SQL Server: How Local Variables Can Reduce Query Performance


It’s a common practice by database developers to use local variables in stored procedures and scripts to place filter on basis of these local variables. YES, these local variables can slowdown your queries. Let’s prove it.
Create a new table and insert dummy rows.

USEAdventureWorks

GO
CREATE TABLE TempTable
      (tempID UNIQUEIDENTIFIER,tempMonth INT,tempDateTime DATETIME )
GO

INSERT INTO TempTable (tempID, tempMonth, tempDateTime)

SELECT NEWID(),(CAST(100000*RAND() AS INT) % 12) + 1 ,GETDATE()
GO 100000 — (EXECUTE THIS BATCH 100000 TIME)

— Create an index to support our query

CREATE NONCLUSTERED INDEX[IX_tempDateTime] ON [dbo].[TempTable]
([tempDateTime] ASC)
INCLUDE ( [tempID]) WITH ( ALLOW_ROW_LOCKS  = ON, ALLOW_PAGE_LOCKS  = ON) ON [PRIMARY]
GO
Now let’s execute a simple query with hard coded values in WHERE clause

SET STATISTICS IO ON

GO
SELECT * FROM TempTable
WHEREtempDateTime > ‘2012-07-10 03:18:01.640’
——————————————————————————————-
Table ‘TempTable’. Scan count 1, logical reads 80,physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0.

Check out its execution plan and index seeks properties. You can find that estimated rows are double to actual rows but that’s not a big difference to affect execution plan and resultantly optimizer has selected a proper plan to execute this query.

Query optimizer has estimated number of rows from its base statistics histogram i.e.  EQ_ROWS + AVG_RANGE_ROWS (77 + 88.64286)

DBCC SHOW_STATISTICS (‘dbo.TempTable’, IX_tempDateTime)

Now, let’s modify our SELECT query and use local variable and execute it. You will find that query optimizer has selected a different plan this time, a more costly plan. WHY ??

DECLARE@RequiredDate DATETIME
SET@RequiredDate = ‘2012-07-10 03:18:01.640’

SELECT * FROM TempTable
WHEREtempDateTime  >@RequiredDate
——————————————————————————————
Table ‘TempTable’. Scan count 1, logical reads 481, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0.

Huge difference of estimated and actual number of rows clearly indicating that query optimizer was unable to proprly estimate number of rows and with this wrong estimation, it has selected a more costly execution plan. Basically Query Optimizer does not know the value of local variable at the time of optimization and resultantly can’t use histogram of statistics. It behaves differently with inequality and equality operators.

In Case of Inequality Operator:
In our case of inequality operator in query, query optimizer used a simple formula of 30% of total rows.

Estimated Rows =(Total Rows * 30)/100 = (100000*30)/100 = 30000

 In Case of Equality Operator:

DECLARE@RequiredDate DATETIME
SET@RequiredDate = ‘2012-07-10 03:18:01.640’

SELECT * FROM TempTable
WHEREtempDateTime  =@RequiredDate

If equality operator is used with local variables, query optimizer gets estimated rows figure from a different formula i.e.  Density * Total Number of Table Rows. Execute following query to get density value.

DBCC SHOW_STATISTICS (‘dbo.TempTable’, IX_tempDateTime)

All Density = 0.0007358352

Total Number of Rows in Table = 100000
Estimated Rows = Density * Total Number =  0.0007358352 *  100000 = 73.5835

Drop table when not required

DROP TABLETempTable

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Posted on July 10, 2012, in Index, Performance Tuning, Sql Server 2005, Sql Server 2008, SQL Server 2012, Sql Server Internals, Store Procedures. Bookmark the permalink. 1 Comment.

  1. I see the result too, but I have to disagree on the conclusion.Since not all columns are included, the second query goes for a total scan for all rows to avoid the costly key lookup, hence 481 reads.The first query takes only 3 reads to get the wanted 77 rows, but then it uses 77 reads to get the missing column. If you use SET STATISTICS TIME ON, you can see there is no (or minimal) time difference between the two approaches.If you make tempmonth column included too, you get identical results with both queries.

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