Query tuning with Optimization Service Center

Transcription

1 Session: F08 Query tuning with Optimization Service Center Patrick Bossman IBM May 20, :00 p.m. 5:00 p.m. Platform: DB2 for z/os 1

2 Agenda Overview of Optimization Service Center Workload (application) Tuning Query tuning 2 IBM Corporation

3 Overview DB2 for z/os Optimization Service Center (OSC) New no-charge offering Included in DB2 Accessories Suite for z/os V1.1 Available via web download Simultaneous availability with DB2 9 for z/os GA in March IBM Corporation

4 VE & OSC feature comparison Functions Queries from Cache, Catalog Query Formatter, Annotation Access Plan Graph Query Report Visual Plan Hint Query Statistics Advisor Workload Statistics Advisor Workload Query Report Profile based Monitoring Visual Explain Yes Yes Yes Yes Optimization Service Center Yes Yes Yes Yes Yes Yes Yes Yes Yes 4 IBM Corporation

5 After connecting, the welcome page is where I go to navigate through OSC. It is the portal into the functions provided by OSC. From the welcome page, you can connect and configure DB2 subsystems, view workloads, view query activity, tune a workload, tune a single query, and view monitor profiles. 5

6 Tuning an application 6 IBM Corporation

7 Application tuning process What is application tuning? Identify what the application workload is Individual SQL statements Get an understanding of the applications behavior How often are individual SQL statements executing? What is the performance of individual SQL statements? Determine statistics for workload Workload statistics advisor More workload analysis features coming (?) Remeasure workload Identify top tuning candidates Use query based tools to further analyze (next session) 7 IBM Corporation 2007 With the introduction of workloads, users can now perform application tuning, rather than just query focused tuning. 7

8 OSC and OE support multiple workload sources. Snapping the statement cache, retrieving SQL from the catalog, QMF and QMF HPO, a file, and other workloads. 8

9 Select a plan, package or set of packages Very flexible filter criteria. 9

10 Choose all packages in a particular collection id with a package name mask. 10

11 Primarily, you d use this tab if you want all the SQL for a particular plan. 11

12 The cost and object filters allow you to supplement package / plan filters. You can further limit the SQL retrieved to match any or all of the criteria specified for the cost and object filters. So if you only want to see SQL which has a PROCMS over a certain value, or SQL which uses a particular index, or SQL which accesses a particular table. 12

13 Only choose queries which have certain access path characteristics 13

14 Capture the workload After selecting packages / plans / filters Click finish to capture workload OSC goes about the business of collecting the statements Queue Jeopardy music, get some coffee. 14 IBM Corporation

15 Workload options shows what you can do with this workload you ve just collected. 15

16 Workload statements shows the SQL within the workload. You should note that executions is set to 1, and there is no runtime execution information contained in this view. For the catalog source, as well as manual input, text file, and QMF sources there is no runtime information available through these workload generation sources. Earlier I indicated that one aspect of workload tuning is understanding the workload how often statements execute and what their performance is, and how that is helpful for guiding analysis. Using the catalog source tells us what SQL are in the workload, but not how often they execute, and what their typical performance is. We will be able to generate SQL targeted statistics recommendations even without knowing the frequency of execution and performance characteristics. So there is value to using this method, but we re still lacking the runtime information which we also would want. 16

17 You can capture more statements using another catalog extraction, or via other workload input options. 17

18 Two things to note: 1) Edit statement runtime information. 2) You can launch the individual query based advisors right from within a workload. We re going to cover the query based tuning tools later. 18

19 Run workload advisors. Note, for Optimization Service Center there currently is only one workload advisor workload statistics advisor. There is a for-charge product built on the same base which includes workload statistics advisor and another advisor. There are other workload analysis features under consideration but not yet available. 19

20 Why statistics advisor? Statistics are collected to help optimizer in costing available access paths Say you interview for a DBA position with three companies, and they all provided offers. What is the salary? How much vacation? How is the commute? Will you have to work weekends, nightshift, how often? What if you had to make a decision between the three offers, and you did not have (accurate) answers to the above questions? Without adequate answers to these questions, what are the odds you d be satisfied with your choice? Statistics advisor is asking these questions of your data for your queries. 20 IBM Corporation 2007 Sometimes I get challenged on what statistics are important and why. I have other presentations and articles which have covered this topic, but I wanted to use a metaphor to personalize the type of decision the optimizer has to make. 20

