1. Modern Performance - SQL Server Joe Chang www.qdpma.com Jchang6 @ yahoo

2. About Joe SQL Server consultant since 1999 Query Optimizer execution plan cost formulas (2002) True cost structure of SQL plan operations (2003?) Database with distribution statistics only, no data 2004 Decoding statblob/stats_stream – writing your own statistics Disk IO cost structure Tools for system monitoring, execution plan analysis See http://www.qdpma.com/http://www.qdpma.com/ Download: http://www.qdpma.com/ExecStatsZip.htmlhttp://www.qdpma.com/ExecStatsZip.html Blog: http://sqlblog.com/blogs/joe_chang/default.aspxhttp://sqlblog.com/blogs/joe_chang/default.aspx

3. Overview General SQL Server Performance Why performance is still important today? – Brute force? Yes, but … Special Topics – spectacular fails Automating data collections SQL Server Engine – What developers/DBA need to know?

4. Not in this session List of rules to be followed blindly without consideration for the underlying reason and whether rule actually applies in the current circumstance DBA skill: cause and effect analysis & assessment

5. Common Themes? execution plan – Very large (multiple order of magnitude) error in row estimate Single (execute) of large operation – Might still be tolerable Multiple (executes) of large operations

6. select a.Header, a.CUSIP, a.SecNo, a.Security, a.Symbol,a.Split_rep, a.Sales_Person_Name,cast(sum(a.January) as float) as January,cast(sum(a.February) as float) as February,cast(sum(a.March) as float) as March,cast(sum(a.April) as float) as April,cast(sum(a.May) as float) as May,cast(sum(a.June) as float) as June,cast(sum(a.July) as float) as July,cast(sum(a.August) as float) as August,cast(sum(a.September) as float) as September,cast(sum(a.October) as float) as October,cast(sum(a.November) as float) as November,cast(sum(a.December) as float) as December,cast(sum(a.Total) as float) as Total from( select cast(hdr.Header as varchar(100)) as Header,cast(AcctSec.CUSIP as varchar(100)) as CUSIP,cast(AcctSec.Sec_No as varchar(100)) as SecNo,cast(AcctSec.Sec_Desc1 as varchar(100)) as Security,cast(AcctSec.Symbol as varchar(100)) as Symbol,case when RefMonth.[MonthName] = 'January' then fct.Comm else 0 end as January,case when RefMonth.[MonthName] = 'February' then fct.Comm else 0 end as February,case when RefMonth.[MonthName] = 'March' then fct.Comm else 0 end as March,case when RefMonth.[MonthName] = 'April' then fct.Comm else 0 end as April,case when RefMonth.[MonthName] = 'May' then fct.Comm else 0 end as May,case when RefMonth.[MonthName] = 'June' then fct.Comm else 0 end as June,case when RefMonth.[MonthName] = 'July' then fct.Comm else 0 end as July,case when RefMonth.[MonthName] = 'August' then fct.Comm else 0 end as August,case when RefMonth.[MonthName] = 'September' then fct.Comm else 0 end as September,case when RefMonth.[MonthName] = 'October' then fct.Comm else 0 end as October,case when RefMonth.[MonthName] = 'November' then fct.Comm else 0 end as November,case when RefMonth.[MonthName] = 'December' then fct.Comm else 0 end as December,fct.Comm as Total,AcctEmp.split_rep,AcctEmp.Sales_Person_Name from PayoutSystemDW.[dbo].[PS_FactAccountSummary] fct join PayoutSystemDW.dbo.PS_DimensionRptBus RptBus on fct.DimRptBusID = RptBus.DimRptBusID join PayoutSystemDW.dbo.PS_DimensionHeader hdr on fct.DimHeaderID = hdr.DimHeaderID join PayoutSystemDW.dbo.PS_DimensionCurrency cur on fct.DimCurID = cur.DimCurID and cur.DimCurID = 1 join PayoutSystemDW.dbo.PS_DimensionAcctEmp AcctEmp on fct.DimAcctEmpID = acctemp.DimAcctEmpID and AcctEmp.Empno = 8125 and AcctEmp.Split_rep in ('PB54') join PayoutSystemDW.dbo.PS_DimensionAcctSec AcctSec on fct.DimAcctSecID = AcctSec.DimAcctSecID join PayoutSystemDW.dbo.PS_DimensionRefBuySell bs on fct.DimRefBuySellID = bs.DimRefBuySellID join PayoutSystemDW.[dbo].[PS_DimensionAcctOrg] AcctOrg on fct.DimAcctOrgID = AcctOrg.DimAcctOrgID and AcctOrg.OrgCode in ('38C') join PayoutSystemDW.[dbo].[PS_DimensionAcctClt] as AcctClt on AcctClt.DimAcctCltID = AcctClt.DimAcctCltID and AcctClt.ClientName = 'BRACY DENNIS M' join PayoutSystemDW.dbo.PS_DimensionTradeInd ti on ti.DimTradeIndID = fct.DimTradeIndID and ti.[Trade_Ind_Year] = 2014 join PayoutSystemDW.dbo.PS_DimensionRefMonth RefMonth on RefMonth.MonthID = ti.Trade_Ind_Month where RptBus.ReportID = 1 ) a group by a.Header, a.CUSIP, a.SecNo, a.Security, a.Symbol,a.Split_rep,a.Sales_Person_Name

