DB2 V11.1.1.1 Overview

DB2 V11.1.1.1 Overview

© 2017 IBM Corporation

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Agenda

• What is DB2 11.1.1.1?

• What’s new in DB2 11.1.1.1

⎼

Encryption Enhancements

⎼

Even Greater Availability

⎼

Additional Core Functionality

⎼

Even Greater SQL Compatibility

⎼

Increased Serviceability

⎼

Performance Improvements

⎼

Removal of Limitations

⎼

Support for Additional Operating Systems

http://ibm.box.com/v/DB2v11eBook

⎼

Updates to Data Server Manager

⎼

Updates to the Data Server (DS) Driver and DB2 Connect

• What to know before updating from DB2 11.1 GA


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Why 11.1.1.1 (instead of 11.1.1)?

The official DB2 product signature consists of 4 parts and has the format VV.RR.MM.FF where:

–

VV = Version number

–

RR= Release number

–

MM = Modification number

–

FF = Fix pack number

Until now, the modification value for DB2 LUW has always been

0 (zero)

Traditionally, interfaces that return the product signature have supplied only 3 elements – VV, RR, and FF

It has not always been obvious when a Fix Pack contains new functionality

Starting with this deliverable, the modification value (MM) will be used to indicate the existence of new functionality or behaviors in a fix pack


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DB2 Developer-C Edition

Introduce DB2 Developer-C Edition

–

Freely downloadable just like Express-C

–

Fully functional DB2 database server

• pureScale and DPF deployments

• Compression and BLU Acceleration

Use Limitations

–

For development and non-production only

–

Unsupported edition (non-warranted)

–

Environment limited usage:

• 4 cores, 16GB of memory

• 100GB of data in user tablespaces


DB2 Developer-C Supporting Programs

Sample of Supporting Programs to be included with Developer-C

–

IBM Database Add-ins for Visual Studio

–

IBM Data Server Drivers (all)

–

IBM Tivoli System Automation for Multiplatforms

–

IBM Enterprise Content Management Text Search

–

IBM Security Directory Server

–

IBM Global Security Toolkit

–

IBM Spectrum Scale

–

IBM DB2 Connect Enterprise Edition

–

IBM InfoSphere Data Replication (CDC component)

–

IBM Data Studio

9

DB2 Advanced/Developer supporting programs NOT included

–

IBM Data Server Manager Enterprise Edition

–

IBM InfoSphere Data Architect

–

IBM Cognos Analytics

–

IBM WebSphere Application Server

–

IBM WebSphere MQ


DB2 11.1.1.1 Highlights

Comprehensive Enterprise Security

Enterprise Encryption

• PKCS#11 HSM support

• SSL Encryption for HADR

• Initially available on Linux/x86 only

Higher Availability and Core Capabilities

Even Greater Availability

• Seamless HADR pureScale upgrades

• FORCE_ALL for ADMIN_MOVE_TABLE()

Asynchronous UNDO (technical preview)

Additional Core Functionality

• Workload Manager (WLM) enhancements

• Federation integration and simplification

• DECIMAL and DECFLOAT improvements

More Compatibility and Serviceability

Even Greater SQL Compatibility

• Column support for BOOLEAN data type

• Common table expressions (DB2 for z/OS)

• WITH and SELECT INTO support


• Maximum log file size increased to 64 GB

• Client info in db2diag for lock and lock errors

• Backup image size in event monitor history

10

Column-Organized (BLU) Tables

Performance Improvements

• Synopsis table enhancements (

HTAP

)

• Additional SIMD exploitation

• INSERT from sub-select performance improvements

• Aggregation enhancements, sort elimination

• Additional advantages for SAP

Added Function – Removing Limitations

• Automatic Dictionary Creation on uncommitted data

• ALTER VARCHAR/VARGRAPHIC length support

Additional Operating System Support

DB2 pureScale

• SLES 12, RHEL 6.8 on x86

Ubuntu on z Systems

• Ubuntu 16.04 on zLinux (non-pureScale)

• Text Search support

Windows

• Support for Windows Server 2016


DB2 Native Encryption HSM Support

Support for PKCS #11-compliant Hardware Security Modules

(HSMs) is now available for:

–

Gemalto

(formerly Luna)

