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SQL Server 2000 (& 7.0) Execution Plan Cost Formulas Joe Chang

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Presentation on theme: "SQL Server 2000 (& 7.0) Execution Plan Cost Formulas Joe Chang"— Presentation transcript:

1 SQL Server 2000 (& 7.0) Execution Plan Cost Formulas Joe Chang

2 Database Performance Code Tables, Indexes, Constraints, SQL statements Data Total rows, Rows involved, Statistics Execution Plan Formulas used by the CBO Server Architecture Processor, SMP, etc

3 Topics Component Operation Cost Model Cost formulas for basic operations Dependencies Rows & Pages involved - yes Index depth – no, Locks level – no WHERE conditions – no cost for logic only if row count affected

4 Index Seek - 1 row SELECT xx FROM N1C WHERE ID I/OCPUTotal 1GB > 1GB

5 Index Seek Cost Formula Multiple rows, 1GB I/O: per additional page CPU: per additional row Total: /add. Page / add. row

6 Plan Cost Unit of Measure Time? CPU-usage? time, in seconds sec -> 160/sec >1350/sec (8KB) ->169/sec(64K)-> 10.8MB/sec Too fast for 7200RPM disk random I/Os. About right for 1997 sequential disk transfer rate? S2K BOL: Administering SQL Server, Managing Servers, Setting Configuration Options: cost threshold for parallelism Option Query cost refers to the estimated elapsed time, in seconds, required to execute a query on a specific hardware configuration. S2K5 BOL: Administering SQL Server, Managing Servers, Setting Configuration Options: cost threshold for parallelism Option The cost refers to an estimated elapsed time in seconds required to run the serial plan on a specific hardware configuration.

7 Disk Drive Performance Access time = rotational latency + seek time 7200RPM = 4.17ms Rotational Latency 10000RPM = 3ms, 15000RPM = 2ms Rot.Avg.Sequential YearModelRPMSeek Transfer 1994ST K MB/sec 1996ST K ST K ST K * 1999ST K * 2000 ST K * 2002ST K

8 Bookmark Lookup – Single Row Same cost for bookmark lookup on Heap and Clustered Index SQL Server 2000 up to SP3 (build 760) SQL Server 2000 after MS (build 818)

9 Detail up to SP3 (build 760) after MS (build 818)

10 BL Plan Cost – Single Row I/O CPU 1GB > 1GB I/O CPU Total 1GB > 1GB up to SP3 (build 760) after MS (build 818)

11 Bookmark Lookup Multiple Rows A lower I/O cost per page ( ) for up to 64 rows, original I/O cost applies at 65 rows and above For table size up to approx. 100 pages, I/O cost is bounded by the number of pages, representing an estimate of # of I/O required, at cost / page For larger tables, I/O cost is not bounded by the number of pages I/O Cost: up to SP3 (build 760) after MS (build 818) CPU cost per applies in all cases

12 Bookmark Lookup I/O Cost – SP3 By Table Size (pages) versus rows, steps

13 Bookmark Lookup I/O Cost By Table Size (pages) versus rows, steps

14 Bookmark Lookup I/O Cost – SP3 Plan Cost by Table Size (pages) versus rows, SP3 and earlier

15 Bookmark Lookup I/O Cost Plan Cost by Table Size (pages) versus rows, build 818+

16 Bookmark Lookup IO Count For a bookmark lookup for n rows to a table with p pages 1 st row: 1 I/O required 2 nd row: 1 I/O already done, 1-1/p chance additional I/O F(n,p) = F(n-1,p) + 1 – F(n-1,p)/p = F(n-1,p)(1-1/p) + 1 R = 1-1/p F(n,p) = 1 + R + R 2 + … + R n-1 = (1-R n )/(1-R) = p – p (1-1/p) n

17 Table Scan SELECT xx FROM N1H WHERE ID I/O: /page CPU: /row

18 Bookmark versus Scan Table scan cost for 50,000 row, 506 pages Index Seek and Bookmark Lookup cost for 1GB, SP3

19 Aggregates SELECT MIN(x) FROM M2C WHERE GroupID=1 I/O: NoneCPU: /row Aggregate: MIN & MAX Aggregate & Compute Scalar AVG & SUM For single row result

20 Loop, Hash and Merge Joins SQL Server supports 3 types of joins Loop, Hash, Merge Hash join subtypes In memory, Grace, Recursive Different settings for SQL Batch & RPC Merge join one-to-many many-to-many