7. select fct.Comm as Total, … From FactAccountSummary fct join DimensionRptBus RptBus on fct.DimRptBusID = RptBus.DimRptBusID Join DimensionCurrency cur on fct.DimCurID = cur.DimCurID join DimensionRefBuySell bs on fct.DimRefBuySellID = bs.DimRefBuySellID join DimensionAcctOrg] AcctOrg on fct.DimAcctOrgID = AcctOrg.DimAcctOrgID join DimensionAcctClt as AcctClt on AcctClt.DimAcctCltID = AcctClt.DimAcctCltID

8. QPI CPU & Memory 2001 versus 2014 Xeon E7 v2 (Ivy Bridge), 15 cores, 3 QPI 4 x 15 = 60 cores 3TB (96 x 32GB) 24 DIMMs per socket 40 PCI-E gen3 lanes + x4 g2 / socket 2001 – 4 sockets, 4 cores Pentium III Xeon, 900MHz 4-8GB memory? Xeon MP 2002-4 FSB P L2 PPP MCH Each core today is more than 10x over Pentium III (700MHz?) Mem___2013 __ 2014 16GB __ $191 __ $180 32GB __ $794 __ $650 64GB _____ __ $4510 PCH DMI x4 MC GFX QPI MI PCI-E MI C1 C2 C3 C0 C4 C8 C7 C6 C9 C5 LLC 11 12 13 10 14 QPI MI PCI-E MI C1 C2 C3 C0 C4 C8 C7 C6 C9 C5 LLC 11 12 13 10 14 QPI MI PCI-E MI C1 C2 C3 C0 C4 C8 C7 C6 C9 C5 LLC 11 12 13 10 14 QPI MI PCI-E MI C1 C2 C3 C0 C4 C8 C7 C6 C9 C5 LLC 11 12 13 10 14 DMI 2 PCI-E DMI 2 PCI-E

9. CPU & Memory 2001 versus 2012 Xeon E5 (Sandy Bridge), 8 cores, 2 QPI 4 x 8 = 32 cores total Westmere-EX 1TB (64x16GB) (3 QPI) Sandy Bridge E5: 768GB (48 x 16GB) (2 QPI) FSB P L2 PP P MCH QPI DMI 2 PCI-E 2001 – 4 sockets, 4 cores Pentium III Xeon, 900MHz 4-8GB memory? Xeon MP 2002-4 Each core today is more than 10x over Pentium III (700MHz?) Mem___2013 __ 2014 16GB __ $191 __ $180 32GB __ $794 __ $650 64GB _____ __ $4510 QPI PCI-E QPI MI PCI-E C1C6 C2C5 C3C4 LLC QPI MI C7C0 DMI 2 PCI-E MI PCI-E C1C6 C2C5 C3C4 LLC QPI MI C7C0 PCI-E MI PCI-E C1C6 C2C5 C3C4 LLC QPI MI C7C0 MI PCI-E C1C6 C2C5 C3C4 LLC QPI MI C7C0

