IBM Optim Query Tuning Offerings Optimize Performance and Cut Costs

Transcription

1 IBM Optim Quey Tuning Offeings Optimize Pefomance and Cut Costs Saghi Amisoleymani Solution Achitect Integated Data Management June 9, 2010

2 Disclaime Copyight IBM Copoation [cuent yea]. All ights eseved. U.S. Govenment Uses Resticted Rights - Use, duplication o disclosue esticted by GSA ADP Schedule Contact with IBM Cop. THE INFORMATION CONTAINED IN THIS PRESENTATION IS PROVIDED FOR INFORMATIONAL PURPOSES ONLY. WHILE EFFORTS WERE MADE TO VERIFY THE COMPLETENESS AND ACCURACY OF THE INFORMATION CONTAINED IN THIS PRESENTATION, IT IS PROVIDED AS IS WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED. IN ADDITION, THIS INFORMATION IS BASED ON IBM S CURRENT PRODUCT PLANS AND STRATEGY, WHICH ARE SUBJECT TO CHANGE BY IBM WITHOUT NOTICE. IBM SHALL NOT BE RESPONSIBLE FOR ANY DAMAGES ARISING OUT OF THE USE OF, OR OTHERWISE RELATED TO, THIS PRESENTATION OR ANY OTHER DOCUMENTATION. NOTHING CONTAINED IN THIS PRESENTATION IS INTENDED TO, NOR SHALL HAVE THE EFFECT OF, CREATING ANY WARRANTIES OR REPRESENTATIONS FROM IBM (OR ITS SUPPLIERS OR LICENSORS), OR ALTERING THE TERMS AND CONDITIONS OF ANY AGREEMENT OR LICENSE GOVERNING THE USE OF IBM PRODUCTS AND/OR SOFTWARE. IBM, the IBM logo, ibm.com, DB2 and IBM Optim Quey Tune ae tademaks o egisteed tademaks of Intenational Business Machines Copoation in the United States, othe counties, o both. If these and othe IBM tademaked tems ae maked on thei fist occuence in this infomation with a tademak symbol ( o ), these symbols indicate U.S. egisteed o common law tademaks owned by IBM at the time this infomation was published. Such tademaks may also be egisteed o common law tademaks in othe counties. A cuent list of IBM tademaks is available on the Web at Copyight and tademak infomation at \ 2

3 Quey Pefomance Causes Application Outage Custome example Application sevice dops fom 3 seconds to 5 minutes Limited pefomance management expetise Took 3 days to identify the poblem quey 5 day application outage Loss of confidence in IT team Time and money in analysts Expet analysis evealed Po o 3 Relevant statistics wee not being collected Wasted CPU esouces due to default statistics collection Index design was vey poo Rapid development pactices dove untuned queies into poduction a d at Po o ign s e d te Was ce u o s d e s Po o ss e c o p

4 Why is Quey Tuning Such a Pain? Development Lack of quey tuning skills Use of famewoks that geneate SQL Inadequate testing envionments to dive the wokload and data scale Disconnect between application and data goups Poduction 4 Pefomance poblems appea without waning Aggegate infomation fom multiple places Complexity of analysis equies specialized skills Need to conside entie wokloads, not just single queies

5 IBM Optim Quey Tune Offeings Optimize pefomance and educe costs Optimize pefomance 5 Impove custome satisfaction Impove oganizational poductivity Satisfy sevice level objectives Fit wokloads into maintenance windows Reduce costs Incease oveall system capacity Reduce chagebacks Simplify analysis fo DBAs, developes, designes, and othes Impove statistics collection efficiency Reduce time to espond

6 Single Quey and Wokload Offeings 6 Development Envionment Poduction Envionment Optim Quey Tune Optim Quey Wokload Tune Tune SQL pe-poduction while costs and impact ae low Optimize wokload fo peak pefomance

7 Expet-Enabled Quey Tuning Out of the Box Identify quey candidates DB2 catalog Dynamic statement cache Development Studio hot spots Quey o pefomance monitos Facilitate analysis Quey fomatting Quey annotation Access path visualization and annotation Get expet tuning advice Impove quey design Impove statistics quality Impove database design 7

8 Steamlined Analysis 8 Define o select wokload Execute advisos Dill into advice Validate impovement

9 Gathe High Cost Queies and Wokloads DB2 Plan table Statement table Define o select wokload Catalog plan o package Statement cache Optim Development Studio QMF and QMF HPO DB2 Quey Monito OMEGAMON XE fo DB2 File, text, o expoted wokload Use defined categoy 9

10 Visualize Queies and Costs to Speed Analysis Easily see tables, sections, join pedicates, etc. Examine table statistics and additional infomation Acceleate analysis, educe downtime Spot human eos Identify whee filteing should occu 10

