALIZED VIEW

LOG

Issue

Issue 5298: PostgreSQL doesn't support the

DROP STORAGE clause in the TRUNCATE statement (p. 323)

Issue 5300: PostgreSQL doesn't support the PRESERVE clause in the TRUNCATE statement (p. 323)

Issue 5301: PostgreSQL doesn't support the PURGE clause in the TRUNCATE statement (p. 323)

Resolution

Use TRUNCATE without this option.

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Item

REUSE STORAGE

Issue

Issue 5299: PostgreSQL doesn't support the

REUSE STORAGE clause in the TRUNCATE statement (p. 324)

Resolution

Use TRUNCATE without this option.

UDT

Item

STATUS=INVALID

Issue

Issue 5577: PostgreSQL doesn't support a

UDT with body (p. 324)

Resolution

Perform a manual conversion.

UDT collection-type arguments

Item Issue

:= collection_type(...)

Issue 5120: PostgreSQL doesn't support constructors of the "collection" type (p. 324)

EXTEND(n[,i])

Issue 5587: PostgreSQL doesn't support

EXTEND method with parameters (p. 324)

FORALL

Issue 5121: PostgreSQL doesn't support the

FORALL statement (p. 324)

TYPE .. IS TABLE OF...

Issue 5118: PostgreSQL doesn't support table type variables (p. 324)

Resolution

Use the "array" type.

Perform a manual conversion.

Use a FOR LOOP statement.

Use the "array" type.

Universal

Item Issue

Universal action item

Issue 5339: The %s object is invalid (p. 324)

Universal action item

Issue 5591: The %s synonym is system (p. 325)

Resolution

To correct this, update the original source code to make the speciﬁed object valid.

Perform a manual conversion.

Unknown

Item

Unknown object

Unparsed SQL

Issue

Issue 5025: This syntactic element conversion is not supported yet (p. 325)

Issue 5351: Automatic conversion of %s object is not supported (p. 325)

Issue 5576: Unparsed SQL (p. 325)

Resolution

Perform a manual conversion.

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UPDATE

Item

ERROR LOG

PARTITION

QUERY

Issue

Issue 5064: PostgreSQL doesn't support the

UPDATE statement with the ERROR LOG option (p. 325)

Issue 5558: PostgreSQL doesn't support the

UPDATE statement for a PARTITION (p. 325)

Issue 5065: PostgreSQL doesn't support the

UPDATE statement for a subquery (p. 325)

Resolution

You can add error records by inserting them into the log in the exception block.

Iterate through the errors in the exception block, add them to the log, and use the EXIT command when ﬁnished.

Either insert data into the overlying partition, or perform a manual transformation using the

UPDATE statement.

Perform this operation on the underlying tables instead.

VIEW

Item

CAST (MULTISET( constraint

OID_TEXT IS NOT

NULL

PIVOT clause

STATUS=INVALID

VIEW_TYPE_OWNER

IS NOT NULL

WITH READ ONLY

Issue

Issue 5245: PostgreSQL doesn't support views with nested table columns (p. 326)

Resolution

Revise your code to replace nested table with another solution.

Perform a manual conversion.

Issue 5583: PostgreSQL doesn't support constraints for view (p. 326)

Issue 5321: PostgreSQL doesn't support the object view (p. 326)

Issue 5077: PostgreSQL doesn't support the PIVOT clause for the SELECT statement (p. 326)

Perform a manual conversion.

You can use a stored procedure to prepare data, and then return the data with a VIEW.

Perform a manual conversion.

Issue 5320: PostgreSQL doesn't support the view with invalid status (p. 326)

Issue 5322: PostgreSQL doesn't support the typed view (p. 326)

Issue 5075: PostgreSQL doesn't support VIEW with the READ ONLY option (p. 326)

Perform a manual conversion.

Use VIEW without this option instead.

Conversion Issues with Build_in_services

Issue 5590: The function was converted as procedure

Can't return a reply because this functionality is asynchronous.

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Related Topics

•

•

•

Conversion Issues with BUILT-IN SQL FUNCTIONS

Issue 5584: The function %s depends on the time zone setting

Review the transformed code, and set the time zone manually if necessary.

Issue 5340: PostgreSQL doesn't support the %s function

You have SQL code that uses an Oracle function that PostgreSQL doesn't support. Re-write the code to either use an alternative function or create a user-deﬁned function instead. Some of the functions that are not supported are as follows:

• NANVL

• NLS_LOWER

• NLS_UPPER

• SYS_CONTEXT

Issue 5271: The Oracle GREATEST function and PostgreSQL GREATEST function might give diﬀerent results

Review your transformed code and modify it to change the argument's type if necessary.

Issue 5272: The Oracle LEAST function and PostgreSQL LEAST function might give diﬀerent results

Review your transformed code and modify it to change the argument's type if necessary.

Issue 5579: The second parameter of %s function can be processed incorrectly

Review your transformed code and modify it if necessary.

Related Topics

•

•

•

Conversion Issues with CREATE

Issue 5099: Unable convert object due to %s not created

Review the %s object.

Issue 5332: The object has references on the object in %s schema

Convert the object in %s schema also.

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Issue 5582: Encrypted Objects

Decrypt the object before conversion.

Related Topics

•

•

•

Conversion Issues with CREATE CONSTRAINT

Issue 5326: PostgreSQL doesn't support constraints with the status DISABLED

PostgreSQL doesn't support the DISABLE clause on constraints. Drop the constraint prior to conversion.

Related Topics

•

•

•

Conversion Issues with CREATE INDEX

Issue 5208: PostgreSQL doesn't support domain indexes

Revise your code to use a simple index instead.

Issue 5555: PostgreSQL doesn't support functional indexes that aren't singlecolumn

Revise your code to use a simple index instead.

Issue 5206: PostgreSQL doesn't support bitmap indexes

Revise your code to use a simple index instead.

Related Topics

•

•

•

Conversion Issues with CREATE TABLE

Issue 5212: PostgreSQL doesn't have a data type BFILE

Either store a named file with the data and create a routine that gets that file from the file system, or store the data blob inside your database.

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Issue 5201: PostgreSQL doesn't support all partition types

Perform a manual conversion for the partition types that aren't supported.

Issue 5199: PostgreSQL doesn't support CLUSTERED TABLE

Try using a table with triggers instead.

Issue 5200: PostgreSQL doesn't support EXTERNAL TABLES

Try moving the data from the external data source to a regular database table.

Issue 5198: PostgreSQL doesn't support GLOBAL TEMPORARY TABLE

Use of the GLOBAL and LOCAL keywords is deprecated in PostgreSQL. Modify your code to create a temporary table without using these keywords.

Issue 5196: PostgreSQL doesn't support OBJECT TABLE

Revise your code to remove references to tables that are based on an OBJECT type, as shown in the following example:

CREATE TYPE department_typ AS OBJECT

( d_name VARCHAR2(100),

d_address VARCHAR2(200) );

CREATE TABLE departments_obj_t OF department_typ;

Issue 5581: PostgreSQL doesn't support index-organized table

Revise your architecture with a custom solution for the table type. A typical approach is using a simple table instead in PostgreSQL.

Issue 5348: PostgreSQL doesn't support NESTED TABLES

Revise your code to avoid NESTED TABLE.

Issue 5550: PostgreSQL doesn't have a data type ROWID

Review your transformed code and modify it if necessary to use a diﬀerent data type.