10. Intel E5 & E7 v2 (Ivy-Bridge) PCH DMI x4 MC GFX E3 v3

11. Processor – Core

12. Microprocessor Pipeline Branch Predict Instruction Fetch Decode Register Allocate & Rename Re-Ordering Buffer Schedule Execute Flags Retire BP IFIDRATROBSchExecFlags 1st RetireBPIFIDRATROBSchExecFlags 2nd Retire 3GHz 0.33ns clock 5 ns from start to finish 200MHz Microprocessor (core) is (multi-lane) assembly line Each core is superscalar Processor (socket) has multiple cores System has multiple sockets

13. Micro-architecture Sandy-Bridge

14. Haswell (Xeon E5/7 v3)

15. CPU Access Times L1 IL1 D L2 Unified L3 Slice DRAM Core – 3.33GHz 1 CPU cycle = 0.3ns L1 cache – 4 CPU clocks (1ns) L2 cache 12 CPU cycles (4ns?) L3 cache 29+ cycles Local node memory 28 cycles + 49 ns (open page) 28 cycles + 56 ns (random page) Remote node (1-hop) memory 28 + 100ns 2-hop 150-300ns+? Logical 0 Logical 1

16. Latency Orders of Magnitude PCH DMI x4 MC GFX Core Core – 3.33GHz 1 CPU cycle = 0.3ns L1 cache – 4 CPU clocks (1ns) L2 cache 12 CPU cycles (4ns?) L3 cache 29+ cycles Local node memory 28 cycles + 49 ns (open page) 28 cycles + 56 ns (random page) Remote node (1-hop) memory 28 + 100ns 2-hop 150-300ns+? L1 Cache LLC

17. Westmere-EX 8-Socket System QPI IOH 0 QPI IOH 1 QPI IOH 2 QPI IOH 3 PCI-E x8 PCI-E x4 ESI PCI-E x8 PCH C2 C1 C0 C7 C8 C9 C4C5 QPI C3C6 MC LLC MC QPI C2 C1 C0 C7 C8 C9 C4C5 QPI C3C6 MC LLC MC QPI C2 C1 C0 C7 C8 C9 C4C5 QPI C3C6 MC LLC MC QPI C2 C1 C0 C7 C8 C9 C4C5 QPI C3C6 MC LLC MC QPI C2 C1 C0 C7 C8 C9 C4C5 QPI C3C6 MC LLC MC QPI C2 C1 C0 C7 C8 C9 C4C5 QPI C3C6 MC LLC MC QPI C2 C1 C0 C7 C8 C9 C4C5 QPI C3C6 MC LLC MC QPI C2 C1 C0 C7 C8 C9 C4C5 QPI C3C6 MC LLC MC QPI Large server systems are very complicated Software developed without consideration for system architecture will likely have severe problems This applies to the OS, SQL Server and the application SMB

18. Storage 2001 versus 2012/13 QPI 192 GB PCIe x8 PCIe x4 IBRAID 10GbE HDD SSD 2001 100 x 10K HDD 125 IOPS each = 12.5K IOPS IO Bandwidth limited: 1.3GB/s (1/3 memory bandwidth) 2013 64 SSDs, >10K+ IOPS each, 1M IOPS total possible 10-20GB/s+ IO Bandwidth easy 6.4GB/s on each PCIe G3 x8 SAN vendors – questionable BW PCI MCH RAID HDD http://www.qdpma.com/Storage/Storage2013.html http://www.qdpma.com/ppt/Storage_2013.pptx