21 Workload statistics advisor recommendations page. 21

22 Workload Statistics Advisor will ALWAYS generate complete workload statistics recommendation. It will recommend recollection of the statistics you ve got, and supplement with any correlation (COLGROUP and KEYCARD) and skew (frequencies, histograms) which it believes are required based on the predicates in your SQL. If you ve collected all the statistics that statistics advisor thinks are necessary, it will STILL generate a complete suggestion marked as high priority, but the LOW priority repair recommendation will disappear. This has caused some confusion with users. The primary purpose of WSA is to generate a complete, targeted statistics recommendation which recollects existing statistics as well as supplementing with missing / conflicting statistics. If the low priority repair suggestion is absent, then WSA has determined that your statistics are good. We re working on a GUI change which will make this more clear. 22

23 Runstats control statements This section contains the actual RUNSTATS suggestions. 23

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26 Output looks complex RUNSTATS commands are more targeted Only collect on tables used in queries Only collect column statistics on columns used as predicates Collect frequency and histogram statistics based on predicates which would benefit 26 IBM Corporation

27 Pause for questions on WSA? 27 IBM Corporation

28 Cache statement view Cache statement view Number of executions Accumulated & average CPU time Accumulated & average elapsed time SQL text Cache as input provides more visibility into how often SQL executing, cost of statements 28 IBM Corporation 2007 When you snap the dynamic statement cache, if you ve got IFCID turned on, you also get runtime information. So with the dynamic statement cache source input, you can get a better picture of how often SQL are running and it s performance characteristics which is useful for targeting your tuning efforts, understanding your application, and for measuring performance improvements. One drawback of the statement cache is it s a snapshot in time. Some SQL run by the application may not have executed yet, or their frequency of execution could be underreported depending on when the snapshot is taken. So it s not an ideal way to get an accurate profile of all SQL for an application. 28

29 When you snap the statement cache, you get runtime information. The runtime information from a snap of the statement cache has limitations. What if you snapped the statement cache early in the workload and an important statement is underrepresented from a number of executions perspective? It could be underrated from index advisor analysis perspective. Some SQL for the workload may have been flushed from the cache, or not yet put into the cache. So we can t be sure we have a complete picture of the workload. So it s imperfect, but having the runtime information is still more valuable than having nothing. 29

30 Monitor workload Normal monitor workload All SQL based on certain criteria Obtain runtime information for all monitored SQL (including static) Useful to profile an application Which SQL running most frequently? Which queries consuming most elapsed / execution time? Useful to identify which SQL are consuming most resources, tuning opportunities Exception monitor Workload generated based on exception criteria All SQL for package > x seconds elapsed All SQL for package > x seconds elapsed 30 IBM Corporation 2007 Workload monitoring is the ideal way to profile an application. You can define a workload consisting of plan, or a set of packages, as well as an IP address authid combination for remote dynamic SQL. You can then start the monitor, and perform a controlled run the application. When the application completes, or runs long enough to get a good perspective of the application, stop the monitoring. A workload is generated containing all the SQL which executed static or dynamic - with runtime information. Exception monitoring takes the scope of normal monitoring and overlays the option of setting CPU consumption thresholds to build a workload for all application SQL which exceeds the defined thresholds. 30

31 Create a normal or exception monitor. 31

32 You can build a list of packages as well as dynamic statements to monitor. 32

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34 Just wanted to show a snapshot of the runtime information for static SQL. Number of executions, accumulated / average elapsed times, and accumulated / elapsed CPU times. 34

35 For an exception monitor, you set thresholds on which statements will generate the workload. This is useful to generate a workload from SQL consuming high CPU. 35

36 Application tuning Normal monitor allows for capture of all SQL Specify list of packages Prevents workload pollution which can occur with statement cache Capture valuable execution information Ideally initially used in QA environment to profile / tune application before production implementation How often does this execute? How long does this run? you can have answers to these questions Selectively use in production to develop application profile and tune application 36 IBM Corporation

37 Which workload source to use? Which workload source provides Identification of static and dynamic SQL statements executed Statement execution information Statement accumulated and average execution CPU and elapsed times Provides runtime information for any source Can re-measure and expect to see the same SQL again, compare results Is not polluted with dynamic SQL which are not relevant to the application? Workload monitoring (normal) 37 IBM Corporation

38 End of Workload tuning Next up, Query tuning with OSC Statistics Advisor Query annotation Query report Visual Explain Visual plan hint 38 IBM Corporation

