Modern Performance - SQL Server
Joe Chang
www.qdpma.com
Jchang6 @ yahoo
About Joe
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•
•
•
•
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 http://www.qdpma.com/ExecStats/SQLExecStats.html
Download: http://www.qdpma.com/ExecStatsZip.html
Blog: http://sqlblog.com/blogs/joe_chang/default.aspx
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 versus 2012
PCI-E
PCI-E
PCI-E
PCI-E
PCI-E
PCI-E
PCI-E
PCI-E
PCI-E
P
QPI
C3
C2
C1
C0
MCH
2001 – 4 sockets, 4 cores
Pentium III Xeon, 900MHz
4-8GB memory?
LLC
MI
MI
QPI
PCI-E
C3
C2
C1
C0
LLC
MI
C3
C2
C1
C0
PCI-E
LLC
MI
C4
C5
C6
C7
C4
C5
C6
C7
MI
QPI
QPI
C3
C2
C1
C0
PCI-E
LLC
MI
C4
C5
C6
C7
MI
PCI-E
PCI-E
PCI-E
PCI-E
PCI-E
PCI-E
DMI 2
PCI-E
PCI-E
_____ 2013 __ 2014
16GB $191 __ $180
32GB $794 __ $650
QPI
MI
PCI-E
Each core today is more
than 10x over PIII
PCI-E
PCI-E
Xeon MP 2002-4
C4
C5
C6
C7
QPI
QPI
FSB
PCI-E
QPI
P
PCI-E
P
PCI-E
PCI-E
P
L2
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)
CPU & Memory 2001 versus 2014
C5
C6
C7
C8
C9
PCI-E
C5
C6
C7
C8
C9
MI
C5
C6
C7
C8
C9
PCI-E
C5
C6
C7
C8
C9
MI
QPI
QPI
PCI-E
C5
C6
C7
C8
C9
MI
QPI
QPI
C4
C3
C2 LLC
C1
C0
MI
PCI-E
PCI-E
PCI-E
PCI-E
PCI-E
PCI-E
PCI-E
DMI 2
PCI-E
Mem___2013 __ 2014
16GB __ $191 __ $180
32GB __ $794 __ $650
PCI-E
Each core today is more
than 10x over Pentium III
(700MHz?)
PCI-E
PCI-E
Xeon MP 2002-4
PCI-E
2001 – 4 sockets, 4 cores
Pentium III Xeon, 900MHz
4-8GB memory?
PCI-E
QPI
C4
C3
C2 LLC
C1
C0
MI
PCI-E
QPI
PCI-E
C5
C6
C7
C8
C9
PCI-E
C5
C6
C7
C8
C9
MI
PCI-E
QPI
C4
C3
C2 LLC
C1
C0
MI
PCI-E
MCH
C5
C6
C7
C8
C9
PCI-E
FSB
QPI
C4
C3
C2 LLC
C1
C0
MI
PCI-E
P
PCI-E
P
PCI-E
P
PCI-E
PCI-E
P
L2
Xeon E7 v2 (Ivy Bridge)
4 x 15 = 60 cores
3TB (96 x 32GB)
24 DIMMs per socket (12 shown)
Intel E5 & E7 v2 (Ivy-Bridge)
E3 v3
GFX
MC
DMI
x4
x4
x4
x4
PCH
Storage 2001 versus 2012/13
QPI
192 GB
MCH
HDD
HDD
HDD
10GbE
RAID
RAID
RAID
RAID
SSD
SSD
SSD
SSD
HDD
HDD
HDD
HDD
PCIe x8
HDD
HDD
PCIe x8
HDD
PCIe x8
PCI
RAID
PCIe x8
PCI
RAID
PCIe x8
PCI
RAID
PCIe x4
PCI
RAID
192 GB
QPI
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
http://www.qdpma.com/Storage/Storage2013.html
http://www.qdpma.com/ppt/Storage_2013.pptx
IB
SAN
Node 1
Node 2
768 GB
768 GB
SSD
SSD
8 Gb
FC
Switch
x4 SAS
2GB/s
Switch
SP A
SP B
24 GB
24 GB
x4 SAS
Main Volume
Log volume
SSD
10K 7.2K
Hot Spares
x8
24 GB
x8
24 GB
Node
2
768 GB
x8
SP B
x8
SP A
768 GB
x8
8 Gbps
FC
or
Switch
10Gbps
FCOE
x8
Switch
Node
1
2GB/s
Data 1
Data 2
Data 3
Data 4
Data 5
Data 6
Data 7
Data 8
Data 9
Data 10
Data 11
Data 12
Data 13
Data 14
Data 15
Data 16
SSD 1
SSD 2
SSD 3
SSD 4
Log 1
Log 2
Log 3
Log 4
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
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
Factors to Consider
SQL
Tables
Indexes
Statistics
Query
Optimizer
Storage
Engine
Hardware
Compile
Parameters
DOP
memory
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
http://blogs.msdn.com/b/sqlcat/archive/2013/09/09/when-to-break-down-complex-queries.aspx
1a. Data type mismatch
DECLARE @name nvarchar(25) = N'Customer#000002760'
SELECT * FROM CUSTOMER WHERE C_NAME = @name
Table column is varchar
Parameter/variable is nvarchar
SELECT * FROM CUSTOMER WHERE C_NAME = CONVERT(varchar, @name)
.NET auto-parameter discovery?
