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Best Practices for Optimizing
DB2 Performance
Author
This presentation was prepared by:

Craig S. Mullins
President & Principal Consultant
Mullins Consulting, Inc.
and
DB2 Practice Consultant
Datavail Corporation
E‐mail: 
craig@craigsmullins.com
craig.mullins@datavail.com

This document is protected under the copyright laws of the United States and other countries as an unpublished work. This document
contains information that is proprietary and confidential to Mullins Consulting, Inc., which shall not be disclosed outside or
duplicated, used, or disclosed in whole or in part for any purpose other than as approved by Mullins Consulting, Inc. Any use or
disclosure in whole or in part of this information without the express written permission of Mullins Consulting, Inc. is prohibited.
© 2013 Craig S. Mullins and Mullins Consulting, Inc. (Unpublished). All rights reserved.

11/8/2013

www.datavail.com

2
The Tuning Progression
Problem Resolution
•

Application
•
•

•

Database
•
•
•

•

Indexing
Database and Index Organization
Database Design (normalization / denormalization)

DB2 Subsystem
•

•

SQL
Host Language Code

ZPARMs, Pools, Locking, IRLM, DDF, etc.

Environment
•
•
•

Network
TP Monitor (CICS, IMS/TM)
Operating System

© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

3
Basic Tuning Rules
•

80% of the results of tuning come 
from 20% of the tuning effort 
• 20% of your DB2 applications cause 
80% of your problems

•

20%

Tune one thing at a time
• How else do you know whether the 
action helped or not?

•

All tuning optimizes:
• CPU,  I/O or concurrency

80%

© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

4
A Few General Performance Themes 
to Remember 
• Almost never say always or never.
•

There are rarely any “rules” 
that always apply.

• Don’t panic and remain humble.
•

Remaining calm and open to all solutions, even ones that recognize “you” as being 
the culprit, is important for building efficient DB2 databases and applications.

• It is better to design for performance from the start.
•

The further into the development process you are, the more painful it becomes to 
makes changes.

• And always remember the Cardinal Rule  “It Depends!”
•
•

It depends because relational database performance is a complex thing that is not 
simply explained: situations, implementations & requirements vary.
But the secret to optimizing DB2 performance is being able to answer the follow‐up 
question to “It Depends,” which is “What does it depend upon?”

© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

5
Application Code and SQL
Most relational tuning
experts agree that the
majority of performance
problems with
applications that access
a relational database are
caused by poorly coded
programs or improperly
coded SQL…


as high as 70% to 80%

Everything
Else

Application
Code & SQL

© 2013 Mullins Consulting, Inc.
Application Tuning: SQL 
•

Simpler is better, but complex SQL can be efficient

•

In general, let SQL do the work, not the program

•

Always provide join predicates
•

•

Avoid Cartesian products

Favor Stage 1 and Indexable predicates
•

Host variable data type/length should match column

•

Avoid table space scans for large tables (usually)

•

Avoid sorting when possible:
•
•
•

Indexes for ORDER BY and GROUP BY
Judicious use of DISTINCT
UNION ALL versus UNION (if possible)

© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

7
Application Tuning: Stage 1 and 2
Result

SQL Request

STAGE 2 - Evaluated after
data retrieval via the RDS
(Relational Data Services)
which is more expensive
than the Data Manager.

RELATIONAL DATA SERVICES

STAGE 1 - Evaluated at the
time the data rows are
retrieved. There is a
performance advantage to
using Stage 1 predicates
because fewer rows are
passed to Stage 2 via the
Data Manager

DATA MANAGER

BUFFER MANAGER
Data
© 2013 Mullins Consulting, Inc.

I/O

Managing Performance (SC19-2978)
•

Table 66 starting on page 269
Stage 3?
•

Not an actual Stage but…
•

•

It can be helpful to think of moving 
predicates from SQL into your programs 
as Stage 3

Easy to remember:
•
•

Stage 1 better than Stage 2 and…
Stage 2 better than Stage 3

© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

9
Ask Only for What You Absolutely Need
Retrieve the absolute minimum # of rows required

•
•
•

Code appropriate WHERE clauses
The only rows that should be returned to your program should be those that you 
need to process

Retrieve only those columns required:  never more

•
•
•

Don’t ask for what you don’t need
Sometimes shortened to  Avoid SELECT *
–

This is a good idea for several reasons:
1.
2.

