SQL Server Execution Plans for Mere Mortals

1. Execution Plans for Mere Mortals
A beginners overview of execution
plans and what to look for.

2. Who Am I?
Mike Lawell
Mike Lawell
Principal Consultant
Twitter: @SQLDiver
Blog: SQLServerAssociates.com
LinkedIn: LinkedIn.com/in/MikeLawell

3. EXECUTION STEPS

4. On The Inside
Relational Engine
Optimizer
Command
Parser
Query
Executor
SNI
User
Storage Engine
Buffer
Manager
Access
Methods
Transaction
Manager
SQL OS
Buffer Pool
Borrowed from Bradley Ball’s “SQL Internals, Recovery Models, & Backups” presentation
Plan Cache
Data
Cache
Data

5. Query Parsing
Relation Engine
1. Is the query syntactically correct?
SELECT [Nmae], [Number] FROM [Production].[Product]
Msg 207, Level 16, State 1, Line 3
Invalid column name 'Nmae'.
SELCT [Name], [Number] FROM [Production].[Product]
Msg 156, Level 15, State 1, Line 3
Incorrect syntax near the keyword 'FROM'.
2. No Errors Output as Parse Tree to Algebrizer

6. Query Parsing
SELECT [Nmae], [Number] FROM [Production].[Product]
Msg 207, Level 16, State 1, Line 3
Invalid column name 'Nmae'.

7. Query Parsing
SELECT [Name], [Number] FROM [Production].[Product]

8. Algebrizer
1. Resolve the Names of the objects (tables, columns, etc.)
2. Resolve the data types for the objects being accessed.
3. Finds aggregate operations (min, max, group by) and performs an operation
called aggregate binding.
If the names of the objects, columns aren’t found an error is output and the process
halts.
If it is successful the algebrizer outputs the query processor tree to the query
optimizer. The query hash is generated and passed with the query processor tree.

9. Query Optimizer
1. The query optimizer checks the hash against the plan cache. If it exists use it and
the optimization step is skipped and plan is passed to query execution.
2. The query optimizer uses the query processor tree and the statistics to determine
an estimated execution plan.
3. The optimizer goes through a process of using different types of joins and indexes
and assigns a cost to each step by CPU and I/O and determines a cost for each
possible estimated plan it generates.
4. Once an acceptable estimated plan is found it is stored in the plan cache then sent
to the query execution.

10. Query Execution
Storage Engine
1. The storage engine determines if a recompile was triggered causing a change in
the estimated execution plan.
2. SQL Server determines based upon cost whether it exceeds the threshold for
parallelism changing the estimated plan for parallelism.
3. Statistics that have changed causing a change in the estimated plan.
SQL Server returns the results.

11. Cardinality Estimation
The optimization process depends on a cost estimation of each physical operator and the
estimated number of records (cardinality estimation) to be processed.
DBCC SHOW_STATISTICS ("[Sales].[SalesOrderDetailEnlarged]", [_WA_Sys_00000003_3D7E1B63]);
The accuracy of the cardinality estimation depends upon the distribution of values in one or
more columns of a table (statistics).
Name Updated Rows Rows Sampled Steps Average key length String Index Filter Expression Unfiltered Rows
_WA_Sys_00000003_3D7E1B63 Nov 26 2014 11:26AM 1000 1000 196 24 YES NULL 1000
RANGE_HI_KEY RANGE_ROWS EQ_ROWS DISTINCT_RANGE_ROWS AVG_RANGE_ROWS
002EE045-E30 0 1 0 1
0169388E-8EC 6 1 6 1
031622B3-B68 3 1 3 1
0424F840-4C2 3 1 3 1
04C4FEAC-7C1 3 1 3 1

12. Swag Question
Name
_WA_Sys_00000003_3D7E1B63

13. Cardinality Estimation
There are multiple factors that can negatively impact the cardinality estimation process:
1. Out of date Statistics
SELECT object_name(object_id) as TableName, name AS stats_name,
STATS_DATE(object_id, stats_id) AS statistics_update_date
FROM sys.stats
WHERE object_id = OBJECT_ID('[Sales].[SalesOrderDetailEnlarged]');
2. Cardinality Estimation Errors
https://www.sqlskills.com/blogs/joe/cardinality-estimation-model-version/

14. Swag Question
Why 70 vs 120?

15. EXECUTION PLAN BASICS

16. Required Permissions
Server or database roles with permissions:
sysadmin, dbcreator or db_owner or showplan
To give showplan rights to the database:
GRANT SHOWPLAN TO [username];

17. How to Read

18. BASIC OPERATORS

19. Basic Operators

20. JOIN OPERATORS

21. Nested LoopNon-blocking
Description
For each row in the top (outer) input, scan the
bottom (inner) input, and output matching rows.
Where does it happen: Joins with
indexes on join columns.