39 Tuning a query Steps to tuning a query Identify statement Collect information regarding SQL Formatted SQL Physical design of referenced objects Statistics Access path Advisor output (like having another DBA perspective) Mentally compute, is access path efficient? Could we do better? 39 IBM Corporation

40 From the welcome page. Easist route to tuning a query is to select. Tune a query! 40

41 Pick your query. Note We ve buried things like the CURRENT DEGREE special register, CURRENT SCHEMA, explain with stored procedure within the Specify Query Context area. So, do take a whirl into that area to familiarize yourself. 41

42 I believe this is self explanatory... 42

43 One big improvement of OSC over Visual Explain is the consolidation of sources. Within VE, explaining dynamic SQL, static SQL, or looking at the dynamic statement cache the query inputs were scattered in different menu options. Some buried so well, you d hardly know there was any option at all. Early on, Statistics Advisor in VE only worked with a dynamically explained SQL (eventually, it was expanded in VE to support static, and explain from statement cache). Anyway, OSC has consolidated the query input options, and the query action options. You go to one place and you can get a query from any of the supported inputs. All of the query tools are available for all of the various input methods using a consolidated common interface. Personally, I think this is much cleaner. 43

44 Another significant improvement over VE With VE, when you used the statement cache interface, you had to define your filter and sort criteria over and over again. With OSC, there are some canned views, which display the statement cache in several desirable display and sort sequences. So you can choose from our preconfigured views (if you don t like them it s my fault). Alternately, you can create your own filter / sort / display view and save it for repeating use. I think this is a small, but very significant usability improvement. 44

45 Other cache improvements Design your own cache display view Choose filter criteria Choose how to sort rows retrieved from cache Choose which columns to display After rows retrieved, you can re-sort the rows displayed on the screen also Vastly improved statement cache interface One-time setup, repeating use 45 IBM Corporation

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47 After you ve selected a query Query options Run SQL Categorize SQL Advisors Run statistics advisor Tools Query annotation Query graph Visual Plan Hint Query report 47 IBM Corporation

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51 Original SQL Query annotation Format SQL Annotate SQL with statistics Helpful highlighting Expand / collapse query sections 51 IBM Corporation 2007 Just FYI Query annotation is probably the favorite feature of the entire product for the team that performs SQL service. Very often, we are provided completely unformatted and unanalyzed queries. Query annotation formats and provides both the original and transformed SQL text so that it s readable. It then annotates the SQL with valuable statistics and important costing information like qualified rows estimates at the table level, and estimated filtering at the predicate level. Let s take a look 51

52 Original SQL SELECT S_SUPPKEY, S_NAME, SUM(L_EXTENDEDPRICE*(1-L_DISCOUNT)) AS REVENUE FROM SYSADM.ORDER, SYSADM.LINEITEM, SYSADM.SUPPLIER WHERE L_ORDERKEY = O_ORDERKEY AND S_SUPPKEY = L_SUPPKEY AND O_ORDERDATE >= DATE(' ') AND O_ORDERDATE < DATE(' ') + 3 MONTH AND L_RETURNFLAG = 'R' AND S_NATIONKEY IN (1,2,3,4,5) AND S_SUPPKEY < GROUP BY S_SUPPKEY, S_NAME HAVING SUM(L_EXTENDEDPRICE*(1-L_DISCOUNT)) > ORDER BY REVENUE DESC QUERYNO 3 52 IBM Corporation 2007 You see, when someone sends me an SQL like this, I know that they have done absolutely nothing to analyze this SQL. If you can t read it, you can t analyze it. 52

53 Formatted SELECT SYSADM.SUPPLIER.S_SUPPKEY, SYSADM.SUPPLIER.S_NAME, SUM( SYSADM.LINEITEM.L_EXTENDEDPRICE * ( 1 - SYSADM.LINEITEM.L_DISCOUNT ) ) AS REVENUE FROM SYSADM.SUPPLIER, SYSADM.ORDER, SYSADM.LINEITEM WHERE ( SYSADM.LINEITEM.L_ORDERKEY = SYSADM.ORDER.O_ORDERKEY AND SYSADM.SUPPLIER.S_SUPPKEY = SYSADM.LINEITEM.L_SUPPKEY AND SYSADM.LINEITEM.L_RETURNFLAG = 'R' AND SYSADM.ORDER.O_ORDERDATE < ( DATE( ' ' ) + 3 MONTHS ) AND SYSADM.ORDER.O_ORDERDATE >= DATE( ' ' ) AND SYSADM.SUPPLIER.S_NATIONKEY IN ( 1, 2, 3, 4, 5 ) AND SYSADM.SUPPLIER.S_SUPPKEY < ) GROUP BY SYSADM.SUPPLIER.S_SUPPKEY, SYSADM.SUPPLIER.S_NAME HAVING SUM( SYSADM.LINEITEM.L_EXTENDEDPRICE * ( 1 - SYSADM.LINEITEM.L_DISCOUNT ) ) > ORDER BY REVENUE DESC 53 IBM Corporation 2007 Snap, SQL is formatted. Nice feature all by itself. 53