–

Insulation of programs from change
Performance

But it is not enough…

© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

10
What is Wrong with this SQL?

Why are we asking
for things we
already know?

© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

11
http://www.craigsmullins.com/dbu_0703.htm
© 2013 Mullins Consulting, Inc.
Application Tuning: Optimization
SQL
Statement(s)

DB2 Subsystem

Plan
Tables

DB2
Optimizer

Other System
Information

Query Cost
Formulas

• PLAN_TABLE
• DSN_STATEMNT_TABLE
• DSN_FUNCTION_TABLE
• Plus many others

DB2
Catalog
Optimization
Hint

OPTHINT in PLAN_TABLE

Optimized
Access
Path(s)

DBAS
(DSNDBM1)

© 2013 Mullins Consulting, Inc.
Application Tuning: EXPLAIN Analysis

Hint used?

SQL Text

Index used?

Table & Index Information



Single, Multiple

Matching column(s)?
Index only?



DDL



Stats

Cardinality



Sequential



List

Parallelism used?

Other Stuff



Nested Loop



Triggers



Merge Scan



Hybrid



Constraints

I/O, CPU, Sysplex
Degree

Sort required?

RI






TS scan (page range)
Type of Join?

Prefetch?



Join, Unique,
Group By, Order By

Locking

© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

14
Application Tuning: Locking
• Minimize deadlocks by coding updates in the same 
sequence regardless of program
• Issue data modification SQL statements as close 
to the end of the UOW as possible
• the later in the UOW the update occurs, the 
shorter the duration of the lock

• Plan and implement a COMMIT strategy
• or experience TIMEOUTs and DEADLOCKs

• Encourage Lock Avoidance
• ISOLATION(CS) / CURRENTDATA(NO)
• Can be used only by read only cursors

• Consider ISOLATION(UR) to avoid locking
© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

15
Application Tuning: Program
•

Do not embed efficient SQL in inefficient program logic
• Classic example: finely tuned, efficient 
SQL inside of a program loop that 
executes 3,510,627 times!

•

Let SQL do the work when possible
• e.g.) do not code “program” joins

•

Sign of trouble: SQL followed by lots of 
IF...ELSE or CASE statements

•

If you are only going to retrieve one row, consider
coding a singleton SELECT (usually)

•

Consider adopting multi‐row FETCH
• Multiple tests have shown that moving to multi‐row FETCH can yield between a 
50% to 60% improvement for 100 and 1000 FETCHes

•

Online versus Batch
•
•

Limit the amount of data to be retrieved to a reasonable amount
Consider OPTIMIZE FOR 1 ROW to disable list prefetch

© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

16
Database Object Tuning
DATABASE
Segmented
Table Space

STOGROUP

Index

Index
Table
Index

Table

LOB
Tablespace

Table

w/LOB

Auxiliary
(LOB)
Table

Index
Universal
Table Space

Index

Table
Non-Partitioned
Segmented + Partitioned

Index
Partitioned
Table Space

Partitioned
Index

Separate LOB
Tablespace
per Partition
(for each
LOB column)

w/LOB
Auxiliary
(LOB)
Table
© 2013 Mullins Consulting, Inc.
General Table Space Recommendations
• Universal table spaces are the future (and present) of DB2 
table spaces
• Favor using universal table spaces over segmented or traditional 
partitioned table spaces
– Partition by growth (PBG) is ideal when a table is expected to exceed 64 
GB but there is no suitable partitioning key
– PBR, or range‐partitioned, universal table spaces are ideal for partitioning 
data and should be considered the standard instead of classic partitioning

• At some point, other table space types are likely to be deprecated 
(like simple table spaces, which already have been)

• In most cases limit yourself to one table per table space
• You can still use a segmented table space when you must have multi‐
table TS
© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

18
Database Organization
• Be sure to run RUNSTATS
• as data volume changes, new data structures added
• followed by (RE)BIND with /EXPLAIN(YES)