Unable to use index seek
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
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
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)
IF block
DECLARE @Orderkey int, @Partkey int = 1
These are actually the
stored procedure
parameters
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
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
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)
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 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'
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
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
http://msdn.microsoft.com/en-us/library/dd535534.aspx
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
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
– Random pages
• But always first and last page???
– All rows in selected 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 = @ServerName
But CAESIUM does not exist in TReplWS!
Good and Bad Plan?
SqlPlan Compile Parameters
SqlPlan Compile Parameters
<?xml version="1.0" encoding="utf-8"?>
<ShowPlanXML xmlns="http://schemas.microsoft.com/sqlserver/2004/07/showplan" Version="1.1" Build="10.50.2500.0">
<BatchSequence>
<Batch>
<Statements>
<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" />
<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="0.0032843" Parallel="0" EstimateRebinds="0" EstimateRewinds="0">
</RelOp>
<ParameterList>
<ColumnReference Column="@ServerName" ParameterCompiledValue="'CAESIUM'" />
</ParameterList>
</QueryPlan>
</StmtSimple>
</Statements>
</Batch>
</BatchSequence>
</ShowPlanXML>
Compile parameter values at bottom of sqlplan file
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
5a Single Table OR
-- Single table
SELECT * FROM LINEITEM
WHERE L_ORDERKEY = 1
OR L_PARTKEY = 184826
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
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 --
5b AND/OR Combinations
• Hash Join is good method to process many rows
– Requirement is equality join condition
SELECT xx FROM A WHERE col1 IN (expr1) AND col2 NOT IN (expr2)
SELECT xx FROM A WHERE (expr1) AND (expr2 OR expr3)
• 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
More on AND/OR combinations:
http://www.qdpma.com/CBO/Relativity3.html
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: http://www.qdpma.com/CBO/Relativity4.html
http://blogs.msdn.com/b/sqlcat/archive/2013/09/09/when-to-break-down-complex-queries.aspx
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
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 Really need to rethink
parallelism / NUMA strategies
– Others at DOP 16?
More on Parallelism:
http://www.qdpma.com/CBO/ParallelismComments.html
http://www.qdpma.com/CBO/ParallelismOnset.html
Number of concurrently running queries x DOP less
than number of logical/physical processors?
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
SQL PASS 2013
Understanding Data Files at the Byte Level
Mark Rasmussen
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
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
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
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