Modern Performance - SQL Server Joe Chang & SolidQ

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 ExecStats Download: Blog:

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

CPU & Memory 2001 and – 4 sockets, 4 cores Pentium III Xeon, 900MHz 4-8GB memory? Xeon MP – 4 sockets, 8 cores each 4 x 8 = 32 cores total 768GB (48 x 16GB), Westmere-EX 1TB 15 cores in next generation? FSB P L2 PP P MCH QPI DMI 2 PCI-E QPI PCI-E MI PCI-E C1C6 C2C5 C3C4 LLC QPI MI C7C0 MI PCI-E C1C6 C2C5 C3C4 LLC QPI MI C7C0 MI PCI-E C1C6 C2C5 C3C4 LLC QPI MI C7C0 MI PCI-E C1C6 C2C5 C3C4 LLC QPI MI C7C0 Each core today is more than 10x over PIII 16GB $191 32GB $794

Storage 2001 versus 2012/13 PCIe x8 PCIe x4 IBRAID 10GbE QPI 192 GB HDD SSD x 10K HDD 125 IOPS each = 12.5K IOPS IO Bandwidth limited: 1.3GB/s (1/3 memory bandwidth) SSDs, >10K+ IOPS each, 1M IOPS possible IO Bandwidth 10GB/s easy SAN vendors – questionable BW PCI MCH RAID HDD

SAN Node GB Node GB Switch SP ASP B 8 Gb FC 24 GB x4 SAS 2GB/s SSD x8 SSD x8 Data 5Data 6Data 7 Data 1Data 2Data 3Data 4 Data 8 Data 9 Data 13 Data 10 Data 14 Data 11 Data 15 Data 12 Data 16 SSD 1SSD 2SSD 3SSD 4 Log 1Log 2Log 3Log 4 Log volume SSD10K7.2K Hot Spares Node 1Node 2 Switch SP ASP B 8 Gbps FC or 10Gbps FCOE 768 GB x4 SAS 2GB/s 24 GB Main Volume

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, 60-cores later in 2013? – Enough memory that IO is only sporadic – Unlimited IOPS with SSD What can go wrong? Today’s topic

Factors to Consider SQLTablesIndexes Query Optimizer Statistics Compile Parameters Storage Engine Hardware

Special Topics Data type mistmatch Multiple Optional Search Arguments (SARG) – Function on SARG Parameter Sniffing versus Variables Statistics related (big topic) first OR, then AND/OR combinations Complex Query with sub-expressions Parallel Execution Not in order of priority

1a. Data type mismatch nvarchar(25) = N'Customer# ' SELECT * FROM CUSTOMER WHERE C_NAME SELECT * FROM CUSTOMER WHERE C_NAME = auto-parameter discovery? Unable to use index seek

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

SELECT TOP plus Row Estimate Error SELECT TOP 1000 [Document].[ArtifactID] FROM [Document] (NOLOCK) WHERE [Document].[AccessControlListID_D] IN (1, , ) 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

2. Multiple Optional SARG int = 1 SELECT * FROM LINEITEM WHERE IS NULL OR L_ORDERKEY AND IS NULL OR L_PARTKEY AND IS NOT NULL IS NOT NULL)

Dynamically Built Parameterized SQL int = nvarchar(100) = N‘/* Comment */ SELECT * FROM LINEITEM WHERE = int' IF IS NOT NULL) + N' AND L_ORDERKEY IF IS NOT NULL) + N' AND L_PARTKEY IF block is easier for few options Dynamically built parameterized SQL better for many options Considering /*comment*/ to help identify this

IF block int = 1 IF IS NOT NULL) SELECT * FROM LINEITEM WHERE (L_ORDERKEY AND IS NULL OR L_PARTKEY ELSE IF IS NOT NULL) SELECT * FROM LINEITEM WHERE (L_PARTKEY Need to consider impact of Parameter Sniffing, Consider the OPTIMIZER FOR hint This is actually the stored procedure parameters

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 ' ' AND ' ' int = 1 SELECT COUNT(*), SUM(L_EXTENDEDPRICE) FROM LINEITEM WHERE L_SHIPDATE AND

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

3 Parameter Sniffing -- first call, procedure compiles with these parameters exec = = ' ' -- subsequent calls, procedure executes with original plan exec = = ' ' Need different execution plans for narrow and wide range Options: 1) WITH RECOMPILE 2) 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

4 Statistics Auto-recompute points Sampling strategy – Percentage – 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 Writer: Eric N. Hanson and Yavor Angelov Contributor: Lubor Kollar

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

Statistics Auto/Re-Compute Automatically generated on query compile Recompute at 6 rows, 500, every 20%? Has this changed?

Statistics Sampling Sampling theory – True random sample – Sample error - square root N Relative error 1/ N SQL Server sampling – All rows in random pages

Row Estimate Problems Skewed data distribution Out of bounds Value does not exist

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

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 But CAESIUM does not exist in TReplWS!

Good and Bad Plan?

SqlPlan Compile Parameters

<StmtSimple varchar(50) = ISNULL(MAX(id),0) FROM TReplWS WHERE Hostname StatementId="1" StatementCompId="43" StatementType="SELECT" StatementSubTreeCost=" " 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=" " Parallel="0" EstimateRebinds="0" EstimateRewinds="0"> Compile parameter values at bottom of sqlplan file

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

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 = OR O_CUSTKEY =

5a UNION 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 = 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 = AND (L_PARTKEY <> OR L_PARTKEY IS NULL) -- Caution: select list should have keys to ensure correct rows UNION removes duplicates UNION ALL does not -- Hugo Kornelis trick --

5b AND/OR Combinations Hash Join is good method to process many rows – Requirement is equality join condition In complex SQL with AND/OR or IN NOT IN 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:

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: When Estimate is low, and actual rows is high, need to balance temp table insert overhead versus plan benefit. Would a join hint work?

Temp Table and Table Variable Forget what other people have said – Most is 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

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: Really need to rethink parallelism / NUMA strategies

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

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

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

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 with sub-expressions Parallel Execution