19. SAN SSD10K7.2K Hot Spares Auto-tier pools Switch SP ASP B 8 Gb FC x4 SAS 2GB/s 24 GB HBA PCIe or 10Gb FCOE 0.8 GB/s x4 SAS 2GB/s Data 5Data 6Data 7Data 1Data 2Data 3Data 4Data 8Data 9Data 13Data 10Data 14Data 11Data 15Data 12Data 16SSD 1SSD 2SSD 3SSD 4Log 1Log 2Log 3Log 4 Node 1 1024 GB Node 2 1024 GB Switch SP ASP B 8 Gb FC 24 GB SSD x8 SSD x8 SSD x8 SSD Node 1Node 2 768 GB http://sqlblog.com/blogs/joe_chang/archive/2013/05/10/enterprise-storage-systems-emc-vmax.aspx http://sqlblog.com/blogs/joe_chang/archive/2013/02/25/emc-vnx2-and-vnx-future.aspx

20. Performance Past, Present, Future When will servers be so powerful that … – Been saying this for a long time Today – 10 to 100X overkill – 32-cores in 2012, 60-cores in 2014 – Enough memory that IO is only sporadic – Unlimited IOPS with SSD What can go wrong? Today’s topic

21. SQL Performance Natural keys with unique indexes, not SQL The Execution Plan links all the elements of performance Index tuning alone has limited value Over indexing can cause problems as well Index and Statistics maintenance policy 1 Logic may need more than one execution plan? Compile cost versus execution cost? Tables and SQL combined implement business logic Plan cache bloat? SQL Tables natural keys Indexes Execution Plan Statistics & Compile parameters Compile Row estimate propagation errors Storage Engine Hardware DOP Memory Parallel plans Recompile temp table / table variable Query Optimizer Index & Stats Maintenance API Server Cursors: open, prepare, execute, close? SET NO COUNT Information messages

22. Factors to Consider SQLTablesIndexes Query Optimizer Statistics Compile Parameters Storage Engine Hardware DOP memory

23. Special Topics Data type mismatch Multiple Optional Search Arguments (SARG) – Function on SARG Parameter Sniffing versus Variables Statistics related (big topic) OR, AND/OR combinations IN/NOT IN, EXISTS Complex Query with sub-expressions Parallel Execution Not in order of priority http://blogs.msdn.com/b/sqlcat/archive/2013/09/09/when-to-break-down-complex-queries.aspx

24. 1a. Data type mismatch DECLARE @name nvarchar(25) = N'Customer#000002760' SELECT * FROM CUSTOMER WHERE C_NAME = @name SELECT * FROM CUSTOMER WHERE C_NAME = CONVERT(varchar, @name).NET auto-parameter discovery? Unable to use index seek Table column is varchar Parameter/variable is nvarchar

25. 1b. Type Mismatch – Row Estimate SELECT * FROM CUSTOMER WHERE C_NAME LIKE 'Customer#00000276%' SELECT * FROM CUSTOMER WHERE C_NAME LIKE N’Customer#00000276%' Row estimate error could have severe consequences in a complex query

26. SELECT TOP + Row Estimate Error SELECT TOP 1000 [Document].[ArtifactID] FROM [Document] (NOLOCK) WHERE [Document].[AccessControlListID_D] IN (1,1000064,1000269) AND EXISTS ( SELECT [DocumentBatch].[BatchArtifactID] FROM [DocumentBatch] (NOLOCK) INNER JOIN [Batch] (NOLOCK) ON [Batch].ArtifactID = [DocumentBatch].[BatchArtifactID] WHERE [DocumentBatch].[DocumentArtifactID] = [Document].[ArtifactID] AND [Batch].[Name] LIKE N'%Value%' ) ORDER BY [Document].[ArtifactID] Data type mismatch – results in estimate rows high Top clause – easy to find first 1000 rows In fact, there are few rows that match SARG Wrong plan for evaluating large number of rows http://www.qdpma.com/CBO/Relativity.html