22. Nested Loop
SELECT [sod].[CarrierTrackingNumber], [sod].[OrderQty], [soh].[RevisionNumber], [soh].[Ord
FROM [Sales].[SalesOrderHeader] soh
JOIN [Sales].[SalesOrderDetail] sod
ON sod.[SalesOrderID] = soh.[SalesOrderID]
WHERE soh.[OrderDate] = '2013-08-30 00:00:00.000'
Non-blocking
Outer
Inner

23. Nested Loop
SalesOrderID RevisionNumber OrderDate
55233 8 2013-08-30 00:00:00.000
55234 8 2013-08-30 00:00:00.000
55235 8 2013-08-30 00:00:00.000
55236 8 2013-08-30 00:00:00.000
55237 8 2013-08-30 00:00:00.000
55238 8 2013-08-30 00:00:00.000
55239 8 2013-08-30 00:00:00.000
55240 8 2013-08-30 00:00:00.000
55241 8 2013-08-30 00:00:00.000
55242 8 2013-08-30 00:00:00.000
55243 8 2013-08-30 00:00:00.000
55244 8 2013-08-30 00:00:00.000
55245 8 2013-08-30 00:00:00.000
55246 8 2013-08-30 00:00:00.000
55247 8 2013-08-30 00:00:00.000
55248 8 2013-08-30 00:00:00.000
55249 8 2013-08-30 00:00:00.000
55250 8 2013-08-30 00:00:00.000
55251 8 2013-08-30 00:00:00.000
55252 8 2013-08-30 00:00:00.000
55253 8 2013-08-30 00:00:00.000
SalesOrderID ProductID CarrierTrackingNumber OrderQt
55233 738 1590-499E-95 5
55233 792 1590-499E-95 5
55233 793 1590-499E-95 4
55233 794 1590-499E-95 4
55233 795 1590-499E-95 4
55233 796 1590-499E-95 5
55233 797 1590-499E-95 6
55233 798 1590-499E-95 2
55233 799 1590-499E-95 1
55233 800 1590-499E-95 1
55233 801 1590-499E-95 6
55233 835 1590-499E-95 6
55233 874 1590-499E-95 8
55233 875 1590-499E-95 8
55233 938 1590-499E-95 5
55233 939 1590-499E-95 5
55233 940 1590-499E-95 4
55233 973 1590-499E-95 5
55233 974 1590-499E-95 1
55233 975 1590-499E-95 1
Non-blocking

24. Description
Match rows from two suitably sorted input tables
exploiting their sort order.
Where does it happen: Joins with
indexes on join columns sorted in an
appropriate sort order.
MergeNon-blocking

25. MergeNon-blocking
SELECT [sod].[CarrierTrackingNumber], [sod].[OrderQty], [soh].[RevisionNumber], [soh].[OrderDate]
FROM [Sales].[SalesOrderHeader] soh
JOIN [Sales].[SalesOrderDetail] sod
ON sod.[SalesOrderID] = soh.[SalesOrderID]