54 Annotated SELECT SYSADM.SUPPLIER.S_SUPPKEY, SYSADM.SUPPLIER.S_NAME, SUM( SYSADM.LINEITEM.L_EXTENDEDPRICE * ( 1 - SYSADM.LINEITEM.L_DISCOUNT ) ) AS REVENUE FROM SYSADM.SUPPLIER CARDF=10,000 QUALIFIED_ROWS=1, NPAGESF=402, SYSADM.ORDER CARDF=1,500,000 QUALIFIED_ROWS=57, NPAGESF=42,417, SYSADM.LINEITEM CARDF=4,254,339 QUALIFIED_ROWS=1,048,737.0 NPAGESF=141,743 WHERE ( SYSADM.LINEITEM.L_ORDERKEY = SYSADM.ORDER.O_ORDERKEY COLCARDF=1,063,455/1,500,00 MAX_FREQ= %/ FF= E-7 AND SYSADM.SUPPLIER.S_SUPPKEY = SYSADM.LINEITEM.L_SUPPKEY COLCARDF=10,000/10,000 MAX_FREQ=99.99%/ % FF= E-5 AND SYSADM.LINEITEM.L_RETURNFLAG = 'R' COLCARDF=4 MAX_FREQ= % FF= AND SYSADM.ORDER.O_ORDERDATE < ( DATE( ' ' ) + 3 MONTHS ) COLCARDF=2,304 MAX_FREQ=0.0414% FF= LOW2KEY= HIGH2KEY= AND SYSADM.ORDER.O_ORDERDATE >= DATE( ' ' ) COLCARDF=2,304 MAX_FREQ=0.0414% FF= LOW2KEY= HIGH2KEY= AND SYSADM.SUPPLIER.S_NATIONKEY IN ( 1, 2, 3, 4, 5 ) COLCARDF=25 MAX_FREQ=4.21% FF= AND SYSADM.SUPPLIER.S_SUPPKEY < COLCARDF=10,000 MAX_FREQ=99.99% FF= LOW2KEY=2 HIGH2KEY=9999 ) GROUP BY SYSADM.SUPPLIER.S_SUPPKEY, SYSADM.SUPPLIER.S_NAME HAVING SUM( SYSADM.LINEITEM.L_EXTENDEDPRICE * ( 1 - SYSADM.LINEITEM.L_DISCOUNT ) ) > FF= ORDER BY REVENUE DESC 54 IBM Corporation 2007 Now, take the formatted SQL, and add some costing information into it. 54

55 Here s what it looks like inside OSC. 55

56 Annotation table details Table annotations CARDF number of rows in the table NPAGESF number of pages Qualified rows optimizer estimated number of rows after local filtering (as though table is the outer table) Value Poor join sequence often due to inaccurate filtering estimate at the single table level Qualified rows shows optimizer estimate, is it accurate? CARDF, NPAGESF useful to have this embedded as you re looking at SQL and predicates 56 IBM Corporation 2007 Definition of some of the annotations. 56

57 Annotation table close-ups SELECT cols FROM SYSADM.SUPPLIER CARDF=10,000 QUAL_ROWS=1, NPAGESF=402, SYSADM.ORDER CARDF=1,500,000 QUAL_ROWS=57, NPAGESF=42,417, SYSADM.LINEITEM CARDF=4,254,339 QUAL_ROWS=1,048,737.0 NPAGESF=141, IBM Corporation

58 Annotation predicate details Column information COLCARDF number of distinct values for a column. For join predicate, both COLCARDF s shown Show selectivity of each predicate Max Freq Maximum frequency (if collected) Skew statistics collected? Show most skewed frequency (indicator of degree of skew) 58 IBM Corporation