27. MULTIPLE OPTIONAL SARG

28. 2. Multiple Optional SARG DECLARE @Orderkey int, @Partkey int = 1 SELECT * FROM LINEITEM WHERE (@Orderkey IS NULL OR L_ORDERKEY = @Orderkey) AND (@Partkey IS NULL OR L_PARTKEY = @Partkey) AND (@Partkey IS NOT NULL OR @Orderkey IS NOT NULL)

29. IF block DECLARE @Orderkey int, @Partkey int = 1 IF (@Orderkey IS NOT NULL) SELECT * FROM LINEITEM WHERE (L_ORDERKEY = @Orderkey) AND (@Partkey IS NULL OR L_PARTKEY = @Partkey) ELSE IF (@Partkey IS NOT NULL) SELECT * FROM LINEITEM WHERE (L_PARTKEY = @Partkey) Need to consider impact of Parameter Sniffing, Consider the OPTIMIZER FOR hint These are actually the stored procedure parameters

30. Dynamically Built Parameterized SQL DECLARE @Orderkey int, @Partkey int = 1, @SQL nvarchar(500), @Param nvarchar(100) SELECT @SQL = N‘/* Comment */ SELECT * FROM LINEITEM WHERE 1=1‘, @Param = N'@Orderkey int, @Partkey int' IF (@Orderkey IS NOT NULL) SELECT @SQL = @SQL + N' AND L_ORDERKEY = @Orderkey' IF (@Partkey IS NOT NULL) SELECT @SQL = @SQL + N' AND L_PARTKEY = @Partkey' PRINT @SQL exec sp_executesql @SQL, @Param, @Orderkey, @Partkey IF block is easier for few options Dynamically built parameterized SQL better for many options Consider /*comment*/ to help identify source of SQL

31. 2b. Function on column SARG SELECT COUNT(*), SUM(L_EXTENDEDPRICE) FROM LINEITEM WHERE YEAR(L_SHIPDATE) = 1995 AND MONTH(L_SHIPDATE) = 1 SELECT COUNT(*), SUM(L_EXTENDEDPRICE) FROM LINEITEM WHERE L_SHIPDATE BETWEEN '1995-01-01' AND '1995-01-31' DECLARE @Startdate date, @Days int = 1 SELECT COUNT(*), SUM(L_EXTENDEDPRICE) FROM LINEITEM WHERE L_SHIPDATE BETWEEN @Startdate AND DATEADD(dd,1,@Startdate)

32. Estimated versus Actual Plan - rows Estimated Plan – 1 row??? Actual Plan – actual rows 77,356

33. 3 Parameter Sniffing -- first call, procedure compiles with these parameters exec p_Report @startdate = '2011-01-01', @enddate = '2011-12-31' -- subsequent calls, procedure executes with original plan exec p_Report @startdate = '2012-01-01', @enddate = '2012-01-07' Need different execution plans for narrow and wide range Options: 1) OPTIMIZE FOR – one plan for all ranges 2) WITH RECOMPILE – compile on each execute 3) main procedure calls 1 of 2 identical sub-procedures One sub-procedure is only called for narrow range Other called for wide range Skewed data distributions also important Example: Large & small customers Assuming date data type

34. STATISTICS

35. 4 Statistics Auto-recompute points Sampling strategy – How much to sample - theory? – Random pages versus random rows – Histogram Equal and Range Rows – Out of bounds, value does not exist – etc. Statistics Used by the Query Optimizer in SQL Server 2008 Eric N. Hanson and Yavor Angelov, Contributor: Lubor Kollar Optimizing Your Query Plans with the SQL Server 2014 Cardinality Estimator Joseph Sack http://msdn.microsoft.com/en-us/library/dd535534.aspx

36. Statistics Structure Stored (mostly) in binary field Scalar values Density Vector – limit 30, half in NC, half Cluster key Histogram Up to 200 steps Consider not blindly using IDENTITY on critical tables Example: Large customers get low ID values Small customers get high ID values http://sqlblog.com/blogs/joe_chang/archive/2012/05/05/decoding-stats-stream.aspx