Issue 5554: PostgreSQL doesn't support virtual columns

Emulate the virtual column by using a trigger instead. For example, you could modify the following

Oracle table:

CREATE TABLE employees2 (

id NUMBER,

first_name VARCHAR2(10),

last_name VARCHAR2(10),

salary NUMBER(9,2),

comm1 NUMBER(3),

comm2 NUMBER(3),

salary1 AS (ROUND(salary*(1+comm1/100),2)),

salary2 NUMBER GENERATED ALWAYS AS (ROUND(salary*(1+comm2/100),2)) VIRTUAL,

CONSTRAINT employees_pk PRIMARY KEY (id)

);

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To the following PostgreSQL statements:

CREATE TABLE IF NOT EXISTS TEST_ORA_PG.employees2 (

id DOUBLE PRECISION NOT NULL,

first_name character varying(10),

last_name character varying(10),

salary NUMERIC(9,2),

comm1 NUMERIC(3,0),

comm2 NUMERIC(3,0),

salary1 DOUBLE PRECISION,

salary2 DOUBLE PRECISION

);

ALTER TABLE TEST_ORA_PG.EMPLOYEES2

ADD CONSTRAINT EMPLOYEES_PK PRIMARY KEY (ID);

CREATE OR REPLACE FUNCTION TEST_ORA_PG.f_trigger_vc$employees2 ()

RETURNS trigger

$BODY$

BEGIN

new.salary1 := ROUND(new.salary*(1+new.comm1/100),2);

new.salary2 := ROUND(new.salary*(1+new.comm2/100),2); return NEW;

END;

$BODY$

LANGUAGE plpgsql;

CREATE TRIGGER trigger_vc$employees2 before insert or update on TEST_ORA_PG.employees2

for each row

EXECUTE PROCEDURE TEST_ORA_PG.f_trigger_vc$employees2();

Issue 5213: PostgreSQL expands fractional seconds support for TIME, DATETIME, and TIMESTAMP values, with up to microseconds (6 digits) of precision

Review your transformed code and modify it if necessary to avoid a loss of accuracy.

Issue 5552: PostgreSQL expands fractional seconds support for TIME, DATETIME, and TIMESTAMP values, with up to microseconds (6 digits) of precision

Review your transformed code and modify it if necessary to avoid a loss of accuracy.

Issue 5553: PostgreSQL expands fractional seconds support for TIME, DATETIME, and TIMESTAMP values, with up to microseconds (6 digits) of precision

Review your transformed code and modify it if necessary to avoid a loss of accuracy.

Issue 5551: PostgreSQL doesn't have a data type UROWID

Review your transformed code and modify it if necessary to use a diﬀerent data type.

Related Topics

•

•

•

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Conversion Issues with CREATE TYPE

Issue 5572: PostgreSQL doesn't support object type methods

Revise your architecture with a custom solution for the user type.

Related Topics

•

•

•

Conversion Issues with CURSOR

Issue 5084: PostgreSQL doesn't support the cursor attribute %ISOPEN

Revise how you are using this attribute in your code.

Issue 5226: PostgreSQL doesn't support TYPE ... IS REF CURSOR

PostgreSQL doesn't support the TYPE <type_name> IS REF CURSOR statement. Change the function to a stored procedure and try using a table to store results instead.

Related Topics

•

•

•

Conversion Issues with Datetime Expressions

Issue 5594: PostgreSQL doesn't support %s datetime expression. The loss of precision and/or accuracy of data is possible

PostgreSQL doesn't support the AT LOCAL or AT TIME ZONE <time_zone> datetime expressions. Review your code and modify it if necessary.

Related Topics

•

•

•

Conversion Issues with DELETE

Issue 5067: PostgreSQL doesn't support the DELETE statement with the ERROR

LOG option

You can add error records by inserting them into the log in the exception block. Iterate through the errors in the exception block, add them to the log, and use the EXIT command when ﬁnished.

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Issue 5098: PostgreSQL doesn't support the DELETE statement for a PARTITION

Either insert data into the overlying partition, or perform a manual conversion using the DELETE statement.

Issue 5068: PostgreSQL doesn't support the DELETE statement for a subquery

Perform this operation on the underlying tables instead.

Related Topics

•

•

•

Conversion Issues with DYNAMIC SQL

Issue 5088: PostgreSQL doesn't support the EXECUTE IMMEDIATE statement with BULK COLLECT

Perform a manual conversion.

Issue 5334: PostgreSQL doesn't support the dynamic SQL statement

Review and modify the execution string.

Issue 5087: PostgreSQL doesn't support the RETURNING BULK COLLECT INTO clause

Perform a manual conversion.

Related Topics

•

•

•

Conversion Issues with EXCEPTION

Issue 5561: PostgreSQL doesn't support the ACCESS_INTO_NULL exception

Review the exception used, and if possible convert it to another condition.

Issue 5562: PostgreSQL doesn't support the COLLECTION_IS_NULL exception

Review the exception used, and if possible convert it to another condition.

Issue 5580: The exception block was emptied after conversion

Check converted code and make manual corrections if necessary.

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Issue 5570: PostgreSQL doesn't support exception name declaration

Review the exception used, and if possible convert it to another condition.

Issue 5563: PostgreSQL doesn't support the NO_DATA_NEEDED exception

Review the exception used, and if possible convert it to another condition.

Issue 5560: PostgreSQL doesn't support the PROGRAM_ERROR exception

Review the exception used, and if possible convert it to another condition.

Issue 5564: PostgreSQL doesn't support the ROWTYPE_MISMATCH exception

Review the exception used, and if possible convert it to another condition.

Issue 5565: PostgreSQL doesn't support the SELF_IS_NULL exception

Review the exception used, and if possible convert it to another condition.

Issue 5566: PostgreSQL doesn't support the SUBSCRIPT_BEYOND_COUNT exception

Review the exception used, and if possible convert it to another condition.

Issue 5567: PostgreSQL doesn't support the SUBSCRIPT_OUTSIDE_LIMIT exception

Review the exception used, and if possible convert it to another condition.

Issue 5568: PostgreSQL doesn't support the SYS_INVALID_ROWID exception

Review the exception used, and if possible convert it to another condition.

Related Topics

•

•

•

Conversion Issues with EXPLICIT CURSORS

Issue 5559: PostgreSQL doesn't support the RETURN TYPE for the cursor

PostgreSQL doesn't support specifying a return type for a cursor. Declare the cursor without this statement.

Related Topics

•

•

•

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Conversion Issues with FUNCTION

Issue 5350: The function can't use statements that explicitly or implicitly begin or end a transaction, such as START TRANSACTION, COMMIT, or ROLLBACK

Revise your code to implement transaction control on the application side. Some cases that use

SAVEPOINT <name>… ROLLBACK TO <name> can be converted to BEGIN … EXCEPTION … END.

Related Topics

•

•

•

Conversion Issues with INSERT

Issue 5070: PostgreSQL doesn't support the INSERT statement with the ERROR

LOG option

You can add error records by inserting them into the log in the exception block. Iterate through the errors in the exception block, add them to the log, and use the EXIT command when ﬁnished.

Issue 5024: PostgreSQL doesn't support the INSERT statement with partition_extension_clause

Perform a manual conversion for the partition types that aren't supported.

Issue 5071: PostgreSQL doesn't support the INSERT statement for a subquery

Perform this operation on the underlying tables instead.

Issue 5090: PostgreSQL doesn't support the INSERT statement for a

SUBPARTITION

Either insert data into the overlying partition, or perform a manual conversion using the INSERT statement.

Related Topics

•

•

•

Conversion Issues with MATERIALIZED VIEW

Issue 5094: PostgreSQL doesn't support a materialized VIEW

Revise your code to replace the CREATE MATERIALIZED VIEW statement with another solution.

Issue 5095: PostgreSQL doesn't support using a materialized VIEW

Revise your code to replace the materialized view with another solution.

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Related Topics

•

•

•

Conversion Issues with MERGE

Issue 5102: PostgreSQL doesn't support the MERGE statement

To achieve the eﬀect of a MERGE statement, use separate INSERT, DELETE, and UPDATE statements.

Related Topics

•

•

•

Conversion Issues with Optimizer Hints

Issue 5103: PostgreSQL doesn't support the %s hint

Use PostgreSQL methods for performance tuning.

Related Topics

•

•

•

Conversion Issues with PACKAGES

Issue 5330: PostgreSQL doesn't support global cursors

Use another method for this functionality.

Issue 5331: PostgreSQL doesn't support a global user exception

Use another method for this functionality.