59 Annotation predicate details Column information (cont.) FF (filter factor) optimizer single predicate filter factor estimate Show optimizer filtering estimate Is it accurate? (Compare to actual filtering) LOW2KEY / HIGH2KEY shown for range predicates. Observe literal value with domain of actual values Can spot stale columns statistics Eg. HIGH2KEY = , you ve got 2007 data in the table WHERE SALES_DT BETWEEN AND IBM Corporation

60 Annotation predicate close-up ( SYSADM.LINEITEM.L_ORDERKEY = SYSADM.ORDER.O_ORDERKEY AND SYSADM.SUPPLIER.S_SUPPKEY = SYSADM.LINEITEM.L_SUPPKEY AND SYSADM.LINEITEM.L_RETURNFLAG = 'R' AND SYSADM.ORDER.O_ORDERDATE < ( DATE( ' ' ) + 3 MONTHS ) AND SYSADM.ORDER.O_ORDERDATE >= DATE( ' ' ) AND SYSADM.SUPPLIER.S_NATIONKEY IN ( 1, 2, 3, 4, 5 ) AND SYSADM.SUPPLIER.S_SUPPKEY < COLCARDF=1,063,455/1,500,00 MAX_FREQ= %/ FF= E-7 COLCARDF=10,000/10,000 MAX_FREQ=99.99%/0.0119% FF= E-5 COLCARDF=4 MAX_FREQ= % FF= COLCARDF=2,304 MAX_FREQ=0.0414% FF= LKEY= HKEY= COLCARDF=2,304 MAX_FREQ=0.0414% FF= LOW2KEY= HIGH2KEY= COLCARDF=25 MAX_FREQ=4.21% FF= COLCARDF=10,000 MAX_FREQ=99.99% FF= LOW2KEY=2 HIGH2KEY= IBM Corporation

61 General annotation comments SQL analysis Start at the table level Identify any tables where qualified rows estimate looks off Examine predicates on that table Any individual predicates look too Optimistic? Pessimistic? Frequencies, histograms? After individual predicates are OK, any unaddressed correlation? KEYCARD, COLGROUP? Difficult to estimate predicate? WHERE SUBSTR(C1,1,4) = ABCD 61 IBM Corporation

62 Query annotation transformed SQL Transformed SQL All original SQL annotation benefits plus Show optimizer rewritten SQL Predicate transitive closure Predicate transformations Distribution and pruning Merge / materialization 62 62

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70 Query report Easy to read report which shows Database / table space Table Index Indexed columns Column group cardinality Quick reference Statistics on objects Statistics on indexed columns KEYCARD statistics mapped into index 70 IBM Corporation

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72 New SQL SELECT <cols> FROM SYSIBM.SYSPACKSTMT AS A, SYSIBM.SYSPACKAGE AS C WHERE ( A.QUERYNO > -1 AND C.COLLID = 'TEST' AND C.NAME = 'PGM1' AND A.COLLID = C.COLLID AND A.LOCATION = C.LOCATION AND A.NAME = C.NAME AND A.VERSION = C.VERSION ) ORDER BY <cols> 72 IBM Corporation

73 Query report table 1 73 IBM Corporation

74 Query report table 2 Looks like someone forgot to run RUNSTATS Hey this is MY database! 74 IBM Corporation

75 Statistics advisor says RUNSTATS TABLESPACE DSNDB06.SYSPKAGE TABLE(SYSIBM.SYSPACKSTMT) COLUMN(NAME,QUERYNO,VERSION,COLLID) TABLE(SYSIBM.SYSPACKAGE) COLUMN(NAME,VERSION,COLLID) INDEX(SYSIBM.DSNKSX01 KEYCARD,SYSIBM.DSNKKX02 KEYCARD,SYSIBM.DSNKKX01 KEYCARD) SHRLEVEL CHANGE REPORT YES 75 IBM Corporation

76 Query report table 1 Nice to see cascading MCARD s Only matching on 2 or 3 columns? Easy to see the KEYCARD bound 76 IBM Corporation

77 Query report table 2 Easy to read index, indexed columns report. Observations Clusterratiof of DSNKKX01? (reorg?) COLCARDF of CONTOKEN? Not used as a predicate! 77 IBM Corporation

78 Visual explain Access Plan Graph Ported from Visual Explain product Graphically display access path 78 IBM Corporation

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80 Access plan graph 80 IBM Corporation