37. Statistics Auto/Re-Compute Automatically generated on query compile Recompute at 6 rows, 500, every 20%? Has this changed? 2008 R2 Trace 2371 – lower threshold auto recomputed for large tables http://support.microsoft.com/kb/2754171

38. Statistics Sampling Sampling theory – True random sample – Sample error - square root N Relative error 1/ N SQL Server sampling – Random pages But always first and last page??? – All rows in selected pages

39. Row Estimate Problems (at source) Skewed data distribution Out of bounds Value does not exist Row estimate errors at source – is classified under statistics topic

40. Loop Join - Table Scan on Inner Source Estimated out from first 2 tabes (at right) is zero or 1 rows. Most efficient join to third table (without index on join column) is a loop join with scan. If row count is 2 or more, then a fullscan is performed for each row from outer source Default statistics rules may lead to serious ETL issues Consider custom strategy

41. Compile Parameter Not Exists Main procedure has cursor around view_Servers First server in view_Servers is ’CAESIUM’ Cursor executes sub-procedure for each Server sql: SELECT MAX(ID) FROM TReplWS WHERE Hostname = @ServerName But CAESIUM does not exist in TReplWS!

42. Good and Bad Plan?

43. SqlPlan Compile Parameters

44. <StmtSimple StatementText="@ServerName varchar(50) SELECT @maxid = ISNULL(MAX(id),0) FROM TReplWS WHERE Hostname = @ServerName" StatementId="1" StatementCompId="43" StatementType="SELECT" StatementSubTreeCost="0.0032843" StatementEstRows="1" StatementOptmLevel="FULL" QueryHash="0x671D2B3E17E538F1" QueryPlanHash="0xEB64FB22C47E1CF2" StatementOptmEarlyAbortReason="GoodEnoughPlanFound"> <StatementSetOptions QUOTED_IDENTIFIER="true" ARITHABORT="false" CONCAT_NULL_YIELDS_NULL="true" ANSI_NULLS="true" ANSI_PADDING="true" ANSI_WARNINGS="true" NUMERIC_ROUNDABORT="false" /> <RelOp NodeId="0" PhysicalOp="Compute Scalar" LogicalOp="Compute Scalar" EstimateRows="1" EstimateIO="0" EstimateCPU="1e-007“ AvgRowSize="15" EstimatedTotalSubtreeCost="0.0032843" Parallel="0" EstimateRebinds="0" EstimateRewinds="0"> Compile parameter values at bottom of sqlplan file

45. AND – OR, IN / NOT IN, EXISTS / NOT EXISTS COMBINATIONS

46. 5a Single Table OR -- Single table SELECT * FROM LINEITEM WHERE L_ORDERKEY = 1 OR L_PARTKEY = 184826

47. 5a Join 2 Tables, OR in SARG -- subsequent calls, procedure executes with original plan SELECT O_ORDERDATE, O_ORDERKEY, L_SHIPDATE, L_QUANTITY FROM LINEITEM INNER JOIN ORDERS ON O_ORDERKEY = L_ORDERKEY WHERE L_PARTKEY = 184826 OR O_CUSTKEY = 137099

48. 5a UNION (ALL) instead of OR SELECT O_ORDERDATE, O_ORDERKEY, L_SHIPDATE, L_QUANTITY, O_CUSTKEY, L_PARTKEY FROM LINEITEM INNER JOIN ORDERS ON O_ORDERKEY = L_ORDERKEY WHERE L_PARTKEY = 184826 UNION (ALL) SELECT O_ORDERDATE, O_ORDERKEY, L_SHIPDATE, L_QUANTITY, O_CUSTKEY, L_PARTKEY FROM LINEITEM INNER JOIN ORDERS ON O_ORDERKEY = L_ORDERKEY WHERE O_CUSTKEY = 137099 -- AND (L_PARTKEY <> 184826 OR L_PARTKEY IS NULL) -- Caution: select list should have keys to ensure correct rows UNION removes duplicates (with Sort operation) UNION ALL does not -- Hugo Kornelis trick --

