1. Modern Performance - SQL Server
Joe Chang
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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

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=" 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