Issue 5569: PostgreSQL only supports session variables using SQL standard date and time types

If your code uses variables of other types, such as associative arrays, cursors, ref cursors, or subtypes, revise your architecture with a custom solution for replacing that type.

Related Topics

•

•

•

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Conversion Issues with Parser Error

Issue 5293: Unable to resolve the object

Verify if object <object_name> is present in the database. If it isn't, check the object name or add the object. If the object is present, transform the code manually.

Related Topics

•

•

•

Conversion Issues with PRAGMA

Issue 5571: PostgreSQL doesn't support PRAGMA options

Review the exception used, and if possible convert it to another condition.

Related Topics

•

•

•

Conversion Issues with SELECT

Issue 5140: PostgreSQL doesn't support BULK COLLECT INTO

Include all of the ﬁelds from your table in an INTO clause instead.

Issue 5139: PostgreSQL doesn't support FOR UPDATE SKIP LOCKED

Try using FOR UPDATE without SKIP LOCKED.

Issue 5144: PostgreSQL doesn't support FOR UPDATE WAIT clauses

Try using FOR UPDATE without WAIT.

Issue 5586: Automatic conversion for queries with NOCYCLE clause not supported

Perform a manual conversion.

Issue 5126: PostgreSQL doesn't support the MODEL statement

Revise your code. Try using user procedures and temporary tables instead.

Issue 5585: Automatic conversion of an outer join into a correlation query is not supported

Perform a manual conversion.

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Issue 5557: PostgreSQL doesn't support GROUPING SETS, CUBE, and ROLLUP functions

These functions can be emulated using CTE expressions instead. GROUPING SETS, CUBE, and ROLLUP functionality is available in PostgreSQL v.9.5 or higher.

Issue 5578: Unable to automatically transform the SELECT statement

The indicated SELECT statement contains language that can't be converted, for example an unsupported function. Try rewriting the statement.

Related Topics

•

•

•

Conversion Issues with SEQUENCE

Issue 5574: PostgreSQL doesn't support the sequence's status

Check the original sequence for errors, and perform the conversion again.

Related Topics

•

•

•

Conversion Issues with Statements

Issue 5335: PostgreSQL doesn't support the GOTO operator

PostgreSQL doesn't support the GOTO operator in stored procedures. Try one of the following alternatives instead:

• Set a ﬂag and test for it.

• Return from the procedure if updates should be made, and add the updates after the return.

• Put the updates in another stored procedure, and call it in your IF statements.

Related Topics

•

•

•

Conversion Issues with Synonym

Issue 5333: This object uses a private synonym

Check that a referenced object created after synonym conversion exists.

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Issue 5592: This object uses a public synonym which references a table, a view, or a function

Check that a referenced object created after synonym conversion exists.

Issue 5593: This object uses a public synonym which doesn't reference any other objects

Check that a referenced object created after synonym conversion exists.

Related Topics

•

•

•

Conversion Issues with System Package

Issue 5503: MySQL does not have functionality similar to %s module

Try using Amazon Simple Workﬂow (Amazon SWF). For more information, see What Is Amazon Simple

Workﬂow Service?

in the Amazon Simple Workﬂow Service Developer Guide.

Issue 5502: MySQL does not have functionality similar to %s module

Try using AWS Snowball. For more information, see What Is AWS Snowball?

Issue 5501: MySQL does not have functionality similar to %s module

Try using the AWS Lambda service with Scheduled Events. For more information, see What Is AWS

Lambda?

Issue 5500: MySQL does not have functionality similar to %s module

Try using the Amazon Simple Queue Service (Amazon SQS). For more information, see What is Amazon

Simple Queue Service?

Related Topics

•

•

•

Conversion Issues with TRIGGERS

Issue 5313: PostgreSQL doesn't support the action-type clause

Use another method for this functionality.

Issue 5415: PostgreSQL doesn't support system triggers

Revise your code to replace system triggers with another solution.

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Issue 5311: PostgreSQL doesn't support system triggers

Revise your code to replace system triggers with another solution.

Issue 5242: PostgreSQL doesn't support COMPOUND TRIGGER

Create a single trigger for each part of the compound trigger.

Issue 5241: PostgreSQL doesn't support the FOLLOWS | PRECEDES clause

Try using the FOR EACH ROW trigger.

Issue 5240: PostgreSQL doesn't support triggers on nested table columns in views

Revise your code to replace the nested table with another solution.

Issue 5238: PostgreSQL doesn't support the REFERENCING clauses

Modify references to pseudo-rows to use OLD and NEW instead.

Issue 5317: PostgreSQL doesn't support the PARENT referencing clause

Use another method for this functionality.

Issue 5306: Transformation from invalid trigger

Check the original trigger for errors, and perform the conversion again.

Issue 5556: PostgreSQL doesn't support conditional predicates

Revise your code and try using simple triggers instead.

Related Topics

•

•

•

Conversion Issues with TRUNCATE TABLE

Issue 5298: PostgreSQL doesn't support the DROP STORAGE clause in the

TRUNCATE statement

Use the TRUNCATE TABLE statement without this option.

Issue 5300: PostgreSQL doesn't support the PRESERVE clause in the TRUNCATE statement

Use the TRUNCATE TABLE statement without this option.

Issue 5301: PostgreSQL doesn't support the PURGE clause in the TRUNCATE statement

Use the TRUNCATE TABLE statement without this option.

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Issue 5299: PostgreSQL doesn't support the REUSE STORAGE clause in the

TRUNCATE statement

Use the TRUNCATE TABLE statement without this option.

Related Topics

•

•

•

Conversion Issues with UDT

Issue 5577: PostgreSQL doesn't support a UDT with body

Perform a manual conversion.

Related Topics

•

•

•

Conversion Issues with UDT collection-type arguments

Issue 5120: PostgreSQL doesn't support constructors of the "collection" type

Use the "array" type instead.

Issue 5587: PostgreSQL doesn't support EXTEND method with parameters

Perform a manual conversion.

Issue 5121: PostgreSQL doesn't support the FORALL statement

Use a FOR LOOP statement instead.

Issue 5118: PostgreSQL doesn't support table type variables

Use the "array" type instead.

Related Topics

•

•

•

Conversion Issues with Universal

Issue 5339: The %s object is invalid

Revise the original source code to make the speciﬁed object valid.

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Issue 5591: The %s synonym is system

Perform a manual conversion.

Related Topics

•

•

•

Conversion Issues with Unknown

Issue 5025: This syntactic element conversion is not supported yet

Perform a manual conversion.

Issue 5351: Automatic conversion of %s object is not supported

Perform a manual conversion.

Issue 5576: Unparsed SQL

Perform a manual conversion.

Related Topics

•

•

•

Conversion Issues with UPDATE

Issue 5064: PostgreSQL doesn't support the UPDATE statement with the ERROR

LOG option

You can add error records by inserting them into the log in the exception block. Iterate through the errors in the exception block, add them to the log, and use the EXIT command when ﬁnished.

Issue 5558: PostgreSQL doesn't support the UPDATE statement for a PARTITION

Either insert data into the overlying partition, or perform a manual transformation using the UPDATE statement.

Issue 5065: PostgreSQL doesn't support the UPDATE statement for a subquery

Perform this operation on the underlying tables instead.

Related Topics

•

•

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•

Conversion Issues with VIEW

Issue 5245: PostgreSQL doesn't support views with nested table columns

Revise your code to replace the nested table with another solution.

Issue 5583: PostgreSQL doesn't support constraints for view

Perform a manual conversion.

Issue 5321: PostgreSQL doesn't support the object view

Perform a manual conversion.

Issue 5077: PostgreSQL doesn't support the PIVOT clause for the SELECT statement

You can use a stored procedure to prepare data, and then return the data with a view.

Issue 5320: PostgreSQL doesn't support the view with invalid status

Perform a manual conversion.

Issue 5322: PostgreSQL doesn't support the typed view

Perform a manual conversion.