26. MergeNon-blocking
SalesOrderID RevisionNumber OrderDate
55233 8 2013-08-30 00:00:00.000
55234 8 2013-08-30 00:00:00.000
55235 8 2013-08-30 00:00:00.000
55236 8 2013-08-30 00:00:00.000
55237 8 2013-08-30 00:00:00.000
55238 8 2013-08-30 00:00:00.000
55239 8 2013-08-30 00:00:00.000
55240 8 2013-08-30 00:00:00.000
55241 8 2013-08-30 00:00:00.000
55242 8 2013-08-30 00:00:00.000
55243 8 2013-08-30 00:00:00.000
55244 8 2013-08-30 00:00:00.000
55245 8 2013-08-30 00:00:00.000
55246 8 2013-08-30 00:00:00.000
55247 8 2013-08-30 00:00:00.000
55248 8 2013-08-30 00:00:00.000
55249 8 2013-08-30 00:00:00.000
55250 8 2013-08-30 00:00:00.000
55251 8 2013-08-30 00:00:00.000
55252 8 2013-08-30 00:00:00.000
55253 8 2013-08-30 00:00:00.000
SalesOrderID ProductID CarrierTrackingNumber OrderQt
55233 738 1590-499E-95 5
55233 792 1590-499E-95 5
55233 793 1590-499E-95 4
55233 794 1590-499E-95 4
55233 795 1590-499E-95 4
55233 796 1590-499E-95 5
55233 797 1590-499E-95 6
55233 798 1590-499E-95 2
55233 799 1590-499E-95 1
55233 800 1590-499E-95 1
55233 801 1590-499E-95 6
55233 835 1590-499E-95 6
55233 874 1590-499E-95 8
55233 875 1590-499E-95 8
55233 938 1590-499E-95 5
55233 939 1590-499E-95 5
55233 940 1590-499E-95 4
55233 973 1590-499E-95 5
55233 974 1590-499E-95 1
55233 975 1590-499E-95 1

27. Hash Match
Description
Use each row from the top input to build a hash
table, and each row from the bottom input to probe
into the hash table, outputting all matching rows.
Where does it happen: Missing Index,
Missing Where Clause, Where Clause
that is non-sargable.

28. Hash MatchBlocking
SELECT [sod1].[ProductID], [sod1].[CarrierTrackingNumber], [sod1].[UnitPrice], [sod1].[OrderQty]
FROM [Sales].[SalesOrderDetail] sod1
JOIN [Sales].[SalesOrderDetail] sod2
ON [sod1].[ProductID] = [sod2].[ProductID]
AND [sod1].[CarrierTrackingNumber] = [sod2].[CarrierTrackingNumber]
AND [sod1].[OrderQty] > 5

29. Hash MatchBlocking
ProductID CarrierTrackingNumber Hash
707 4BC2-4C6D-83 -767544381
711 2AA4-4D12-9F -767515863
715 C811-4D40-80 -767499885
715 8FCD-4D55-8F -767496256
714 CC2F-4D47-8C -767488607
712 BE3B-4D30-A7 -767488106
707 9EBF-4C7E-82 -767471833
716 F78B-4D68-8E -767470049
712 8EBE-4D2C-AB -767459569
716 7DE5-4D74-A7 -767455808
715 46EF-4D44-A9 -767449380
711 9FC2-4D08-A7 -767447057
ProductID CarrierTrackingNumbe
736 2554-4F68-AB -767556491
717 9526-4D73-83 -767556433
715 CC2F-4D47-8C -767554143
715 2960-4D59-96 -767553412
722 9708-4E22-A4 -767551834
722 6F5C-4E3C-B5 -767549829
717 7E0A-4D6E-9E -767545458
707 4BC2-4C6D-83 -767544381
716 F108-4D76-8A -767543168
711 B900-4D0D-AF -767541067
711 67A0-4D10-87 -767539667
707 8441-4C6F-89 -767535798
Hash Table 1 Hash Table 2

30. Fixed Hash Match

31. OTHER OPERATORS

32. Parallelism
SELECT [sod1].[ProductID], [sod1].[CarrierTrackingNumber], [sod1].[UnitPrice], [sod1].[OrderQty]
FROM [Sales].[SalesOrderDetail] sod1
JOIN [Sales].[SalesOrderDetail] sod2
ON [sod1].[ProductID] = [sod2].[ProductID]
AND [sod1].[CarrierTrackingNumber] = [sod2].[CarrierTrackingNumber]

33. Parallelism
SET STATISTICS IO ON
SET STATISTICS TIME ON
SELECT [sod1].[ProductID], [sod1].[CarrierTrackingNumber], [sod1].[UnitPrice], [sod1].[OrderQty]
FROM [Sales].[SalesOrderDetail] sod1
JOIN [Sales].[SalesOrderDetail] sod2
ON [sod1].[ProductID] = [sod2].[ProductID]
AND [sod1].[CarrierTrackingNumber] = [sod2].[CarrierTrackingNumber]
SELECT [sod1].[ProductID], [sod1].[CarrierTrackingNumber], [sod1].[UnitPrice], [sod1].[OrderQty]
FROM [Sales].[SalesOrderDetail] sod1
JOIN [Sales].[SalesOrderDetail] sod2
ON [sod1].[ProductID] = [sod2].[ProductID]
AND [sod1].[CarrierTrackingNumber] = [sod2].[CarrierTrackingNumber]
OPTION(MAXDOP 1)