Safenet HSM

(firmware version 6.23.0; software version 6.1 and above)

–

Thales nShield Connect+

(software version 11.50)

Simple Key Mgt : a local flat file used for a specific DB2 instance

Enterprise Key Mgt : a centralized key manager or HSM that can be used across many databases, file systems and other uses across an enterprise

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SSL Encryption Between HADR Primary and Standby Servers

• Provides integrated

protection of sensitive data in the log stream

• Enabled via the

HADR_SSL_LABEL database configuration parameter

• All synchronization

modes supported

• Multiple standbys

supported

• Currently works with

Linux on x86 (nonpureScale) platforms only

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Seamless HADR Upgrades for DB2 pureScale Environments

• DB2 pureScale HADR environments can now be upgraded without

having to stop HADR or re-initialize the standby(s)

• Standby databases ‘replay’ upgrades made to the primary

• Not supported with DB2 9.7, 10.1, or 10.5 – Fix Pack 8 or earlier; will

be supported in an upcoming 10.5 Fix Pack

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FORCE_ALL Option For ADMIN_MOVE_TABLE()

The ADMIN_MOVE_TABLE() procedure provides the ability to move data from an active ‘source’ table to a new table object that has the same name, while the table remains online and accessible.

A new FORCE_ALL option enables administrators to avoid potential lock issues when performing table movement operations:

ADMIN_MOVE_TABLE(<SchemaName>,<TableName>,'','FORCE_ALL','SWAP‘)

Helps avoid deadlocks and timeouts due to heavy use of the source table during the SWAP phase

Behaves like the FORCE APPLICATION command

Requires SYSADM, SYSCTRL, or SYSMAINT authority

Care should be exercised when using the FORCE_ALL option!

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WLM Dispatcher: CPU Control at the Database Level

• New database-level share values control the division of CPU

resources between databases

⎼

Enables prioritized allocation of CPU in multi-database environments

⎼

Configured via the

WLM_CPU_SHARES

and

WLM_CPU_SHARE_MODE

database configuration parameters

• New database-level limit value controls the total CPU consumption of

all service classes within a database

⎼

Configured via the

WLM_CPU_LIMIT

database configuration parameter

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Federation Integration and Enhancements

Federation capabilities extended to more data sources

–

More drivers directly integrated into the DB2 installer

–

Expansion to both SQL- and NoSQL-based data stores

–

Expansion to both on-premises and cloud data sources

Set-up simplified

–

CREATE WRAPPER statement and WRAPPER clause of CREATE SERVER now optional (a default wrapper will be created if clause is omitted)

–

Can create server with host, port, and service name without first cataloging the remote node and database

This image shows only a subset of all supported data sources

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Core Functionality and SQL Compatibility Improvements

(1)

DECIMAL/DECFLOAT data type improvements

–

Arithmetic on AIX, Intel, Linux on Power (LE), and zLinux accelerated

–

AIX and Intel Conversion between row- and column-organized formats optimized

–

SUM() operations on DB2 for zLinux optimized

Table column and expression support for BOOLEAN data type added

–

Valid values include TRUE , ‘ true ’, ‘ t ’, ‘ yes ’, ‘ y ’, ‘ on ’, ‘ 1 ’, FALSE , ‘ false ’, ‘ f ’, ‘ no ’,

‘ n ’, and ‘ 0 ’

–

Some initial restrictions:

• Replication (SQL / Q Replication, CDC) not allowed

• IMPORT operations not allowed

• ALTER NICKNAME – column data type change to/from BOOLEAN not allowed

(column name changes supported)

• Cannot be used with ANALYZE_TABLE expressions

• External functions and procedures written in C, COBOL, CLR, and OLE cannot use

BOOLEAN input or return values

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Core Functionality and SQL Compatibility Improvements

(2)

Common Table Expression support extended to increase compatibility with DB2 on z

–

The

WITH

clause can now be used with

SELECT INTO

statements for

Static SQL, SQL User-Defined functions, and SQL Stored Procedures:

WITH cte_1(c1, c2) AS (SELECT c1, c2 FROM t1)

SELECT SUM(c2) INTO :outvar FROM cte_1

WHERE c1 BETWEEN :lowval AND :highval

The db2_install command now requires the user to accept the license agreement before the installation can proceed