Issue 5075: PostgreSQL doesn't support VIEW with the READ ONLY option

Create the view without this option instead.

Related Topics

•

•

•

Related Topics

•

•

Issue 6115: MySQL doesn't support expressions in

PostgreSQL to MySQL Supported Schema

Conversion

The following sections list the schema elements from a PostgreSQL database and whether they are supported for automatic conversion to MySQL using the AWS Schema Conversion Tool.

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DDL

Statements

Tables

Clause Automatically

Converted

Details

ALTER TABLE Yes

Auto-incremented columns Yes

Columns with default values

Partial

DEFAULT constraints, so they are converted to a BEFORE

INSERT trigger (p. 370)

CREATE TABLE

Deferrable constraints

Yes

Partial

Issue 6111: MySQL doesn't support deferrable constraints (p. 370)

DROP TABLE

Expression as default value for column

Yes

Partial

Issue 6115: MySQL doesn't support expressions in

DEFAULT constraints, so they are converted to a BEFORE

INSERT trigger (p. 370)

Foreign keys

Not-null columns

Partial

Issue 6117: Unable to keep the NOT NULL constraint for

%s column while converting its DEFAULT constraint based on an expression (p. 371)

Issue 6114: MySQL doesn't support SET DEFAULT as a referential action in foreign keys (p. 370)

Issue 6117: Unable to keep the NOT NULL constraint for

%s column while converting its DEFAULT constraint based on an expression (p. 371)

Primary keys

Regular tables

Table inheritance

Yes

Tables with check constraints

Partial

Issue 6108: MySQL doesn't support inherited tables (p. 371)

Issue 6113: MySQL doesn't support check constraints; the source constraint is converted to a conditional error raising in triggers (p. 370)

Tables with exclusion constraints

Tables without columns

Trigger disablement

Partial

Issue 6112: MySQL doesn't support exclusion constraints (p. 370)

Issue 6109: MySQL doesn't support typed tables (p. 372)

Issue 6087: MySQL doesn't support disabling triggers (p. 372)

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DML

Clause

Typed tables

Unique keys

Unlogged tables

Automatically

Converted

Details

Issue 6110: MySQL doesn't support tables without columns (p. 371)

Issue 6120: MySQL doesn't support user-deﬁned data types (p. 374)

Yes

Issue 6107: MySQL doesn't support unlogged tables (p. 371)

DML

Built-In SQL Functions

Aggregate

Clause

All

Automatically

Converted

Details

Partial

Issue 6667: MySQL doesn't support the %s function (p. 357)

Character

Clause

All

Automatically

Converted

Details

Partial

Issue 6667: MySQL doesn't support the %s function (p. 357)

Conversion

Clause

All

Automatically

Converted

Details

Partial

Issue 6667: MySQL doesn't support the %s function (p. 357)

DateTime

Clause

All

Automatically

Converted

Details

Partial

Issue 6667: MySQL doesn't support the %s function (p. 357)

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DML

Numeric

Clause

All

Automatically

Converted

Details

Partial

Issue 6667: MySQL doesn't support the %s function (p. 357)

Other

Clause

All

Automatically

Converted

Details

Partial

Issue 6667: MySQL doesn't support the %s function (p. 357)

Window

Clause

All

Automatically

Converted

Details

Issue 6667: MySQL doesn't support the %s function (p. 357)

XML

Clause

All

Automatically

Converted

Details

Issue 6667: MySQL doesn't support the %s function (p. 357)

Joins

TRUNCATE TABLE

Clause Automatically

Converted

Details

[NATURAL ] [ INNER ] JOIN Yes

[NATURAL ] {LEFT |RIGHT |

FULL } [ OUTER ] JOIN

Yes

CROSS JOIN Yes

USING ( join_column [, ...] ) Yes

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DML

Operators and Date Functions

Bit String Operators

Clause

||,&,|,#,~,<<,>>,

Automatically

Converted

Details

Yes

Date/Time Operators

Clause

+,-,*,/

Automatically

Converted

Details

Partial

Issue 6660: Unable to convert the %s operation with the interval value as one or more arguments (p. 365)

Issue 6661: The operation will return the number of days instead of the interval value (p. 365)

Mathematical Operators

Clause Automatically

Converted

Details

+,-,*,/,

%,^,|/,||/,!,!!,@,&,|,#,~,<<,>>,

Yes

String Operators

Clause

Automatically

Converted

Details

Yes

Predicates

SIMILAR Predicate

Clause

SIMILAR

Automatically

Converted

Details

Issue 6607: Could not convert pattern to MySQL version; check pattern manually (p. 367)

Boolean Conditions

Clause

All

Automatically

Converted

Details

Yes

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DML

Comparison Condition

Clause

'=, <>, <, <=, >, >=

ANY, SOME, ALL

Automatically

Converted

Details

Yes

Exists Conditions

Clause

EXISTS

In Conditions

Clause

Automatically

Converted

Details

Yes

Automatically

Converted

Details

Yes

Null Conditions

Clause

NULL

Automatically

Converted

Details

Yes

Pattern-Matching Conditions

Clause

All

Automatically

Converted

Details

Yes

Range Conditions

Clause

All

Automatically

Converted

Details

Yes

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DML

Set Operators

Text Search Functions and Operators

Clause

EXCEPT

INTERSECT

UNION

Automatically

Converted

Details

Yes

Statements

INSERT

Clause

INSERT INTO table

DEFAULT VALUES;

INSERT INTO table query;

INSERT INTO table

VALUES() RETURNING *;

INSERT INTO table

VALUES() RETURNING

{output_expression [ AS output_name ] [, ...]};

INSERT INTO table

VALUES();

INSERT INTO table

VALUES({ expression

| DEFAULT }

[, ...] ),VALUES({ expression |

DEFAULT } [, ...] ) [, ...];

INSERT INTO table

VALUES({ expression |

DEFAULT } [, ...] );

INSERT INTO table(array)

VALUES({'{' '}[,..]'});

INSERT INTO table[( column [, ...] )]

VALUES();

WITH RECURSIVE with_query [, ...]

UPDATE table_name

SET { column_name =

Automatically

Converted

Details

Yes

Issue 6172: MySQL doesn't support the INSERT statement with the RETURNING option (p. 363)

Issue 6127: MySQL doesn't support the WITH RECURSIVE clause (p. 368)

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DML

Clause

{ expression | DEFAULT }}

[, ...]

WITH with_query [, ...]

UPDATE table_name

SET { column_name =

{ expression | DEFAULT }}

[, ...]

Automatically

Converted

Details

Yes

SELECT

Clause

Add or subtract operators

EXCEPT [ALL]

FROM [ONLY] tablename

[*]

FROM { with_query_name | function_name()}

FROM {(subquery) [ AS ] alias |(VALUES({ expression

| DEFAULT } [, ...])) [ AS ] alias }

FROM tablename [ [ AS ] alias ]

GROUP BY

HAVING

INTERSECT [ALL]

Yes

Partial

LIMIT { count | ALL }

OFFSET start { ROW |

ROWS }

OFFSET start { ROW |

ROWS } FETCH { FIRST |

NEXT } [ count ] { ROW |

ROWS } ONLY

ORDER BY [ ASC | DESC |

USING operator ] [ NULLS

{ FIRST | LAST } ] [, ...]

Partial

Yes

SELECT {* | expression

[ [ AS ] output_name ] [, ...]}

FROM table

Yes

Automatically

Converted

Details

Yes

Partial

Issue 6612: Query with INTERSECT/EXCEPT ALL operator was transformed (p. 363)

Issue 6603: Can't use function in from clause (p. 361)

Issue 6612: Query with INTERSECT/EXCEPT ALL operator was transformed (p. 363)

Issue 6611: LIMIT/OFFSET option was omitted (p. 364)

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DML

Clause Automatically

Converted

Details

Yes SELECT {expression [ [ AS ] output_name ] [, ...]}

SELECT ALL

SELECT DISTINCT

SELECT DISTINCT ON

UNION [ALL]

Yes

WHERE (ﬁeld_name1,

…,ﬁeldnameN) IN

Yes

(subquery_with_multiple_ﬁelds)

WHERE comparison_condition

(=;<>;!