• Review statistics (or better yet RTS) to determine 
when to REORG
• NEARINDREF and FARINDREF
• LEAFDIST, PERCDROP
• For clustering indexes

 NEAROFFPOSF and FAROFFPOSF
 CLUSTERRATIOF

• Migrate to Real Time Statistics!
• Analyze access patterns before reorganizing
 Random vs. sequential
 Consider automation

© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

19
Scheduling Regular Rebinds: The Five R’s
• RTS  (or RUNSTATS)

RR

• REORG
• RUNSTATS

RR

• REBIND

R

• Recheck
• In other words, what did the REBIND do?
– Did any access paths change?
– Are they better or worse?
– Does anything need attention?

© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

20
Access Path Degradation Correction
• Problem access paths can still occur. If so:
• Absolutely determine you are not at fault by re‐re‐checking
– Statistics up‐to‐date?
– Correct statistics run?
– Package rebound with latest statistics?

• If problems persist, one of the following 
approaches could work for you:
– Plan Stability 
– Tweak SQL (ways to “coerce” the optimizer)
– Code and Use an Access Path Hint
– Manipulate statistics (caution)

© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

21
Table Design Guidelines
• As normalized as possible, but performance before aesthetics; 
normalization optimizes “update” at the expense of “retrieval”
• Don’t let data modelers dictate “physical” design

• Avoid the defaults ‐ they are usually wrong
• Determine amount of free space
• PCTFREE – amount of each page to remain free during REORG
• FREEPAGE – after this many pages of data, keep an empty page 
• Don’t just let everything default (for example, to 10).
– Should be based on the volatility of the data

• Use appropriate data types
• Character, numeric, date‐time, binary, XML, BLOBs…

• Compression versus VARCHAR
• Compression = less overhead (no 2 byte prefix)
• Compression requires no programmatic handling
© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

22
Database Design: Columns and RI
• Sequence columns based on logging

New DB2 9
Format

• Infrequently updated non‐variable columns first
• Static (infrequently updated) variable columns

Reordered
Row Format

• Frequently updated columns last
• Frequently modified together, place next to each other

• Use DB2 declarative RI instead of program RI (usually)
• Declarative usually outperforms program RI
• Ensures integrity for both planned and ad hoc database modification
• Do not use RI for lookup tables (overkill)
– consider CHECK constraints vs. lookup tables

• Specify indexes on foreign keys

© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

23
Database Design: Indexes
• A proper indexing strategy can be the #1 
factor to ensure optimal performance
• First take care of unique & PK constraints
• Then for foreign keys (usually)
• Heavily used queries ‐ predicates
• Overloading of columns for IXO
• Index to avoid sorting
• ORDER BY, GROUP BY

• Consider INS / UPD / DEL implications
• Consider how to index variable cols ‐ [PADDED | NOT PADDED]
• Index not used? SYSIBM.SYSINDEXSPACESTATS.LASTUSED
© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

24
System & DB2 Subsystem Tuning

Allied
Agent
Address
Spaces
• CICS
• IMS
• TSO

SSAS
System Services
Address Space
Logging
Recovery
Access to TP

DBAS
Database Services
Address Space

IRLM
Internal Resource
Lock Manager

RDS - Optimizer
Data Manager
Buffer Manager

Locking

DDF
Distributed
Data
Facility

SPAS/WLM
Stored
Procedures
VSAM
Media
Manager
Data

11/8/2013

© 2013 Mullins Consulting, Inc.

www.datavail.com

25
Swimming in DB2’s “ Pools”
• Relational database systems “love” memory
• Performance improves if important information and run‐time details 
are cached in memory instead of being read from disk every time they 
are needed.

• DB2 uses four types of “pools” – or memory structures to 
cache data and information to avoid costly disk I/O
•

Buffer Pools ‐ used to cache data in memory when it is read from disk.

•

RID Pool ‐ used to sort RIDs (record identifiers) for List Prefetch, 
Multiple Index Access, and Hybrid Joins. 

•

EDM Pool ‐ used to cache program details 
(access paths, dynamic PREPARE, authorization) 
and database structural information (DBD).