49. 5b AND/OR Combinations Hash Join is good method to process many rows – Requirement is equality join condition – AND/OR, IN NOT IN, EXISTS NOT EXISTS combinations – Query optimizer may not be to determine that equality join condition exists – Execution plan will use loop join, – and attempt to force hash join will be rejected Re-write using UNION in place of OR And LEFT JOIN in place of NOT IN SELECT xx FROM A WHERE col1 IN (expr1) AND col2 NOT IN (expr2) SELECT xx FROM A WHERE (expr1) AND (expr2 OR expr3) More on AND/OR combinations: http://www.qdpma.com/CBO/Relativity3.htmlhttp://www.qdpma.com/CBO/Relativity3.html

50. COMPLEX QUERIES

51. Complex Queries High Compile effort – Many joins, Many indexes – Estimated plan cost correlation Row estimation errors after multiple operations Row estimate errors at source – is classified under statistics topic

52. Complex Query with Sub-expression Query complexity – really high compile cost Repeating sub-expressions (including CTE) – Must be evaluated multiple times Main Problem - Row estimate error propagation Solution/Strategy – Get a good execution plan – Temp table when estimate is high, actual is low. More on AND/OR combinations: http://www.qdpma.com/CBO/Relativity4.htmlhttp://www.qdpma.com/CBO/Relativity4.html http://blogs.msdn.com/b/sqlcat/archive/2013/09/09/when-to-break-down-complex-queries.aspx When Estimate is low, and actual rows is high, need to balance temp table insert overhead versus plan benefit. Would a join hint work?

53. More Plan Details Query with joining 6 tables Each table has too many indexes Row estimate is high – plan cost is high Query optimizer tries really really hard to find better plan Actual rows is moderate, any plan works

54. Temp Table and Table Variable Forget what other people have said – Most is cr@p Temp Tables – subject to statistics auto/re-compile Table variable – no statistics, assumes 1 row Question: In each specific case: does the statistics and recompile help or not? – Yes: temp table – No: table variable Is this still true?

55. Row Estimate Error after Join IO – synchronous when estimate rows is 25

56. Row Estimate 2

57. Parallelism Designed for 1998 era – Cost Threshold for Parallelism: default 5 – Max Degree of Parallelism – instance level – OPTION (MAXDOP n) – query level Today – complex system – 32 cores – Plan cost 5 query might run in 10ms? – Some queries at DOP 4 – Others at DOP 16? More on Parallelism: http://www.qdpma.com/CBO/ParallelismComments.html http://www.qdpma.com/CBO/ParallelismOnset.html Really need to rethink parallelism / NUMA strategies Number of concurrently running queries x DOP less than number of logical/physical processors? Tables with computed columns may inhibit parallelism?

58. Parallel Execution – or not? Tables with computed columns using UDF prevent parallelism

59. Full-Text Search Loop Join with FT as inner Source Full Text search Potentially executed many times

60. varchar(max) stored in lob pages Disk IO to lob pages is synchronous? – Must access row to get 16 byte link? – Feature request: index pointer to lob SQL PASS 2013 Understanding Data Files at the Byte Level Mark Rasmussen

61. legacy API Server Cursors / Cursor Stored Procedures – sp_prepare / sp_prepexec, sp_execute, sp_unprepare – sp_cursoropen, sp_cursorfetch, sp_cursorclose – sp_cursorprepare / sp_cursorprepexec, sp_cursorexecute, sp_cursorunprepare Guess which is not called? – Symptom: sp_reset_connection http://technet.microsoft.com/en-us/library/ms187088(v=sql.105).aspxhttp://technet.microsoft.com/en-us/library/ms187088(v=sql.105).aspx API Server Cursors http://technet.microsoft.com/en-us/library/ms187801(v=sql.120).aspxhttp://technet.microsoft.com/en-us/library/ms187801(v=sql.120).aspx Cursor Stored Procedures