–

Acceptance can be made by specifying the new

-y

parameter

–

If the -y parameter is not specified, the user is prompted to either accept or decline the license agreement

–

The -y parameter must be specified if the -n parameter is specified

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(1)

Log file size limit increased to 64 GB (from 4 GB)

–

Larger log files allow for larger log space

–

Actual size used is controlled by the LOGFILSIZ database configuration parameter

Client information is now written to db2diag.log for lock and lock error events

–

Additional CLIENT diagnostic information (i.e., CLIENT USERID, CLIENT

ACCTNG, CLIENT APPLNAME, and CLIENT WRKSTNNAME) is recorded in the log when:

• A transaction exceeds the number of log files it can span ( NUM_LOG_SPAN database configuration parameter value)

• A transaction exceeds the amount of primary log space it can consume ( MAX_LOG database configuration parameter value)

• A transaction triggers a lock escalation event

–

In MPP (DPF) environments, this information is written only if the events occur on the coordinator node

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(2)

Backup image sizes can now be obtained using an event monitor

–

New BYTES_TOTAL monitor element added to the UTILSTOP logical data group

–

Used by BACKUP change history event monitors only

Example:

–

Connect to a database named TEST (that has been configured for online backups), create a BACKUP change history event monitor, and then start an online backup:

$ db2 “CONNECT TO test”

$ db2 “CREATE EVENT MONITOR em1 FOR CHANGE HISTORY WHERE EVENT IN

(BACKUP) WRITE TO TABLE AUTOSTART”

$ db2 “BACKUP DATABASE test ONLINE”

–

Obtain the size of the backup image created using SQL:

$ db2 “SELECT UTILITY_TYPE, START_EVENT_TIMESTAMP, BYTES_TOTAL

FROM utilstop_em1”

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UTILITY_TYPE START_EVENT_TIMESTAMP BYTES_TOTAL

---------------- ------------------------- ---------------------

BACKUP 2017-01-10.8.43.48.663294 184627200


Synopsis Updates with Block Inserts (Good)

First Last Address

First

John

Last

Smith

Address

1 Cork St Carson

City

CA

State

Katrina Jones

Bob Taylor

132 Front Ave Buffalo

23 Bee St Akron OH

Enzo Brown 9 Elbow Pl

Denver

Rick Hewitt 31 King St Astoria

CO

OR

NY

5

First

Bob

City

State

Rick

Last

Brown

Address City

State

Taylor 1 Cork St 9 Elbow Pl Akron Denver CA OR

1) Records are inserted into the various columns

2) The synopsis table is updated with MIN/MAX values for each column

3) Only one synopsis update for the block insert

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Synopsis Updates with Individual Inserts (Not so good)

First Last Address City

First

John

Last

Smith

Address

1 Cork St Carson

City

CA

State

State

Katrina Jones

Bob Taylor

132 Front Ave Buffalo

23 Bee St Akron OH

Enzo Brown 9 Elbow Pl

Denver

Rick Hewitt 31 King St Astoria

CO

OR

NY

5

First

John

John

Bob

Bob

Bob

John

Katrina

Katrina

Katrina

Rick

Last

Smith

Jones

Jones

Brown

Brown

Address City

State

Smith 1 Cork St 1 Cork St Carson Carson CA CA

Smith 1 Cork St 132 Front Av Carson CA NY

Taylor 1 Cork St 23 Bee St Akron Carson CA OH

Taylor 1 Cork St 9 Elbow Pl Akron Denver CA OH

Taylor 1 Cork St 9 Elbow Pl Akron Denver CA OR

1) Records are inserted into the various columns

2) The synopsis table is updated with MIN/MAX values for each column

3) One synopsis update for the each insert

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New In-Memory Synopsis

Synopsis updates collected in memory until 1024 rows/TSNs have accumulated

The transaction that inserted 1024th value will update the persisted synopsis table with a single entry

–

After recovery from crash, ‘lost’ synopsis values rebuilt via limited scan of

‘tail’ of table

New in-memory algorithm used for all synopsis tables in DB2 v11.1.1.1 and beyond

Benefits:

–

Significant reduction in pages updated in small transactions and corresponding significant performance improvements