11 View Optimize Tansfomations Acceleate analysis, educe downtime Spot tansfomations which will occu 11

12 Execute Advisos Statistics Get ecommendations on the best statistics to captue to influence access path selection Quey Get ecommendations egading how to ewite the quey fo bette efficiency Index Get ecommendations on additional indexes that can educe database scans 12

13 Analyze Access Plans Visualize access path See flow of quey pocessing See indexes and opeations See optimize ationale Assess access path stability to educe isk of pefomance egession Is the optimize able to apply the filteing ealy? Ae thee indexes that suppot an efficient path? Do statistics allow distinction between the choices? 13

14 Analyze Access Plans (cont.) Inteogate the plan table to discove access plan flags 14

15 Impove Statistics Quality and Collection Povides advice on Missing statistics Conflicting statistics Out-of-date statistics Geneates RUNSTATS contol statements Results Accuate estimated costs Bette quey pefomance Less CPU consumption Impoved maintenance window thoughput Half of access path PMRs could be esolved by statistics adviso befoe calling IBM suppot. IBM Suppot 15 Indicates conflicting and missing statistics Conflicting statistics explanation

16 Impove Quey Design Guad against eos and ovesights: Futhe constain quey, incease index utilization, and educe data eads View analysis summay Filte ecommendations by seveity Highlights elevant components of the quey Recommendati on and ationale Quey Adviso checks fo Missing join pedicate fo efeential constaint Pedicates that can be ewitten as indexable Stage 2 pedicates that can be ewitten as stage 1 pedicates 16

17 Indexing Advice to Impove Quey Efficiency Impove quey efficiency Indexing foeign keys in queies that do not have indexes defined Identifying index filteing and sceening Suppot fo index only access Indexing to avoid sots Simplify use Consolidate indexes and povide a single ecommendation Enables what-if analysis Povides DDL to ceate indexes Run immediately o save Test befoe deployment Utilize vitual index capabilities built into the DB2 engine 17

18 Validate Impovement Captue wokloads epeatedly to see tuning effects Visualize changes in access plan I was able to test a small wokload in QWT. 213 dynamic statements wee un and captued fom cache. Befoe tuning the wokload was 2.49 cpu seconds and elapsed seconds. Afte the advisos the wokload was 0.42 cpu seconds and 6.33 elapsed seconds. Renee Walton, UPS 18

19 Vesion to Vesion Migation Saved Challenge Pefomance egession discoveed acoss ange of QMF wokloads Client had been using a tick to affect optimize choices that was not available in the new vesion Expected 6-8 months delay plus additional staff costs Delay in pomised value of new database vesion Solution Optim Quey Wokload Tune Handled complexity of queies and wokloads 30 table joins nested behind seveal layes of views Column names changed in views 100s of queies in multiple wokloads Saved hous of time fomatting, annotating, and analyzing queies Recommended additional statistics and pedicates fo bette pefomance Reduced migation fom months to weeks Ode of magnitude eduction in quey wokload analysis. All wokloads as good as o bette than pio vesion. 19

20 Wokload Tuning vs. Quey Tuning Optimization decisions ae based on tadeoffs Statistics CPU costs vs. quey savings Indexing quey speed vs esouce and tansaction Wokload tuning speeds up analysis Analyzes multiple queies at once Wokload tuning consolidates and optimizes ecommendation fo oveall wokload Statistics ecommendations Index ecommendations Speed up analysis, optimize design, and balance esouce usage 20

21 Envionment Captue Facilitates Collaboation Enable envionment epoduction Speed up sevice pocess 21

22 Quey Tune Achitectue Quey Tools Fomatting Annotating Access plan gaph Visual plan hints Repoting Envionment captue Quey Advice Statistics Quey Index Access Path Wokload Advice Statistics Index Wokload contol cente Windows XP o Vista 22 Resticted use DB2 Connect Optim Quey Tune Client Catalog tables QT tables Pofile tables DB2 stoed pocedues fo use with Optim Quey Tune poducts DB2 fo z/os, V8 o late with DDF enabled

23 Steamline Monito and Respond Scenaios DB2 Quey Monito Optim Quey Tune OMEGAMON XE 23

24 Foste coss-ole collaboation Released in Decembe! Challenge Disconnect between application and data goup Solution- vebose HTML file Oveview Recommended actions Input sql statement Access Plan Summay Tansfomed/optimized quey Pedicates Table access Join opeation Table and index catalog infomation: table, column and index 24

25 Reduce Risk of Pefomance Regession Afte Migation Compaing quey costs via an HTML epot Vesion to Vesion migations of DB2 Requies the packages ae bound with EXPLAIN in the old vesion, and then the binds with EXPLAIN ae done on the new vesion into new collections Cases whee a mass-ebind is needed Obtain Access Plan infomation Run Access Plan Cost compaison epot Filte Citeia 25

26 Pevent Poblems Befoe They Impact the Business Identify Poblematic Package Tables View analysis summay based on TOTAL_COST Identify Poblematic SQL statement SQL statement with the highest % cost Tune a single quey o at a wokload level 26