=;<;>;>=;<=;ANY;SOME;ALL)

Yes

WHERE Yes compound_condition_with_or_and_not

WHERE ﬁeld_name

BETWEEN arg1 AND arg2

Yes

Yes WHERE ﬁeld_name IN

(const1,...,constN)

WHERE ﬁeld_name IN

(subquery)

WHERE like_condition

(operator LIKE)

WITH RECURSIVE with_query [, ...]

WITH with_query [, ...]

Yes

Issue 6127: MySQL doesn't support the WITH RECURSIVE clause (p. 368)

WINDOW DEFINITION

DELETE

Clause Automatically

Converted

Details

Issue 6672: MySQL does not support delete by cursor (p. 360)

DELETE FROM table_name

WHERE CURRENT OF cursor_name

DELETE FROM table_name

FROM from_list WHERE condition

Yes

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DML

Clause

DELETE FROM table_name RETURNING

{output_expression [ AS output_name ] [, ...]}

DELETE FROM table_name

RETURNING *

DELETE FROM table_name

WHERE condition

DELETE FROM ONLY table

[ [ AS ] alias ]

DELETE FROM table [ [ AS ] alias ]

DELETE FROM table *

[ [ AS ] alias ]

Automatically

Converted

Details

Issue 6069: MySQL doesn't support the DELETE statement with the RETURNING option (p. 359)

Yes

Issue 6069: MySQL doesn't support the DELETE statement with the RETURNING option (p. 359)

Issue 6603: Can't use function in from clause (p. 361)

SELECT

Clause

[ existing_window_name ]

[ PARTITION BY expression

[, ...] ] [ ORDER BY expression [ ASC | DESC |

USING operator ] [ NULLS

{ FIRST | LAST } ] [, ...] ]

[ frame_clause ]

Automatically

Converted

Details

Issue 6678: MySQL doesn't support function %s with

OVER/ORDER BY/WITHIN GROUP/FILTER clause (p. 356)

UPDATE

Clause

UPDATE ONLY table_name

SET { column_name =

{ expression | DEFAULT }}

[, ...]

UPDATE table_name *

SET { column_name =

{ expression | DEFAULT }}

[, ...]

UPDATE table_name [ [ AS ] alias ] SET { column_name

= { expression | DEFAULT }}

[, ...]

Automatically

Converted

Details

Yes

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DML

Clause

UPDATE table_name

SET { column_name =

{ expression | DEFAULT }}

[, ...]

UPDATE table_name

SET { column_name =

{ expression | DEFAULT }}

[, ...] WHERE CURRENT OF cursor_name

UPDATE table_name

SET { column_name =

{ expression | DEFAULT }}

[, ...] FROM from_list

WHERE condition

UPDATE table_name

SET { column_name =

{ expression | DEFAULT }}

[, ...] RETURNING

{output_expression [ AS output_name ] [, ...]}

UPDATE table_name

SET { column_name =

{ expression | DEFAULT }}

[, ...] RETURNING *

UPDATE table_name

SET { column_name =

{ expression | DEFAULT }}

[, ...] WHERE condition

UPDATE table_name SET

{( column_name [, ...] ) =

( { expression | DEFAULT }

[, ...] ) } [, ...]

UPDATE table_name SET

{( column_name [, ...] ) =

( query ) }

WITH RECURSIVE with_query [, ...]

UPDATE table_name

SET { column_name =

{ expression | DEFAULT }}

[, ...]

WITH with_query [, ...]

UPDATE table_name

SET { column_name =

{ expression | DEFAULT }}

[, ...]

Automatically

Converted

Details

Yes

Partial

Yes

Issue 6672: MySQL does not support delete by cursor (p. 360)

Issue 6669: FROM clause was rewritten (p. 375)

Issue 6066: MySQL doesn't support the UPDATE statement with the RETURNING option (p. 375)

Issue 6127: MySQL doesn't support the WITH RECURSIVE clause (p. 368)

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PL/pgSQL

Basic Statements

Assignment

Clause

Variable assignment

Automatically

Converted

Details

Partial

Issue 6668: MySQL doesn't support ROW/RECORD type (p. 367)

Executing a Command with No Result

Clause

PERFORM

Automatically

Converted

Details

Yes

Executing a Query with a Single-Row Result

Clause

INTO

Automatically

Converted

Details

Issue 6668: MySQL doesn't support ROW/RECORD type (p. 367)

Executing Dynamic Commands

Clause

EXECUTE, INTO, STRICT,

USING

Automatically

Converted

Details

Issue 6334: MySQL doesn't support the dynamic SQL statement RETURN QUERY EXECUTE (p. 360)

Related Topics

•

•

•

Conversion Issues with ALTER

Issue 6676: Automatic conversion of the ALTER statement isn't supported

Perform a manual conversion.

Related Topics

•

•

•

Conversion Issues with Arithmetic Operators

Issue 6681: Unable to perform an automated migration of arithmetic operations with string and other types

Arithmetic operations that use a string type as one of the operands can't be automatically converted.

Modify the code to cast values as the intended type.

Related Topics

•

•

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Conversion Issues with ARRAY

Issue 6608: MySQL doesn't support arrays

Perform a manual conversion.

Related Topics

•

•

•

Conversion Issues with Buildin Function

Issue 6677: MySQL does not support time zone

Perform a manual conversion.

Related Topics

•

•

•

Conversion Issues with Built-In SQL Functions

Issue 6667: MySQL doesn't support the %s function

Create a user-deﬁned function instead.

Related Topics

•

•

•

Conversion Issues with CREATE

Issue 6094: Unable to convert object due to %s not created

Review the %s object.

Related Topics

•

•

•

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Conversion Issues with CURSOR

Issue 6639: MySQL doesn't support the direction clause

MySQL doesn't support the following direction clauses when using FETCH with cursors:

• ABSOLUTE 2

• BACKWARD

• FIRST FROM

• FORWARD

• LAST FROM

• PRIOR FROM

• RELATIVE 2

• RELATIVE 3

Perform a manual conversion in these cases.

Issue 6640: MySQL doesn't support the MOVE option

Revise your code to eliminate cursors with the MOVE option.

Issue 6638: MySQL doesn't support the SCROLL option in cursors

Revise your code to eliminate cursors with the SCROLL option.

Issue 6337: MySQL doesn't support a variable of REFCURSOR type

Try revising the code to use temporary tables instead.

Related Topics

•

•

•

Conversion Issues with Databases

Issue 6101: MySQL doesn't support this clause in an ALTER DATABASE statement

Perform a manual conversion.

Issue 6100: The database-to-database migration is not provided

Use the schema-to-database migration plan instead.

Related Topics

•

•

•

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Conversion Issues with DATA TYPES

Issue 6673: MySQL doesn't support %s type in the CAST function, and a loss of precision or accuracy of data is possible

Statements that cast values to any of the following data types are converted to statements that cast values to CHAR:

• BYTEA

• CIDR

• JSON

• int4range

For example, take the following PostgreSQL statements.

select '1'::BYTEA select CAST('1' AS BYTEA)

These are both converted to the following MySQL statement.

select CAST('1' AS CHAR)

Review the converted code and revise it if necessary.

Issue 6674: MySQL doesn't support %s type in the CAST function

Statements that cast a value to the TXID_SNAPSHOT data type are converted to statements that cast a value to CHAR. For example, take the following PostgreSQL statements.

select '2628:2628:'::TXID_SNAPSHOT select CAST('2628:2628:' AS TXID_SNAPSHOT)

These are both converted to the following MySQL statement: select CAST('2628:2628:' AS CHAR)

Review the converted code and revise it if necessary.