•

Sort Pool ‐ used when DB2 must sort data.

© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

26
Subsystem Tuning: Buffer Pools
• DB2 provides up to 80 buffer pools ‐ USE THEM!
• ‐ 4K: BP0 thru BP49

‐ 8K: BP8K0 thru BP8K9

• ‐ 16K: BP16K0 thru BP16K9

‐ 32K: BP32K, and BP32K1 thru BP32K9

• Consider reserving a buffer pool for tuning
• Move problem objects there to isolate for tuning

• Monitor hit ratio: % times a page is found in the buffer pool
• The higher the ratio the better
(GETPAGES – PAGES READ) / GETPAGES
SYNC I/O + ASYNC I/O

• Monitor and tune buffer pools thresholds 
• Variable and Fixed
© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

27
Buffer Pools: Tune Thresholds
•

Variable Thresholds

VPXPSEQT: Assisting
Parallel Sequential
(0% of VPPSEQT)

VDWQT: Vertical
Deferred Write (5%)

VPPSEQT: Parallel
Sequential
(50% of VPSEQT)

DWQT: Deferred
Write ( 30%)
(default was 50% pre-V9)

•

Prefetch Disabled
(90%)

VPSEQT:
Sequential
Steal (80%)

Fixed Thresholds
Data Manager Critical
(95%)

Immediate Write
(97.5%)

(default was 10% pre-V9)

© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

28
RID Pool Overview
• One RID pool for all processing.
• The default RID pool size is 4 MB. Can 
be changed. 
• RID Pool is used for:
•
•

enforcing unique keys while updating 
multiple rows
sorting RIDs during the following 
operations:
–

List prefetch, including single index list 
prefetch

–

Access via multiple indexes

–

Hybrid Joins

© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

29
The EDM Pool: Contents & Changes
• What’s in the EDM Pool

General ROT: shoot for
80% EDM efficiency
(1 in 5 DBD/SKPT/SKCT
needs to be loaded)

• V8: EDM Pool split into three specific pools:
• Below the 2GB Bar
– EDMPOOL: EDM Pool stores only CTs, PTs, SKCTs, SKPTs
– Provides VSCR below the 2GB Bar storage

• Above the 2GB Bar
– EDMDBDC: DBDs
– EDMSTMTC: Cached Dynamic Statements

• V9: Introduces additional changes
• Above the 2GB Bar: EDM_SKELETON_POOL
– All SKCTs and SKPTs 

• A portion of the CT and PT is moved above the bar, too
© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

30
Sort Pool and Sorting Guidelines
• Sort Pool value is the maximum size of the sort work area 
allocated for each concurrent sort user.
• Minimize the amount of data that needs to be sorted!
•
•

DB2 uses a tournament sort unless the Sorted Record > 4075, in which case it uses a tag 
sort (which is less efficient)
Keys + RID are sorted… the data is retrieved from the sort using the RID

• Sorts that don’t fit in the Sort Pool overflow to workfile
•

In general, the larger the sort pool, the more efficient the sort. 

• Allocate additional physical work files in excess of the defaults, 
and put those work files in their own buffer pool (e.g. BP7). 
•

At least 5, sized the same, with no secondary  

• The better sorted the data is originally, the more efficient the 
sort will be. 
© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

31
Subsystem: Logging
• DB2 will only run as fast as the log
• Log Configuration
• Dual Active Logging is the preferred configuration
• Each log defined to separate devices and on separate channels

• DB2 rollbacks from log data on disk
• Consider keeping archive logs on disk*

*

and then migrate archive logs to tape after a specified period of time (HSM)

© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

32
Subsystem: System Checkpoint
• Periodically DB2 takes a checkpoint, containing:
• currently open unit of recoveries (UR) within DB2, all open page sets, a list 
of page sets with exception states, and a list of page sets updated by any 
currently open UR
• Dirty pages are written out at checkpoint and processing stops until they 
are written – so make sure DWQT is sized correctly!

• Specified in the CHKFREQ* parameter in DSNZPARM
• Number of log records written (CHKLOGR)
• Or, as of V7, number of minutes (CHKMINS)

• Can be changed dynamically using:
5 minute intervals for
checkpoints during
peak processing times.