–

Significant storage savings in synopsis tables for small transactions

–

Significant performance improvements for queries that exploit synopsis tables

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In-Memory Synopsis : Example Benefits

Previous synopsis maintenance was designed for batch inserts

(1000s of rows)

In-memory synopsis is aimed at both batch inserts and small OLTP transactions

–

Updates values in memory and writes them to synopsis table after 1024 rows are covered

In this lab test we observed …

–

Elapsed Time of INSERT Size of Synopsis Table

–

With and Without InWith and Without In-

–

Memory Synopsis Memory Synopsis

600,00 900

500,00

800

700

39%

400,00

300,00

200,00

46%

600

500

400

300

87%

100,00

0,00

EE MPP

200

100

0

No Optimization With Optimization

No Optimization With

Optimization

Query Elapsed Time

With and Without In-Memory

Synopsis

0,07000

0,06000

0,05000

0,04000

0,03000

0,02000

0,01000

0,00000

60%

46%

EE MPP

No Optimization With Optimization

•

•

IBM p760 / POWER7+ 32 cores / 1TB RAM

Table with 50 columns.

•

•

•

Single user

Insert test 100K rows with commit count = 1

Select query with 10 pairs of range predicates

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Performance is based on measurements and projections using standard IBM benchmarks in a controlled environment. The actual throughput or performance that any user will configuration, and the workload processed. Therefore, no assurance can be given that an individual user will achieve results similar to those stated here.

Multi-Core Parallelism Directions

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DB2 has exceptional multi-core scalability for queries:

–

Very strong scalability on the largest SMPs

–

Combined MPP and SMP parallelism

–

Includes the SELECT component of an INSERT from sub-select

–

Includes columnar and row-based tables

Future Deep Multi-Core Parallelism for Writes

–

Includes a variety of data population methods

(i.e., INSERT, INGEST, etc.)

–

Includes index update parallelism

–

Includes MPP support

DB2 v11.1.1.1 adds INSERT parallelism

–

Very significant reduction in data population/ingest job duration

–

Very significant reduction in ETL/ELT batch jobs

–

UPDATE/DELETE expected in the future


Multi-Core INSERT Parallelism – Example Benefits

Elapsed time (seconds) for:

INSERT INTO table2 (SELECT * FROM table1)

Single Node (48 cores)

12 DPF DB Partitions

(48 cores total)

6000

5000

4000

700

600

500

400

3000

2000

1000

34.5x

27.5x

300

200

100

3.9x

3.4x

0

Columnar Source

Current

Row Source

with Write Multi-Core Parallelism

100 Million Rows

47GB

0

Columnar Source

Current

Row Source

with Write Multi-Core Parallelism

DPF tests used 12 logical DB partitions, & co-located tables

Same 48 core server used for single-node and DPF tests

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Performance is based on measurements and projections using standard IBM benchmarks in a controlled environment. The actual throughput or performance that any user will configuration, and the workload processed. Therefore, no assurance can be given that an individual user will achieve results similar to those stated here.

Multi-Core INSERT Parallelism – Details

Enabled with two registry variables –

DB2_REDUCED_OPTIMIZATION and

DB2_EXTENDED_OPTIMIZATION

:

$ db2set DB2_REDUCED_OPTIMIZATION=ENABLE_RTABLE_INS –immediate

$ db2set DB2_EXTENDED_OPTIMIZATION=CDE_PAR_IUD –immediate

Remember to keep previous settings, if needed; for example:

$ db2set DB2_REDUCED_OPTIMIZATION=STARJN_CARD,ENABLE_RTABLE_INS –immediate

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In the future, we expect this behavior to be enabled by default

–

Once enabled, the degree of parallelism is automatically determined based on data volume (i.e., number of rows)

• INSERT with values that touch just a few rows

is not likely

to be parallelized

• INSERT with sub-select from a large source table

is likely

to be parallelized

• The actual DEGREE of parallelism chosen by the optimizer is shown in the

RETURN

operator of the

EXPLAIN_ARGUMENT

table

For more information, refer to the Technote titled Parallel INSERT at http://www-01.ibm.com/support/docview.wss?uid=swg27049357 .