21 Loop Join Outer Source (Top Input) Inner Source (Bottom Input) Join

22 Loop Join Cost Loop Join Cost = Outer Source Cost + Inner Source Cost + Join Cost

23 Loop Join, cont I/O Cost: 0 CPU Cost per row

24 Loop Join, Inner Source I/O and CPU cost is for 1 execute Cost is for all executes Number of executes is row count from outer source row count is expected matches per row for each row from outer source (rounded down)

25 Loop Join IS Cost Assumptions: CPU Cost: per row applies for 1:1 join IO Cost: Single row base cost same as Index Seek Multiple rows: estimate of number pages required For small IS table (<100 pages) Bounded by per page For large IS table (>200 pages) Bounded by per page for up to 132 rows Approx (1GB) per row for 133 rows and above

26 Loop Join IS I/O Costs (1) Inner Source I/O Cost by table size versus rows Excluding base I/O cost

27 Loop Join IS I/O Costs (2) Inner Source I/O Cost by table size versus rows Excluding base I/O cost

28 Loop Join Costs Small & Big IS Source table size

29 Hash Join Hash Join Cost = Outer Source + Inner Source + Hash Match SELECT * FROM M2C m INNER HASH JOIN M2D n ON n.ID = m.ID WHERE m.GroupID AND n.GroupID

30 Hash Join Cost Outer Source & Inner Source are index seeks or scans 1 execute, 1 or more rows

31 Hash Join - IS Hash join cost independent of IS column count or size

32 Hash Join - OS Hash join cost dependent on OS size Q1 Q2 Q3

33 Hash Join Cost Q1 Q2 Q3

34 Hash Join Cost Formula Base CPU Cost = base Fudge factors (2-30 rows) (100 rows) Cost per row byte, 1 st 100 (1:1 join) >1K (parallel) per row per 4 bytes in OS OS / IS I/O Cost = per row over >64-102MB? per row per 4 byte Hash join spills to tempdb at MB in 32-bit 1-2GB memory 700MB+ in 64-bit with 32GB memory

35 Merge Join Merge Join Cost = Outer Source + Inner Source + Merge cost SELECT xx FROM M2C m INNER MERGE JOIN M2D n ON n.ID = m.ID WHERE m.GroupID AND n.GroupID

36 Merge Join Cost Cost CPU: /row Discrepancy: /row IS /row OS

37 Merge + Sort

38 Many-to-Many Merge I/O: per row CPU: per row

39 Loop, Hash & Merge Join

40 Loop, Hash & Merge Join (2)

41 Loop, Hash & Merge Join (3)

42 1 to Many Joins Each row from OS joins to n rows in IS Join Cost per additional IS row Loop Hash~ Merge ~ IS Index Seek cost: /row + IO costs

43 Sort Cost I/O: CPU: *(rows-1)^1.26 weak dependency on size per row

44 Index Intersection SELECT xx FROM M2C WHERE GroupID AND CodeID SELECT xx FROM M2C a INNER JOIN M2C b ON b.ID = a.ID WHERE a.GroupID AND b.CodeID Table M2x, Index on GroupID Index on CodeID Merge Join cost formula different than previously discussed

45 Execution Plan Costs Recap Index Seek I/OCPUTotal 1GB > 1GB Additional page /p Additional rows /r Bookmark LookupI/OCPUTotal 1GB > 1GB Table ScanI/OCPUTotal Base Additional page /p Additional row /r

46 Logical IO count Example: Index Depth 2, rows per page: 100 I/O per additional row Bookmark Lookup (Heap)1 Bookmark Lookup (Clustered)2 Loop Join (IS)2 I/O per addition 100 rows Index Seek1 Hash & Merge join2 Very little relation between IO count and plan cost for different component operations IO count comparisons more relevant for similar operations

47 Accurate Performance Testing Execution Plan - match Raw size of DB not as important: 1M customers actual, 10K test Cardinality more important 1 Customer – 10 orders – 10 order items per order Statistics & actual data queried Statistics could be accurate but actual queries favors different distribution

48 Aggregates, multiple result rows CPU Cost: per source row per result row CPU Cost per result row:

49 Execution Plan Cost Summary Plan costs do not include RPC cost Plan costs are a model Index seek independent of index depth Bookmark L/U independent of table organization Logic by itself does not influence cost Costs are not influenced by lock hints Populate test DB with accurate cardinality

50 Additional Information SQL Server Quantitative Performance Analysis Server System Architecture Processor Performance Direct Connect Gigabit Networking Parallel Execution Plans Large Data Operations Transferring Statistics SQL Server Backup Performance with Imceda LiteSpeed


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