27 Validation Against a Poduction System Clone poject Acceleate development Develop, test, and un queies, pocedues, and functions. Change database connection Enhance poductivity Analyze impact of changes Enhance poblem isolation Be poactive Leveage best pactices fo new development Test befoe deployment Adapt ahead of impact Minimize poduction slowdowns 27 Pefom analysis

28 IBM Optim Quey Tune Offeings Optimize pefomance and educe costs Optimize pefomance 28 Impove custome satisfaction Impove oganizational poductivity Satisfy sevice level objectives Fit wokloads into maintenance windows Reduce costs Incease oveall system capacity Reduce chagebacks Simplify analysis fo DBAs, developes, designes, and othes Impove statistics collection efficiency Reduce time to espond

29 New! Aticle Tuning SQL with Optim Quey Tune, Pat 1: Undestanding access paths Lean how to monito and tune queies and wokloads to impove application pefomance If you ae a develope, DBA, o quey tuning specialist, it is citical that you undestand the basics of access paths so that you can pecisely tune queies and quey wokloads befoe they cause poblems in you poduction envionment. This basic undestanding, coupled with the visualization and tuning advice povided by IBM Optim quey tuning solutions, can help make you moe efficient at this task. This aticle povides conceptual backgound on access paths, shows you how to ead an access path gaph, and walks though the access path gaph to demonstate citical infomation egading access path selection. The aticle concludes with a sample scenaio that demonstates how to use quey annotation, a featue in Optim Quey Tune that helps you with quey analysis by poviding vital statistical infomation diectly in the SQL statement. dm1006optimqueytune1/index.html 29

30 Resouces Integated Data Management Community IBM Optim Quey Wokload Tune web page SQL Tuning, Not just fo hadcoe DBAs anymoe Redbooks at DB2 9 fo z/os Pefomance Topics SG IBM DB2 9 fo z/os: New Tools fo Quey Optimization SG

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32 UGF Usage of Quey Wokload Tune Thei new Pocess to Tune Queies 1.Evey equest of a new object (table o index) fom the application develope 2. Fom daily/weekly/monthly epots on costs 3. Fom stess test afte existing applications upgade 4. Fom alet coming fom the Scheduling office What they liked Statistics Adviso Easiness in tacing dynamic statements W hat-if analysis Quey Envionment Captue 32

33 Daily pefomance epots Afte quey tune activities: AVG CPU: fom 0.08 to *0.03=1500 sec 33

34 f 2 e 1 -f b 5 e 1 -f b 6 e 1 -feb 7 1 -f b 8 e 1 -f b 9 e 2 -f b 2 e 2 -f b 3 e 2 -feb 4 2 -f b 5 e 2 -f b 6 e 1 -feb 2 mab 3m - a 4m - a 5m - a 8m - a 9m 1 - ma 0 1 -ma 1 1 -ma 2 1 -ma 5 1 -ma 6 1 -ma 7 1 -ma 8 1 -ma 9 2 -ma 2 2 -ma 3 2 -ma 4 2 -ma 5 a 2 -m 6 a 2 -m 9 3 -ma 0 3 -ma 1 -ma 1 a 6 ap -a 7 p 8 ap 9 ap -a p ELA f 1 e 1 -f b 2 e 1 -f b 5 e 1 -f b 6 e 1 -f b 7 e 1 -f b 8 e 1 -f b 9 e 2 -f b 2 e 2 -f b 3 e 2 -f b 4 e 2 -f b 5 e 2 -f b 6 e 1 -fe b 2m b - a 3m - a 4m - a 5m - a 8m - a 9m 1 - ma 0 1 -ma 1 1 -ma 2 1 -ma 5 1 -ma 6 1 -ma 7 1 -ma 8 1 -ma 9 2 -ma 2 2 -ma 3 2 -ma 4 2 -ma 5 2 -ma 6 2 -ma 9 3 -ma 0 a 3 m 1 -ma 1 a -a 6 p 7 ap 8 ap 9 ap -a p ELA 0, ,1 0,0014 0,08 0,0012 0,06 0,001 0,0008 0,04 0,0006 0,02 0 0, ,0002 0,12 0,1 0,08 0,06 0,04 0,02 0 SQLLF000 0,0018 0,0016 0,0014 0,0012 0,001 0,0008 CPU 0,14 ELAmed CPU Achievements: SYSSH200 0,002 0,0018 0,0016 ELAmed CPUmed CPUmed 0,0006 0,0004 0,0002 0

35 Examples at XXX of SQL Quey Pefomance Tuning using Quey Wokload Tune PeopleSoft SQL Quey Example #1 - continued This is the epot afte applying the changes ecommended by Quey Tune s Tuning Advisos. STMT_ID befoe ( ) and afte tuning (368), Shows the aveage CPU pe execution impovement and consideing this statement is executed by PeopleSoft evey 30 seconds, the CPU savings will add up 35