Related Topics

•

•

•

Conversion Issues with DELETE

Issue 6069: MySQL doesn't support the DELETE statement with the RETURNING option

To convert this operation, change the DELETE statement with the RETURNING clause into a DELETE statement with following INSERT statements, and use the same key conditions in each INSERT.

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Issue 6672: MySQL does not support delete by cursor

MySQL doesn't support using a DELETE statement within a cursor. Perform a manual conversion in this case.

Related Topics

•

•

•

Conversion Issues with Domains

Issue 6050: MySQL doesn't support domains

Perform a manual conversion.

Related Topics

•

•

•

Conversion Issues with Dynamic SQL

Issue 6334: MySQL doesn't support the dynamic SQL statement RETURN QUERY

EXECUTE

Review and modify the execution string.

Related Topics

•

•

•

Conversion Issues with Error Handling

Issue 6665: MySQL doesn't support the GET [ CURRENT ] DIAGNOSTICS command

Perform a manual conversion.

Issue 6664: MySQL doesn't support the condition information %s

Some of the condition information items that are used with the GET STACKED DIAGNOSTICS statement in PostgreSQL are not supported by MySQL. These include the following:

• PG_DATATYPE_NAME

• TABLE_NAME

• SCHEMA_NAME

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• PG_EXCEPTION_DETAIL

• PG_EXCEPTION_HINT

• PG_EXCEPTION_CONTEXT

Manually convert the code wherever you use these condition information items.

Issue 6329: MySQL doesn't support the RAISE exception

Review the RAISE exception used, and if possible convert it to an exception using the SIGNAL or

RESIGNAL statement.

Related Topics

•

•

•

Conversion Issues with Exceptions

Issue 6342: MySQL doesn't support the %s condition name

Review the exception used, and if possible convert it to an exception using the SIGNAL or RESIGNAL statement.

Related Topics

•

•

•

Conversion Issues with FROM

Issue 6603: Can't use function in from clause

Code that selects from a function, for example

SELECT * FROM function_name;

, isn't converted. Perform a manual conversion in this case.

Issue 6682: Can't use the table-value function in the from clause

MySQL does not support the table-value function. Perform a manual conversion in this case.

Related Topics

•

•

•

Conversion Issues with FUNCTION

Issue 6675: Automatic conversion function on %s language isn't supported

Perform a manual conversion.

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Issue 6613: Unable to convert a function without OUT parameters returning a

RECORD type

Perform a manual conversion.

Related Topics

•

•

•

Conversion Issues with Functions

Issue 6604: MySQL doesn't support RETURN NEXT clause

Perform a manual conversion.

Issue 6605: MySQL doesn't support VARIADIC mode of an argument

Perform a manual conversion.

Related Topics

•

•

•

Conversion Issues with Indexes

Issue 6091: MySQL doesn't support %s index method

The InnoDB engine in MySQL doesn't support HASH and ON table_name indexes. Perform a manual conversion in these cases.

Issue 6090: MySQL doesn't support indexes on expressions

Perform a manual conversion.

Issue 6092: MySQL doesn't support explicit sort ordering in the index deﬁnition

Indexes that use explicit sort ordering are converted to use the default (ascending) sort order instead. If this conversion causes performance degradation, revise the converted code as necessary.

Issue 6093: MySQL doesn't support partial indexes

Partial indexes are converted to full indexes instead. For example, take the following PostgreSQL statement.

CREATE INDEX i_indexed_partial

ON test_pg_mysql.indexed_partial USING btree

( n )

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WHERE ( n < 100 );

The preceding statement is converted to the following MySQL statement:

CREATE INDEX i_indexed_partial

USING BTREE ON test_pg_mysql.indexed_partial

( n );

If this conversion causes performance degradation, revise the converted code as necessary.

Related Topics

•

•

•

Conversion Issues with INSERT

Issue 6172: MySQL doesn't support the INSERT statement with the RETURNING option

To convert this operation, change the INSERT statement with the RETURNING clause into an INSERT statement with following SELECT statements, and use the same key conditions in each SELECT. You can also use the last value that was generated by any AUTO_INCREMENT column in the key condition.

Related Topics

•

•

•

Conversion Issues with INTERSECT, EXCEPT

Issue 6612: Query with INTERSECT/EXCEPT ALL operator was transformed

The EXCEPT ALL and INTERSECT ALL options of the SELECT statement can't be directly converted, so they are converted to other language options that should produce the same results. For example, take the following PostgreSQL statements.

SELECT * FROM customers except all

SELECT * FROM customers;

SELECT * FROM customers intersect all

SELECT * FROM customers;

The preceding statements are converted to the following MySQL statements.

SELECT customers.id, customers.name, customers.surname, customers.postcode FROM customers where (customers.id, customers.name, customers.surname, customers.postcode)

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PostgreSQL to MySQL Conversion Reference not in (SELECT customers.id, customers.name, customers.surname, customers.postcode FROM

customers);

SELECT customers.id, customers.name, customers.surname, customers.postcode

FROM customers inner join (SELECT customers.id, customers.name, customers.surname,

customers.postcode FROM customers) nn on (customers.id=nn.id or (customers.id is null and nn.id is null))

and customers.name=nn.name

and (customers.surname=nn.surname or (customers.surname is null and nn.surname is null))

and (customers.postcode=nn.postcode or (customers.postcode is null and nn.postcode is

null));

Review the converted code, and revise it if necessary.

Related Topics

•

•

•

Conversion Issues with LABEL

Issue 6344: MySQL doesn't support labeled variables

Try rewriting variables without using labels.

Related Topics

•

•

•

Conversion Issues with LIMIT

Issue 6611: LIMIT/OFFSET option was omitted

MySQL doesn't support use of the LIMIT or OFFSET options with the SELECT statement. These options are dropped during conversion. For example, take the following PostgreSQL statement.

SELECT * FROM customers c offset 3;

This statement is converted to the following MySQL statement:

SELECT * FROM customers c;

Review the converted code, and revise it as necessary.

Related Topics

•

•

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Conversion Issues with Materialized Views

Issue 6130: MySQL doesn't support materialized views; the source materialized view is converted to a table with triggers

Review the converted code to make sure it meets your needs, and revise it if necessary.

Related Topics

•

•

•

Conversion Issues with Messages from Stored Routines

Issue 6332: MySQL doesn't support the RAISE statement to report messages

Try using INSERT to write a message to a log table instead. To do this, you must add code in one of the following tables in the AWS_POSTGRESQL_EXT schema (the temporary work schema used for

PostgreSQL):

• RAISE_DEBUG

• RAISE_LOG

• RAISE_INFO

• RAISE_NOTICE

• RAISE_WARNING

Related Topics

•

•

•

Conversion Issues with Operators and Date Functions

Issue 6660: Unable to convert the %s operation with the interval value as one or more arguments

Some operations with arguments that use an interval data type can't be converted, for example

SELECT

INTERVAL '1-1' YEAR TO MONTH * 2;

. Perform a manual conversion in this case.

Issue 6661: The operation will return the number of days instead of the interval value

After conversion, some calculations that use date or time data types return the number of days rather than an interval value as they did previously, for example

SELECT TIMESTAMP '2012-01-01 09:30:15.01'

- DATE '2010-01-01';

. Check to see if the new return type meets your requirements, and revise the code if necessary.

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Issue 6662: Unsupported format for the interval's value

Currently, the only supported format for a literal value assigned to an interval data type is SQL ANSI.

Perform a manual conversion in the case of an unsupported format.

Related Topics

•

•

•

Conversion Issues with ORDER BY

Issue 6610: AI nulls ﬁrst/last transformation was performed

MySQL doesn't support the NULLS FIRST or NULLS LAST options with the SELECT statement. Instances of this language are converted to use the isnull() function instead. For example, take the following

PostgreSQL statements.

SELECT * FROM customers c order by id nulls last;

SELECT * FROM customers c order by id desc nulls first;

These statements are converted to the following MySQL statements.

SELECT * FROM customers c order by isnull(id), id;

SELECT * FROM customers c order by isnull(id) desc, id desc;

Review the converted code, and revise it if necessary.

