让我们看看这个代码:
DBCC FREEPROCCACHE GO SELECT SUM(LineTotal) AS LineTotal FROM AdventureWorks.Sales.SalesOrderHeader H JOIN AdventureWorks.Sales.SalesOrderDetail D ON D.SalesOrderID = H.SalesOrderID WHERE H.SalesOrderID = 56000 GO SELECT SUM(LineTotal) AS LineTotal FROM AdventureWorks.Sales.SalesOrderHeader H JOIN AdventureWorks.Sales.SalesOrderDetail D ON D.SalesOrderID = H.SalesOrderID WHERE H.SalesOrderID = 56001 GO SELECT stats.execution_count AS cnt, p.size_in_bytes AS [size], LEFT([sql].[text], 200) AS [plan_text] FROM sys.dm_exec_cached_plans p OUTER APPLY sys.dm_exec_sql_text (p.plan_handle) sql JOIN sys.dm_exec_query_stats stats ON stats.plan_handle = p.plan_handle; GO |
在这里,我释放了过程缓存,然后运行这两个包含一个JOIN的、不同的非简单的T-SQL语句。然后我将检查缓存计划。这是这个使用DMV 的SELECT语句的输出(注意,输出被重新格式化了,以便它更易读):
cnt size plan_text --- ----------- ------------------------------------------------------------------------------- 1 49152 SELECT SUM(LineTotal) AS LineTotal FROM AdventureWorks.Sales.SalesOrderHeader H JOIN AdventureWorks.Sales.SalesOrderDetail D ON D.SalesOrderID = H.SalesOrderID WHERE H.SalesOrderID = 56001 1 49152 SELECT SUM(LineTotal) AS LineTotal FROM AdventureWorks.Sales.SalesOrderHeader H JOIN AdventureWorks.Sales.SalesOrderDetail D ON D.SalesOrderID = H.SalesOrderID WHERE H.SalesOrderID = 56000 |
下面是上面的代码被重新编写来使用sp_executesql 系统存储过程:
DBCC FREEPROCCACHE; GO EXEC sp_executesql N'SELECT SUM(LineTotal) AS LineTotal FROM AdventureWorks.Sales.SalesOrderHeader H JOIN AdventureWorks.Sales.SalesOrderDetail D ON D.SalesOrderID = H.SalesOrderID WHERE H.SalesOrderID = @SalesOrderID', N'@SalesOrderID INT', @SalesOrderID = 56000; GO EXEC sp_executesql N'SELECT SUM(LineTotal) AS LineTotal FROM AdventureWorks.Sales.SalesOrderHeader H JOIN AdventureWorks.Sales.SalesOrderDetail D ON D.SalesOrderID = H.SalesOrderID WHERE H.SalesOrderID = @SalesOrderID', N'@SalesOrderID INT', @SalesOrderID = 56001; GO SELECT stats.execution_count AS exec_count, p.size_in_bytes AS [size], [sql].[text] AS [plan_text] FROM sys.dm_exec_cached_plans p OUTER APPLY sys.dm_exec_sql_text (p.plan_handle) sql JOIN sys.dm_exec_query_stats stats ON stats.plan_handle = p.plan_handle; GO |
现在当我运行上面的代码时,我从DMV SELECT语句得到下面的输出(注意,输出被重新格式化了,以便它更易读):
cnt size plan_text --- ----------- ----------------------------------------------------------------------------------------- 2 49152 (@SalesOrderID INT)SELECT SUM(LineTotal) AS LineTotal FROM AdventureWorks.Sales.SalesOrderHeader H JOIN AdventureWorks.Sales.SalesOrderDetail D ON D.SalesOrderID = H.SalesOrderID WHERE H.SalesOrderID = @SalesOrderID |
从这个输出,你可以看出,我有一个参数化缓存计划,它被执行了两次,为每个EXEC语句各执行了一次。
使用参数化查询来节省资源和优化性能
在语句可以被执行之前,每个T-SQL语句都需要被评估,而且需要建立一个执行计划。创建执行计划会占用宝贵的CPU资源。当执行计划被创建后,它使用内存空间将它存储在过程缓存中。降低CPU和内存使用的一个方法是利用参数化查询。尽管数据库可以被设置为对所有查询FORCE参数化,但是这不总是最好的选择。通过了解你的哪些T-SQL语句可以被参数化然后使用sp_executesql存储过程,你可以帮助SQL Server节省资源并优化你的查询的性能。
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