81 Access plan graph 81 IBM Corporation

82 Query graph overview Reading query graph Read from bottom up Left to right 82 IBM Corporation

83 Access plan graph 83 IBM Corporation

84 Access plan graph zoom 84 IBM Corporation

85 Query graph zoom reading Access index Plan_table_IDX1 Qualifies 2 rows Fetch from table Plan table has 930 rows Approximately 1.6 survive Inner table is accessed approximately 1.6 times 85 IBM Corporation

86 Access plan graph zoom 86 IBM Corporation

87 Descriptor 87 IBM Corporation

88 Descriptor 88 IBM Corporation

89 Descriptor Displays detailed information Descriptor changes as you navigate plan graph Click on index node for index information Click on table node, table information shown Double click node will pop-up independent descriptor window for node 89 IBM Corporation

90 Index descriptor Index node information Index creator, name Statistics on index Uniqueness Clustering attribute 90 IBM Corporation

91 Index scan descriptor Index scan information Index cardinality Index leaf pages Matching predicates Individual matching predicate filter factor Bounded matching predicate filter factor Total index filtering (matching and screening) Estimated scanned leaf pages Estimated index qualified rows 91 IBM Corporation

92 There s more Other information Identify matching, screening, S1, S2 predicates Filter factors for predicates Qualified partitions Parallelism Key range Page Range Degree of parallelism Sort keys, sort key length Estimated number of records at Index matching, total index filtering Data access Sort input / output Join 92 IBM Corporation

93 Textual explain view 93 IBM Corporation 2007 See the box on the bottom left? We added textual explain output for those that like textual explain output (umm, like me). 93

94 Textual explain view OSC shows plan_table rows Short / long format this is obviously a truncated view 94 IBM Corporation

95 Visual Plan Hint Visual Plan Hint Graphically alter the explain table Will show an overview More details included as part of Optimization hints presentation

96 Join graph, starting plan 96 On the left, a join graph shows all of the tables that are joined to each other. On the right is where the optimization hint is built. Buttons at the top allow the local and join predicates to be annotate the join graph. The Default Join Sequence drive Visual Plan Hint to start with the optimizer chosen access path. 96

97 Join graph, starting plan Double click to change access attributes 97 On the left, a join graph shows all of the tables that are joined to each other. On the right is where the optimization hint is built. Buttons at the top allow the local and join predicates to be annotate the join graph. The Default Join Sequence drive Visual Plan Hint to start with the optimizer chosen access path. 97

98 Join graph, starting plan 98 This opens a pop up screen which allows you to customize the access to the table. You can change the access method, join method, prefetch, optional sorts. So using visual plan hint makes it easy to make simple alterations to your existing access path, and let visual plan hint handle the mechanics of generating the records for the PLAN_TABLE. 98

99 Change join sequence step 1 Left click on the join graph, then delete 99 On the left, a join graph shows all of the tables that are joined to each other. On the right is where the optimization hint is built. Buttons at the top allow the local and join predicates to be annotate the join graph. The Default Join Sequence drive Visual Plan Hint to start with the optimizer chosen access path. 99

100 Change join sequence step 2 Reconnect the repositioned tables to join nodes. 100 On the left, a join graph shows all of the tables that are joined to each other. On the right is where the optimization hint is built. Buttons at the top allow the local and join predicates to be annotate the join graph. The Default Join Sequence drive Visual Plan Hint to start with the optimizer chosen access path. 100

101 Validate hints 101 Deploy hints brings up a pop up window where you can change query level optimization hints settings. You set the hint name, query number, application and program names, collection id, version, and explain table qualifier to place the hint. 101

102 Validate hint 102 Differences are highlighted in red for easy identification / analysis. You can tell if the access path you end up with is different from the hint you submitted, and what is also different from the original. I have only shown the hint input and hint output, not the original due to display constraints. 102

103 Visual Plan Hint Summary Visual Plan Hint Graphically alter the explain table Use of drop down lists reduces errors Validation of optimization hint built in Colorful compare of before / after access path, very nice

104 OSC Summary Optimization Service Center overview Support for workloads, workload advisors Monitoring allows for profiling of applications and exception generated workloads Consolidated inputs / outputs Improved statement cache display (allow customized views) Improved query tuning tools Statistics advisor Annotation Query report Access plan graph Visual plan hint 104 IBM Corporation

105 Session F08 Query tuning with Optimization Service Center Patrick Bossman IBM