• SET LOG or (temporary)
• SET SYSPARM (permanent)

*CHKFREQ

replaced LOGLOAD in DB2 V7

© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

33
Subsystem Tuning: IRLM
•

MAXCSA 
• 250×(LOCKS PER USER)×(MAX USERS)

•

250 bytes of storage
for each lock.

ITRACE=NO 
• Do not use ITRACE; 
• Instead, if needed, use DB2 lock traces.

•

DEADLOK
1. The number of seconds between two successive 
scans for a local deadlock
2. The number of local scans that occur before a 
scan for global deadlock starts

© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

34
Environment
• Operating System
• version, memory, JCL, RACF, etc.

• TP Monitors
• CICS, IMS/TM, C/S GUI, web, etc.

• Networking
• TCP/IP, SNA, DRDA, stored procedures, etc.

• Hardware
• storage, RAID, zIIP/zAAP, etc.

© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

35
Summary
Application
Database
DB2 Subsystem
Environment
Do one thing at a time and;
You can tune DB2!

© 2013 Mullins Consulting, Inc.

11/8/2013

www.datavail.com

36
Have You Considered Remote DBA Services?
Datavail offers remote DBA services and operates 24 x 7 x 365
With delivery centers in the U.S. and India, Datavail can cover the time 
zones in which our clients operate
Support DBAs are working in live shifts round‐the‐clock
•
•
•

DBAs ready to support your business all the time, as needed, already up & working
No need to wake up local DBA for support
DBAs working with other DBAs – over 350 DBAs

Datavail’s remote services automatically deliver 24x7 coverage
By combining the 24x7 remote coverage 
with a US‐based primary DBA a client 
obtains the benefits of an on‐staff DBA
plus those of Datavail’s remote DBA service

11/8/2013

www.datavail.com

37
Datavail Performance Management
Monitoring Tools
• For customers who have their own preferred monitoring tools and/or 
scripts, if desired, Datavail leverages those tools– Datavail will configure it, 
manage it, and seamlessly integrate into our ticketing system
• For customers who do not have a preferred monitoring solution, Datavail
leverages our proprietary monitoring tool called Datavail Delta
• We also leverage our collection of custom scripts to perform initial and 
periodic environmental health checks

Ticketing System
• Our ticketing system is available to any client using our managed services
• For customers who have their own ticketing system we can leverage your 
toolset and/or create an API integration into Datavail’s ticketing system
All cost related to use of the tools and ITSM platform is included with the service

11/8/2013

www.datavail.com

38
The Value of Datavail Remote DBA Services

The world’s largest pure‐play database support company

“Datavail delivers a managed services solution ‐‐ what 
you are getting is a small slice of a very sophisticated 
operation, built over 10 years by people with literally 
100’s of years of experience in IT operations…” 

11/8/2013

www.datavail.com

39
Datavail Company Profile
Datavail helps you manage your databases, reduce your risk, and lower your cost

250+ Customers
•

Average customer retention of 7 years

350+ DBAs
•

24x7 Live & Available Tier 1, 2, and 3 DBAs 

10+ Years Delivering Database Services
•

Our differentiation is centered in our focus with scale

Headquartered in Broomfield, CO
•
•
•

Regional offices Seattle & New York 
Offshore delivery centers in Mumbai & Bangalore
Acquired Blue Gecko & Bluewolf Database Services

Strong Year‐over‐Year growth
•

Datavail has been growing at a CAGR of 60% over the last 3 years

Mature, Proven Delivery Model
•
•
11/8/2013

Tools, Best Practices and ITIL Processes
Shared Services in an on‐Shore/Off‐Shore Model 
www.datavail.com

40
Questions

Craig S. Mullins
Mullins Consulting, Inc.
Craig.Mullins@datavail.com
craig@mullinsconsultinginc.com
http://www.mullinsconsultinginc.com
Datavail Corporation
11800 Ridge Parkway – Suite 125
Broomfield, CO 80021
info@datavail.com
http://www.datavail.com
(877) 722-8247

11/8/2013

www.datavail.com

41

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