34. Parallelism
Table 'SalesOrderDetail'. Scan count 18, logical reads 2490, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob
read-ahead reads 0.
Table 'Workfile'. Scan count 0, logical reads 0, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads
0.
Table 'Worktable'. Scan count 0, logical reads 0, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead
reads 0.
SQL Server Execution Times:
CPU time = 9593 ms, elapsed time = 2381 ms.
Table 'Workfile'. Scan count 0, logical reads 0, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads
0.
Table 'Worktable'. Scan count 0, logical reads 0, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead
reads 0.
Table 'SalesOrderDetail'. Scan count 2, logical reads 2490, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-
ahead reads 0.
SQL Server Execution Times:
CPU time = 7941 ms, elapsed time = 8372 ms.

35. Parallelism

36. Hash Aggregate
SELECT [sod1].[CarrierTrackingNumber], sum([sod1].[UnitPrice]) UnitPriceTotal,
sum([sod1].[OrderQty]) as OrderQtyTotal
FROM [Sales].[SalesOrderDetail] sod1
JOIN [Sales].[SalesOrderDetail] sod2
ON [sod1].[ProductID] = [sod2].[ProductID]
AND [sod1].[CarrierTrackingNumber] = [sod2].[CarrierTrackingNumber]
AND [sod1].[OrderQty] > 5
GROUP BY [sod1].[CarrierTrackingNumber]

37. Stream Aggregate
SELECT [sod1].[CarrierTrackingNumber], sum([sod1].[UnitPrice]) UnitPriceTotal,
sum([sod1].[OrderQty]) as OrderQtyTotal
FROM [Sales].[SalesOrderDetail] sod1
JOIN [Sales].[SalesOrderDetail] sod2
ON [sod1].[ProductID] = [sod2].[ProductID]
AND [sod1].[CarrierTrackingNumber] = [sod2].[CarrierTrackingNumber]
AND [sod1].[OrderQty] > 5
GROUP BY [sod1].[CarrierTrackingNumber]

38. Sort (spill)
Operator used tempdb to spill data during execution with spill level 1
SELECT [sod].[CarrierTrackingNumber], [sod].[OrderQty], [soh].[RevisionNumber], [soh].[OrderDate]
FROM [Sales].[SalesOrderHeader] soh
JOIN [Sales].[SalesOrderDetailEnlarged] sod
ON sod.[SalesOrderID] = soh.[SalesOrderID]
WHERE [sod].[CarrierTrackingNumber] > '41D0-42A8-A5'
ORDER BY [soh].[RevisionNumber], [soh].[OrderDate]

39. Sort Spill
SELECT TOP 1 [sod].[CarrierTrackingNumber], [sod].[OrderQty], [soh].[RevisionNumber], [soh].[OrderDate]
FROM [Sales].[SalesOrderHeader] soh
JOIN [Sales].[SalesOrderDetailEnlarged] sod
ON sod.[SalesOrderID] = soh.[SalesOrderID]
WHERE [sod].[CarrierTrackingNumber] > '41D0-42A8-A5'
ORDER BY [soh].[RevisionNumber], [soh].[OrderDate]

40. Implicit Conversion
SELECT [sod].[ProductID], [sod].[CarrierTrackingNumber], [sod].[UnitPrice], [sod].[OrderQty], [rowguid]
FROM [Sales].[SalesOrderDetail] sod
WHERE LEFT([sod].[rowguid],4) = N'FE10'

41. Properties

42. Cool Tools/Products
SQL Server Query Plan Analysis by Joe Sack

43. Resources
http://www.red-gate.com/community/books/
Downloadable
FREE!

44. Thank You!
Mike Lawell
Principal Consultant
Twitter: @SQLDiver
Blog: SQLServerAssociates.com
LinkedIn: LinkedIn.com/in/MikeLawell
Email: mike@sqlserverassociates.com

45. Who Am I?
Mike Lawell
Mike Lawell
Principal Consultant
Twitter: @SQLDiver
Blog: SQLServerAssociates.com
LinkedIn: LinkedIn.com/in/MikeLawell