Other BLU Enhancements

(1)

Additional SIMD enhancements

–

Exploitation of the latest SIMD technology:

• Intel® Advanced Vector Extensions 2 (Intel® AVX2)

• Streaming SIMD Extensions 2 (SSE2)

• Supplemental Streaming SIMD Extensions 3

(SSSE3 or SSE3S)

• Streaming SIMD Extensions 4 (SSE4)

–

Support extended to Power8, z13™ and Intel CPUs supporting AVX2

–

More functions and bit operations

–

Utilization of the Fletcher-64 checksum algorithm

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(2)

Performance improvements for INSERT from sub-select operations against BLU tables

–

With IDENTITY columns -

up to 140x faster

–

In MPP environments where RANDOM data distribution is used -

up to

3.5x faster

Reduction (or elimination) of sort operations in some access plans

(e.g., queries against BLU tables with OLAP specifications and/or

ORDER BY clauses)

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Use of uncommitted data for Automatic Dictionary Creation for

BLU tables

–

Compression dictionaries are made available earlier for:

• INSERT, IMPORT, and INGEST operations

• Large INSERT operations such as INSERT with sub-selects

–

Higher

PCTENCODED

(percent encoded) values in SYSCAT.COLUMNS results in:

• Better query performance

• Increased throughput for high concurrency workloads



(3)

• Aggregation

* enhancements for improved memory usage and performance:

⎼

Improved decisions to pre-partition using the GROUP BY columns of the aggregation input stream

⎼

Better memory and performance for single/unique group results

▸

If a group contains a single row, then the column value itself is returned as the aggregation result

⎼

Better decisions to avoid a "Partial-Final" MPP GROUP BY when the partial

GROUP BY does not significantly reduce the aggregation stream

⎼

New and improved 64-bit hashing algorithm reduces the number of collisions in the hash table and better utilizes memory needed for aggregation

✶

Data aggregation is any process in which information is gathered and expressed in a summary form.

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DB2 11.1.1.1 Workload Comparisons Against DB2 11.1

Examples of DB2 11.1.1.1 benchmarking (unofficial) versus

DB2 11.1 GA

–

TPC-DS shows a 24% improvement

–

TPC-H shows a 14% improvement

–

SAP-BW shows a 22% improvement

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Removal of Restrictions and Limitations

A system temporary table space having a page size of 32 K is no longer required for extended row sizes

The ability to alter the length of VARCHAR/VARGRAPH columns in column-organized tables is now supported

–

String units (e.g. CODEUNIT32) cannot be altered

The db2convert command can now be used to convert roworganized tables in MPP and with generated identity columns to column-organized tables

System maintained materialized query tables (MQTs) in MPP can now reference a nickname

32


Additional Operating System Support and Compatibility

DB2 pureScale support for:

–

SLES 12, SP1 on x86

–

RHEL 6.8 on x86

Non-pureScale support for Windows

Server 2016

–

No warehouse components or Tivoli

System Automation

Non-pureScale support for Ubuntu 16.04 on z Systems

–

11.1 GA had prerequisites on 3 libraries which had to be installed manually; this was resolved in 11.1.1.1

Text Search support added for all Linux on z Systems

33


New DB2 JSON Functions

Several JSON functions now available on DB2 10.5 and DB2 11.1

–

Insert, Retrieve, and Document Validation

• BSON2JSON – Convert BSON formatted document into JSON strings

• JSON2BSON – Convert JSON strings into a BSON document format

• BSON_VALIDATE – Checks to make sure that a BSON field in a BLOB object is in a correct format

–

Field Retrieval

• JSON_VAL – Extracts data from a JSON document into SQL data types

• JSON_TYPE – Returns the data type of a specific field within a JSON document

–

Array Retrieval

• JSON_TABLE – Returns a table of values for a document that has array types in it

• JSON_LEN – Returns the count of elements in an array type inside a document

• JSON_GET_POS_ARR_INDEX – Find a value within an array

–

Document Update

• JSON_UPDATE – Update a field or document using set syntax

34


IBM Data Server Gateway for OData Version 1.0.0

What is the problem?

–

Customers want to access Data from non traditional platforms like Mobile platforms, from mobile apps (Android, Windows, iOS, etc.)

