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I have total of 11 years of IT experience with Application development, Database Development and Database Administration. I have worked with different version of SQL server from 7.0 to 2008.Started my carrier as VB ,VC++ and database developer in a banking sector for implementing their core banking solution. Currently working as Database Administrator with wide knowledge in performance tuning, high availability solution, troubleshooting and server monitoring. This blog is my humble attempt to share my knowledge and what I learned from my day to day work.
- Posted on 27 June 2012
In my last post , we have gone through the parameter sniffing and possible solutions for parameter sniffing. In the possible solutions except the local variable and Optimize For Unknown are very straight forward solution and we know how they helps us to resolve the issue.In this post we will see how local variable and option for unknown are resolving the parameter sniffing issue.
If the parameter values are known while compiling the stored procedure , the optimizer use the statistics histogram and generate the best plan for the parameters.When we define local variable and use that in the query, SQL server will not be able use the parameter values to find the optimal value. In this scenario optimizer use density vector information of the statistics and it will generate same execution plan for all input parameter. Let us see how it will work.
Below statement returns returns 13 records by doing index seek and key lookup operation.This plan is generated based on the estimation that, the query will return 44.5 records. The query optimizer done the estimation based on the histogram.
SELECT * FROM Sales.SalesOrderDetail WHERE productid =744
A portion of the out put of the above query will looks like below
The estimated number of rows is calculated based on the EQ_ROWS and AVG_RANGE_ROWS. In this example, the parameter value 744 is not matching with RANGE_HI_KEY and optimizer took AVG_RANGE_ROWS values of 747 to calculate the estimated number of rows. The execution plan will be same if you convert this to a procedure.
Let us see how it will work with procedure with local variable
CREATE PROCEDURE get_SalesOrderDetail
DECLARE @L_ProductId INT
SET @L_ProductId =@ProductId
SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = @L_ProductId
If you execute this procedure with parameter value 744, the execution plan will will looks like below.
EXEC get_SalesOrderDetail 744
This time optimizer gone for index scan under the estimation that the query will return 456 records.As we have defined the local variable, the parameter value is not available at compilation time and optimizer used the density vector to estimate the number of row. The value of estimated number of rows will be same in execution plan of this procedure with any parameter value and hence the execution plan.
Let us see how optimizer calculating the estimated number of rows in this case. As the parameter value is not available at the time of optimization, it assumes that records are distributed uniformly. In the SalesOrderDetail table we have 266 distinct value for Productid and the total number of records is 121317.If you divide total number of records with number of distinct values of productid , you will get 121317/266=456.07 which is same as estimated number of rows. All these data required for the calculation are available in the statistics.The total number of records is available in the first sections. The density value 0.003759399 is available in the second section which is equivalent to 1/266. So the estimated number of rows =121317X0.003759399 = 456.079.
You can see the same execution plan if we change this procedure with optimize for unknown as given below
ALTER PROCEDURE get_SalesOrderDetail (
SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = @ProductId OPTION (OPTIMIZE FOR UNKNOWN)
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