Issue 6609: ORDER option was omitted because MySQL doesn't support key word USING in order by clause

MySQL doesn't support the ORDER BY ﬁeld_name USING clause, for example

SELECT * FROM customers c order by id using >;

. During conversion, the ORDER BY clause is dropped. Review this code and revise it if necessary.

Related Topics

•

•

•

Conversion Issues with Parser Error

Issue 6663: Unable to resolve the object

Verify if object %s is present in the database. If it isn't, check the object name or add the object. If the object is present, transform the code manually.

Related Topics

•

•

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Conversion Issues with Patterns

Issue 6607: Could not convert pattern to MySQL version; check pattern manually

MySQL doesn't support some pattern matching syntax, for example

SELECT * FROM customers where name similar to 'name';

. Perform a manual conversion in this case.

Related Topics

•

•

•

Conversion Issues with ROW, RECORD type

Issue 6606: MySQL doesn't support ROW() function with any, some, or all predicates

MySQL doesn't support the ROW() function with the any, some, or all predicates, for example

SELECT *

FROM customers c where ROW(c.id, c.postcode) <= all (select id, order_sum from orders where id = c.id);

. Perform a manual conversion instead.

Issue 6668: MySQL doesn't support ROW/RECORD type

Perform a manual conversion.

Related Topics

•

•

•

Conversion Issues with SELECT

Issue 6679: Value don't ﬁxed on start transaction

Review your code, and revise it to use a local variable if necessary.

Related Topics

•

•

•

Conversion Issues with SELECT INTO

Issue 6666: Transformation of not strict into clause was performed

Perform a manual conversion.

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Related Topics

•

•

•

Conversion Issues with SELECT, UPDATE, INSERT, DELETE

Issue 6127: MySQL doesn't support the WITH RECURSIVE clause

Use a stored procedure to prepare data, or rewrite your query to avoid the WITH RECURSIVE clause.

Related Topics

•

•

•

Conversion Issues with Sequences

Issue 6060: MySQL doesn't support sequences

Perform a manual conversion.

Related Topics

•

•

•

Conversion Issues with SQL Functions

Issue 6343: MySQL doesn't support the COLLATE option; automatic conversion cannot be performed

You must use the COLLATION settings that were assigned when the database was created.

Related Topics

•

•

•

Conversion Issues with Table Columns

Issue 6006: MySQL doesn't support %s type

Check the target data type and correct it if necessary.

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Issue 6008: MySQL doesn't support array types for table column deﬁnition

MySQL doesn't support using an array data type for either a table column or a function variable, so this code isn't automatically converted from PostgreSQL. Perform a manual conversion instead.

Issue 6011: MySQL doesn't support CIRCLE as a spatial type; the approximated results of BUFFER function of POLYGON data type is used to perform a conversion

Check the converted code, and revise it if the approximated representation doesn't meet your needs.

Issue 6002: MySQL doesn't support %s with precision more than 65 digits and scale more than 30 digits; the loss of precision or accuracy of data is possible

Check to see if you are converting columns whose numeric data types violate these restrictions. If so, perform a manual migration instead.

Issue 6005: MySQL doesn't support INTERVAL type

Perform a manual conversion of any code that uses this data type.

Issue 6010: MySQL doesn't support inﬁnite lines; a LINESTRING with two points on the line is used for conversion

Any instance of the LINE data type is converted to a LINESTRING data type. If the two-pointed representation is not suitable for your purposes, revise this code.

Issue 6009: MySQL doesn't support range types

MySQL doesn't support range data types like LONGTEXT or VARCHAR(length). Manually convert code that uses these data types instead.

Issue 6001: Unable to provide full migration for auto-increment table columns

The PostgreSQL auto-increment data types SMALLSERIAL, SERIAL and BIGSERIAL are converted to the

MySQL SMALLINT, INT, and BIGINT data types, respectively. If you want to enable auto-incrementing,

MySQL supports only one auto-increment column per table and it must be a key. Choose an appropriate column and manually update it to meet these requirements.

Issue 6003: MySQL doesn't support time zone information for %s type

Perform a manual conversion.

Issue 6004: MySQL doesn't support time zone information for %s type

Perform a manual conversion instead. If the time zone information isn't important, you can choose

DATETIME(6) as a target data type. Otherwise, try to convert the data into TIMESTAMP(6), taking into account the value of time_zone server setting.

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Local Variables

Issue 6012: Converted bit strings are right-padded by zero bits to full-byte length

Review the converted code, and revise it if the approximated representation is not suitable for your needs.

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MySQL doesn't support expressions in DEFAULT constraints, so they are converted to a BEFORE INSERT trigger (p. 370)

Conversion Issues with Tables

Issue 6111: MySQL doesn't support deferrable constraints

Check your schema and ensure that nondeferrable constraints can provide the necessary level of integrity. Otherwise, perform a manual conversion on the constraints.

Issue 6112: MySQL doesn't support exclusion constraints

Perform a manual conversion of the exclusion constraint to provide the same level of data integrity.

Issue 6113: MySQL doesn't support check constraints; the source constraint is converted to a conditional error raising in triggers

In MySQL, check constraints are parsed but ignored. Instead, PostgreSQL check constraints are converted to triggers that ﬁre before INSERT and UPDATE events. Review this code to see if it meets your needs, and if necessary perform a manual conversion of the check constraint to provide the expected level of data integrity.

Issue 6114: MySQL doesn't support SET DEFAULT as a referential action in foreign keys

MySQL doesn't support using SET DEFAULT when creating a foreign key. Any SET DEFAULT statements are converted to SET NULL statements. Review this code and modify it if necessary.

Issue 6115: MySQL doesn't support expressions in DEFAULT constraints, so they are converted to a BEFORE INSERT trigger

MySQL doesn’t support using expressions as default values when creating a table, so during conversion a

BEFORE INSERT trigger is created to insert the default values instead. CHARACTER VARYING columns are converted into TEXT or LONGTEXT columns (depending on the length of the source column), which can't have default values in MySQL. Therefore, any default values in such columns are treated as expressions and are also included in the BEFORE INSERT trigger.

For example, take the following PostgreSQL code.

CREATE TABLE IF NOT EXISTS test_pg_mysql.constraint_default_expression

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( n numeric( 10, 0 ) DEFAULT 12345+98765

, d date DEFAULT now()

, d2 date DEFAULT '2016-01-06'::date

, s character varying (10) DEFAULT 'A string'

);

This code is converted into the following MySQL code.

CREATE TRIGGER constraint_default_expression_bir

BEFORE INSERT

ON test_pg_mysql.constraint_default_expression

FOR EACH ROW

BEGIN

default_values_expr: BEGIN

-- default value for n column

IF NEW.n IS NULL THEN

SET NEW.n = 123456 + 98765;

END IF;

-- default value for d column

IF NEW.d IS NULL THEN

SET NEW.d = now( 6 );

END IF;

-- default value for d2 column

IF NEW.d2 IS NULL THEN

SET NEW.d2 = CAST( '2016-01-06' AS DATE );

END IF;

-- default value for s column

IF NEW.s IS NULL THEN

SET NEW.s = 'A string';

END IF;

END default_values_expr;

END;

Issue 6117: Unable to keep the NOT NULL constraint for %s column while converting its DEFAULT constraint based on an expression

MySQL doesn’t support using expressions as default values when creating a table, so during conversion a BEFORE INSERT trigger is created to insert the default values instead. For more details, see

Issue 6115:

If a column that has a default value and so is converted in this way also has a NOT NULL constraint, the NOT NULL constraint is converted as part of the same trigger rather than remaining as part of the

CREATE TABLE statement.

Issue 6110: MySQL doesn't support tables without columns

MySQL doesn't support using the CREATE TABLE statement without specifying at least one column.

This usage is something you might do when creating a table based on a user-deﬁned type, for example.

Perform a manual conversion instead.