62. Summary Hardware today is really powerful – Storage may not be – SAN vendor disconnect Standard performance practice – Top resource consumers, index usage But also Look for serious blunders http://www.qdpma.com/CBO/SQLServerCostBasedOptimizer.html http://www.qdpma.com/CBO/Relativity.html http://blogs.msdn.com/b/sqlcat/archive/2013/09/09/when-to-break-down-complex-queries.aspx Kevin Boles – Common TSQL Mistakes

63. Thank you to our sponsors

66. Special Topics Data type mismatch Multiple Optional Search Arguments (SARG) – Function on SARG Parameter Sniffing versus Variables Statistics related (big topic) AND/OR Complex Query Parallel Execution

67. SQL Server Edition Strategies Enterprise Edition – per core licensing costs – Old system strategy 4 (or 2)-socket server, top processor, max memory – Today: How many cores are necessary 2 socket system, max memory (16GB DIMMs) Is standard edition adequate – Low cost, but many important features disabled BI edition – 16 cores – Limited to 64GB for SQL Server process

68. New Features in SQL Server 2005 – Index included columns – Filtered index – CLR 2008 – Partitioning – Compression 2012 – Column store (non-clustered) 2014 – Column store clustered – Hekaton

69. GENERAL PERFORMANCE General Performance

70. SQL Performance General Client-side architecture – Connection pooling – stored procedures versus SQL, parameterized Database Architecture – Cluster key, primary key, natural keys, foreign keys SQL – Indexing Indexes & Statistics Maintenance

71. Client-side Architecture Connection pooling: – Connection.Open, Execute, Connection.Close – Sp_reset_connection Stored procedures – parameterized SQL – Stored procedure name is short – Parameterized SQL may not be Larger than 1 Ethernet packet? 2?, 8?

72. Database Architecture Normalization Cluster key Primary Key & other unique / natural keys Foreign keys

73. Principles TestingData Server Network Storage

74. QPI CPU & Memory 2001 versus 2014x Xeon E7 v2 (Ivy Bridge, 3 QPI) 4 x 15 = 60 cores 3TB (96 x 32GB) 24 DIMMs per socket 40 PCI-E gen3 lanes + x4 g2 / socket 2001 – 4 sockets, 4 cores Pentium III Xeon, 900MHz 4-8GB memory? Xeon MP 2002-4 FSB P L2 PPP MCH Each core today is more than 10x over Pentium III (700MHz?) Mem___2013 __ 2014 16GB __ $191 __ $180 32GB __ $794 __ $650 PCH DMI x4 MC GFX QPI MI PCI-E MI C1 C2 C3 C0 C4 C8 C7 C6 C9 C5 LLC 11 12 13 10 14 QPI MI PCI-E MI C1 C2 C3 C0 C4 C8 C7 C6 C9 C5 LLC 11 12 13 10 14 QPI MI PCI-E MI C1 C2 C3 C0 C4 C8 C7 C6 C9 C5 LLC 11 12 13 10 14 QPI MI PCI-E MI C1 C2 C3 C0 C4 C8 C7 C6 C9 C5 LLC 11 12 13 10 14 DMI 2 PCI-E DMI 2 PCI-E

75. Work in progress QPI MI PCI-E MI C1 C2 C3 C0 C4 C8 C7 C6 C9 C5 LLC B C D C E MI PCI-E C1C6 C2C5 C3C4 LLC QPI MI C7C0 QPI MI PCI-E MI C1 C2 C3 C4 C8 C7 C6 C5 LLC DMI 2 PCI-E QPI MI PCI-E MI C1 C2 C3 C0 C4 C8 C7 C6 C9 C5 LLC 11 12 13 10 14 PCI-E MI PCI-E C1C6 C2C5 C3C4 LLC QPI MI C7C0