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Modern Performance - SQL Server

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Presentation on theme: "Modern Performance - SQL Server"— Presentation transcript:

1 Modern Performance - SQL Server
Joe Chang 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 ExecStats Download: Blog:

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

4 CPU & Memory 2001 versus 2012 QPI PCI-E MI C1 C6 C2 C5 C3 C4 LLC C7 C0 DMI 2 P P P P L2 FSB MCH 2001 – 4 sockets, 4 cores Pentium III Xeon, 900MHz 4-8GB memory? Xeon MP 2012 – 4 sockets, 8 cores each 4 x 8 = 32 cores total Westmere-EX 1TB (64x16GB) Sandy Bridge E5: 768GB (48 x 16GB), 15 cores in Xeon E7 v2 3TB (96 x 32GB) Each core today is more than 10x over PIII _____ 2013 __ 2014 16GB $191 __ $180 32GB $794 __ $650

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

6 Intel E5 & E7 v2 (Ivy-Bridge)
PCH DMI x4 MC GFX

7 Storage 2001 versus 2012/13 QPI 192 GB 192 GB MCH QPI PCI PCI PCI PCI PCIe x4 PCIe x8 PCIe x8 PCIe x8 PCIe x8 PCIe x8 RAID RAID RAID RAID 10GbE RAID IB HDD HDD SSD SSD SSD SSD HDD HDD HDD HDD 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 possible IO Bandwidth 10GB/s easy SAN vendors – questionable BW

8 SAN Main Volume Log volume SSD 10K 7.2K Hot Spares 8 Gbps FC or 10Gbps
Node 1 Node 2 Switch SP A SP B 8 Gbps FC or 10Gbps FCOE 768 GB x4 SAS 2GB/s 24 GB Main Volume Node 2 768 GB 1 Switch SP A SP B 8 Gb FC 24 GB x4 SAS GB/s SSD x8 Data 5 Data 6 Data 7 Data 1 Data 2 Data 3 Data 4 Data 8 Data 9 Data 13 Data 10 Data 14 Data 11 Data 15 Data 12 Data 16 SSD 1 SSD 2 SSD 3 SSD 4 Log 1 Log 2 Log 3 Log 4 SAN – pools comprised of multiple RAID groups Volumes created from pool, containing a slice from each RAID group

9 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

10 Factors to Consider SQL Tables Indexes Query Optimizer Storage Engine
Statistics Query Optimizer Compile Parameters Storage Engine DOP memory Hardware

11 Special Topics Data type mismatch
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

12 1a. Data type mismatch nvarchar(25) = N'Customer# ' SELECT * FROM CUSTOMER WHERE C_NAME Table column is varchar Parameter/variable is nvarchar SELECT * FROM CUSTOMER WHERE C_NAME = .NET auto-parameter discovery? Unable to use index seek

13 1b. Type Mismatch – Row Estimate
SELECT * FROM CUSTOMER WHERE C_NAME LIKE 'Customer# %' SELECT * FROM CUSTOMER WHERE C_NAME LIKE N’Customer# %' Row estimate error could have severe consequences in a complex query

14 SELECT TOP + 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

15 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)

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

17 Dynamically Built Parameterized SQL
int = 1 nvarchar(100) = N‘/* Comment */ SELECT * FROM LINEITEM WHERE 1=1‘ = 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 Consider /*comment*/ to help identify source of SQL

18 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

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

20 3 Parameter Sniffing -- first call, procedure compiles with these parameters exec = = ' ' -- subsequent calls, procedure executes with original plan exec = = ' ' Assuming date data type 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

21 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 Writer: Eric N. Hanson and Yavor Angelov Contributor: Lubor Kollar

22 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

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

24 Statistics Sampling Sampling theory SQL Server sampling
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

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

26 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

27

28 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!

29 Good and Bad Plan?

30 SqlPlan Compile Parameters

31 SqlPlan Compile Parameters
<?xml version="1.0" encoding="utf-8"?> <ShowPlanXML xmlns="http://schemas.microsoft.com/sqlserver/2004/07/showplan" Version="1.1" Build=" "> <BatchSequence> <Batch> <Statements> <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" /> <QueryPlan CachedPlanSize="16" CompileTime="1" CompileCPU="1" CompileMemory="168"> <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"> </RelOp> <ParameterList> <ColumnReference ParameterCompiledValue="'CAESIUM'" /> </ParameterList> </QueryPlan> </StmtSimple> </Statements> </Batch> </BatchSequence> </ShowPlanXML> Compile parameter values at bottom of sqlplan file

32 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

33 5a Single Table OR -- Single table SELECT * FROM LINEITEM
WHERE L_ORDERKEY = 1 OR L_PARTKEY =

34 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 =

35 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 = UNION (ALL) 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 (with Sort operation) UNION ALL does not -- Hugo Kornelis trick --

36 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:

37 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. When Estimate is low, and actual rows is high, need to balance temp table insert overhead versus plan benefit. Would a join hint work? More on AND/OR combinations:

38 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

39 Parallelism Designed for 1998 era Today – complex system – 32 cores
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? Number of concurrently running queries x DOP less than number of logical/physical processors? Really need to rethink parallelism / NUMA strategies More on Parallelism: Number of concurrently running queries x DOP less than number of logical/physical processors?

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

41 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

42 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

43 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

44 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

45 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


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