Issue 6107: MySQL doesn't support unlogged tables

Unlogged tables in PostgreSQL are converted to regular tables in MySQL. Review this code to see if it meets your needs, and revise it if necessary.

Issue 6108: MySQL doesn't support inherited tables

Perform a manual conversion.

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Issue 6109: MySQL doesn't support typed tables

Perform a manual conversion.

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Conversion Issues with Triggers

Issue 6083: MySQL doesn't support conditional triggers that ﬁre on updates of particular column(s); a conversion will omit such a condition

MySQL doesn't support conditional triggers that rely on the update of a speciﬁc column. For example, take the following statement in PostgreSQL.

CREATE TRIGGER triggering_cond_bur_of

BEFORE UPDATE OF n

This statement is converted to the following statement in MySQL:

CREATE TRIGGER triggering_cond_bur

BEFORE UPDATE

If you require this functionality, perform a manual conversion instead.

Issue 6082: MySQL doesn't support constraint triggers

MySQL doesn't support constraint triggers, so any CREATE CONSTRAINT TRIGGER statements are converted to CREATE TRIGGER statements. Review this code and modify it if necessary.

Issue 6087: MySQL doesn't support disabling triggers

PostgreSQL allows users to disable table triggers so that they aren't ﬁred, and then re-enable them at a later time. MySQL doesn’t support this, so you must perform a manual conversion of this code.

Issue 6086: Unable to automatically transform dropping a trigger

DROP TRIGGER statements aren't automatically converted. Perform a manual conversion instead.

Issue 6084: MySQL doesn't support INSTEAD OF triggers

Perform a manual conversion.

Issue 6085: MySQL doesn't support multiple triggers on the same event; triggers are merged into one in alphabetical order by trigger name

Multiple triggers on one event are automatically merged into a single trigger, with their functionality inserted into the new trigger in alphabetic order by trigger name. Review this trigger code after conversion and revise it if necessary.

For example, take the following PostgreSQL code.

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CREATE TRIGGER triggering_multiple_inc

BEFORE INSERT

ON test_pg_mysql.triggering_multiple

FOR EACH ROW

EXECUTE PROCEDURE test_pg_mysql.fu_triggering_simple_inc();

CREATE TRIGGER triggering_multiple_inc_2

BEFORE INSERT

ON test_pg_mysql.triggering_multiple

FOR EACH ROW

EXECUTE PROCEDURE test_pg_mysql.fu_triggering_simple_inc();

This code is converted into the following MySQL code.

CREATE TRIGGER triggering_multiple_bir

BEFORE INSERT

ON test_pg_mysql.triggering_multiple

FOR EACH ROW

BEGIN

tr1: BEGIN

-- triggering_multiple_inc

SET NEW.n = NEW.n + 1;

END tr1;

tr2: BEGIN

-- triggering_multiple_inc_2

SET NEW.n = NEW.n + 1;

END tr2;

END;

Issue 6081: MySQL doesn't support triggers ﬁring on multiple events; such a trigger is converted to multiple single-event triggers with the same body

PostgreSQL supports specifying multiple events with the CREATE TRIGGER statement, for example

CREATE TRIGGER trigger_name BEFORE INSERT OR UPDATE. However, MySQL only supports specifying one event, for example CREATE TRIGGER trigger_name BEFORE UPDATE. PostgreSQL triggers that specify multiple events are converted to several triggers with the same trigger body, one for each event speciﬁed. Review this trigger code after conversion and revise it if necessary.

For example, take the following PostgreSQL code.

CREATE TRIGGER

triggering_simple_inc BEFORE INSERT

OR UPDATE ON

test_pg_mysql.triggering_simple FOR EACH

ROW EXECUTE PROCEDURE

test_pg_mysql.fu_triggering_simple_inc();

This code is converted into the following MySQL code:

CREATE TRIGGER triggering_simple_bir

BEFORE INSERT

ON test_pg_mysql.triggering_simple

FOR EACH ROW

BEGIN

tr1: BEGIN

SET NEW.n = NEW.n + 1;

END tr1;

END;

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CREATE TRIGGER triggering_simple_bur

BEFORE UPDATE

ON test_pg_mysql.triggering_simple

FOR EACH ROW

BEGIN

tr1: BEGIN

SET NEW.n = NEW.n + 1;

END tr1;

END;

Issue 6080: MySQL doesn't support statement-level triggers

MySQL doesn't support the FOR EACH STATEMENT clause for CREATE TRIGGER statements. Perform a manual conversion of this code.

Issue 6650: Unable to convert the statement with TG_ARGV automatically

CREATE TRIGGER statements that use TG_ARGV to work with trigger arguments can't be converted.

Perform a manual conversion instead.

Issue 6651: Unsupported using of RETURN statement in the trigger converted to

LEAVE statement

Check ﬂow of execution and perform a manual conversion if necessary.

Issue 6652: MySQL doesn't support OLD record in triggers on INSERT or NEW record in triggers on DELETE

MySQL doesn’t support the NEW variable in triggers that use DELETE, and it also doesn't support the

OLD variable in triggers that use INSERT. In these cases, the variable reference is replaced with NULL For example,

NEW.n > 0

is replaced by

NULL > 0

. Review this code to see if using NULL instead of a ﬁeld of the unsupported record is appropriate, and revise as necessary.

Issue 6088: MySQL doesn't support TRUNCATE event for triggers

Perform a manual conversion.

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Conversion Issues with User-Deﬁned Types

Issue 6120: MySQL doesn't support user-deﬁned data types

Perform a manual conversion of any code involving user-deﬁned types. This conversion should include any references to user-deﬁned types, and also any instances of the CREATE TYPE, ALTER TYPE, or DROP

TYPE statements.

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Conversion Issues with Unknown

Issue 6013: This syntactic element conversion is not supported yet

Perform a manual conversion.

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Conversion Issues with UPDATE

Issue 6669: FROM clause was rewritten

The FROM clause in UPDATE statements is rewritten during PostgreSQL to MySQL conversion. For example, take the following PostgreSQL statement.

update test_pg_mysql.customers c set id = c.id +1, name = o.name,

postcode = o.order_sum from test_pg_mysql.orders o where o.id = c.id;

This statement is converted to the following MySQL statement.

update customers c

set id = c.id +1,

name = (select name from orders where id = c.id),

postcode = (select order_sum from orders where id = c.id)

where c.id in (select id from orders);

Review this code to make sure it produces the results that you expect.

Issue 6066: MySQL doesn't support the UPDATE statement with the RETURNING option

To perform this operation, convert the UPDATE statement with the RETURNING clause into an UPDATE statement with following INSERT statements that have the speciﬁed key conditions in the SELECT clause.

Issue 6670: MySQL does not support update by cursor

MySQL doesn't support updating a table from within a cursor, as shown in the following example.

DECLARE c1 CURSOR FOR SELECT id FROM test_pg_mysql.customers;

val numeric(14,0);

BEGIN

OPEN c1;

fetch c1 into val;

update test_pg_mysql.customers set name = 'nfhr' where current of c1;

CLOSE c1;

END

Perform a manual conversion instead.

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Conversion Issues with User-Deﬁned Aggregate Functions

Issue 6140: Unable to convert user-deﬁned aggregate statements

Perform a manual conversion of any user-deﬁned aggregate functions.

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Conversion Issues with VIEW

Issue 6076: The SELECT statement cannot contain a subquery in the FROM clause

Either rewrite the query that the view is based on so that it doesn't use a subquery, or create an auxiliary table for the subquery.

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Conversion Issues with Views

Issue 6072: MySQL doesn't support default values for the view's column

MySQL doesn't support specifying a default value when creating or altering a view, as shown in the following example.

ALTER VIEW test_pg_mysql.v_default_values

ALTER n SET DEFAULT 10;

If you need this functionality, perform a manual conversion instead.

Issue 6071: MySQL doesn't support row-level security

If the same functionality is necessary, perform a manual conversion instead.

Issue 6070: MySQL doesn't support temporary views or views on temporary tables

Perform a manual conversion instead.

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