• And in some cases want to publish access to data as well to 3rd parties

–

Mobile and Cloud developers expect direct HTTP and JSON (API based) access to data (internal like DB2, 3rd party like Salesforce, SAP) – without requiring Database Drivers

What is being delivered:

–

ODATA is standards based way for our customers to leverage DB2, and dashDB in modern Cloud and Mobile Application Models

–

Delivery mechanism to be synergistic with DS Driver packages with

DB2 V11 Mod 1

https://www.youtube.com/watch?v=z06bl_K6Ckc https://www.youtube.com/watch?v=dHVBiTphoCM

35


Preview: Online Crash Recovery (aka Async UNDO)

Significantly increase database availability during crash recovery

–

Focus on scenarios where large batch operations are updating the database

Allow database connections during the UNDO phase of crash recovery (Also HADR TAKEOVER BY FORCE)

–

The UNDO phase is significantly longer if a crash occurred when batch operations or other long-running (e.g. errant) transactions were executing

Alter crash recovery to:

–

Acquire exclusive locks on all tables or table partitions with in-flight operations immediately after the REDO phase

–

Allow new connections to the database as early as possible in the UNDO phase so:

• Access to unlocked tables/partitions can proceed normally

• UR access to locked tables/partitions is allowed

–

Process the UNDO phase asynchronously, releasing table locks as

UNDO progresses

36


35000

30000

25000

20000

15000

10000

5000

Technical Preview: Online Crash Recovery (Async UNDO)

pS

DB up

No Change

prior to

DB down

DB up

11.1

DB up (*)

DB up

11.1.1.1

Preview

DB down

REDO

45000

40000

UNDO pureScale

Preview

Connections allowed after synchronous portion of UNDO completes. Length of synchronous portion is dependent on actual data operations. More detail

In tech note referred to on next page.

Current

37

(*) Some data may be locked while UNDO proceeds concurrently

Time


Preview: Online Crash Recovery – Details

To enable the Online Crash Recovery Technical Preview:

1. Assign the value ‘

YES

’ to the undocumented registry variable

DB2_ASYNC_UNDO

:

db2set DB2_ASYNC_UNDO=YES

2. Reactivate the database

IMPORTANT: Use in DB2 11.1.1.1 non-production environments only; lab validation is not complete!

3. Once enabled, the following administrative notification message is written during crash recovery when the aysnchronous portion of the UNDO phase begins and database connections are allowed:

ADM1505I Crash recovery has completed synchronous processing

For more information, refer to the Technote titled Database accessibility during Backward

phase of crash-recovery or 'HADR Takeover by Force’ at: http://www-01.ibm.com/support/docview.wss?uid=swg21994342

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Data Server Manager 2.1.2 – What’s New for DB2 11.1.1.1

Manage your IBM data Enterprise

• Enterprise view of

DB2 and dashDB

KPIs and alerts from one dashboard

• Data Server Manager Login authentication through

LDAP

• New enterprise grid view shows hundreds of

DB2 and dashDB

servers at a glance

Monitor In Depth

• New powerful database performance overview page for

rapid problem determination

• Database time breakdown

• 18 KPIs in one screen for real-time or historical analysis

• Breakdown by

workload

• For

DB2 and dashDB

Ensure DB2 High Availability

• See the availability of all of your

HADR and DB2 pureScale

clusters at a glance

• Dashboard, SNMP and Email alerts that

highlight

potential availability

problems before they happen

Making remote data act like local data

• Make data in remote DB2, BigSQL or dashDB databases

look and act like local tables

with 11.1.1.1 and Fluid Query

•

Explain and monitor

queries with calls to remote data sources with 11.1.1.1

39


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International DB2 Users Group

IDUG DB2 Tech Conference

Lisbon, Portugal

October 1-5, 2017

• The premier European DB2 Conference will take place

on October 1-5, 2017 at Lisbon, Portugal. Make your plans to attend and experience the latest in DB2 technologies, networking opportunities and the technical content you need to be successful.

• The 2017 event offers new educational opportunities and

more training than ever before! Attendees will experience: 5 days of education sessions

• Half and full-day workshops

• More than 100 one-hour technical sessions

• Three expert panels on z/OS, LUW & Application

Development

• And much more!

• Register at

www.idug.org

before 7 August 2017 to receive

Early Bird Discount!

• Conference hotel:

EPIC SANA Lisboa Hotel, Lisbon


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