数据库性能优化常用sql脚本总结

最近闲来无事，正好抽出时间，来总结总结 sql性能优化方面的一下小技巧,小工具。虽然都是些很杂的东西，但是我个人觉得，如果真的清楚了里面的一下指标，或许真的能抵半个DBA。

　　有些时候，找不到DBA或者根本就没有DBA的时候，程序员就只能靠自己想办法了解决。久而久之，久病成医，说不定就成了半个DBA了。 这里面的一些脚本，有自己总结的，也有网上找的。希望能给程序员在性能优化方面一些帮助。（PS: 这些脚本，都是SQL Server 下的）。

 

 1. 当前连接的Session 有多少

SELECT login_name

,[program_name]

,COUNT(session_id) AS [session_count]

FROM sys.dm_exec_sessions WITH (NOLOCK)

GROUP BY login_name,[program_name]

ORDER BY COUNT(session_id) desc;

 

2. 每个数据库上的Session 数量是多少

SELECT DB_NAME(dbid) AS DBName

,COUNT(dbid) AS NumberOfConnections

,loginame AS LoginName

FROM sys.sysprocesses

WHERE dbid > 0

GROUP BY dbid,loginame

 

3. 查看阻塞

SELECT

SPID                = er.session_id

,STATUS             = ses.STATUS

,[LOGIN]            = ses.login_name

,HOST               = ses.host_name

,BlkBy              = er.blocking_session_id

,DBName             = DB_NAME(er.database_id)

,CommandType        = er.command

,SQLStatement       = st.text

,BlockingText     = bst.text

,ObjectName         = OBJECT_NAME(st.objectid)

,ElapsedMS          = er.total_elapsed_time

,CPUTime            = er.cpu_time

,IOReads            = er.logical_reads + er.reads

,IOWrites           = er.writes

,LastWaitType       = er.last_wait_type

,StartTime          = er.start_time

,Protocol           = con.net_transport

,ConnectionWrites   = con.num_writes

,ConnectionReads    = con.num_reads

,ClientAddress      = con.client_net_address

,Authentication     = con.auth_scheme

FROM sys.dm_exec_requests er

OUTER APPLY sys.dm_exec_sql_text(er.sql_handle) st

LEFT JOIN sys.dm_exec_sessions ses

ON ses.session_id = er.session_id

LEFT JOIN sys.dm_exec_connections con

ON con.session_id = ses.session_id

LEFT JOIN sys.dm_exec_requests ber

ON er.blocking_session_id=ber.session_id

OUTER APPLY sys.dm_exec_sql_text(ber.sql_handle) bst

WHERE er.session_id > 50

ORDER BY er.blocking_session_id DESC,er.session_id

 

4. 找出哪些表的Index 需要改进

SELECT CONVERT(DECIMAL(18, 2), user_seeks * avg_total_user_cost * (avg_user_impact * 0.01)) AS [index_advantage]

,migs.last_user_seek

,mid.[statement] AS [Database.Schema.Table]

,mid.equality_columns

,mid.inequality_columns

,mid.included_columns

,migs.unique_compiles

,migs.user_seeks

,migs.avg_total_user_cost

,migs.avg_user_impact

FROM sys.dm_db_missing_index_group_stats AS migs WITH (NOLOCK)

INNER JOIN sys.dm_db_missing_index_groups AS mig WITH (NOLOCK) ON migs.group_handle = mig.index_group_handle

INNER JOIN sys.dm_db_missing_index_details AS mid WITH (NOLOCK) ON mig.index_handle = mid.index_handle

ORDER BY index_advantage desc

 

 5. 查看Index 的Statistics 最后更新时间

SELECT SCHEMA_NAME(o.[schema_id]) + N'.' + o.[name] AS [Object Name]

,o.type_desc AS [Object Type]

,i.[name] AS [Index Name]

,STATS_DATE(i.[object_id], i.index_id) AS [Statistics Date]

,s.auto_created

,s.no_recompute

,s.user_created

,st.row_count

,st.used_page_count

FROM sys.objects AS o WITH (NOLOCK)

INNER JOIN sys.indexes AS i WITH (NOLOCK) ON o.[object_id] = i.[object_id]INNER JOIN sys.stats AS s WITH (NOLOCK) ON i.[object_id] = s.[object_id]

AND i.index_id = s.stats_id

INNER JOIN sys.dm_db_partition_stats AS st WITH (NOLOCK) ON o.[object_id] = st.[object_id]

AND i.[index_id] = st.[index_id]WHERE o.[type] IN ('U','V')

AND st.row_count > 0

ORDER BY STATS_DATE(i.[object_id], i.index_id) desc;

 

6. 查看Index 碎片化指数

SELECT DB_NAME(ps.database_id) AS [Database Name]

,OBJECT_NAME(ps.[object_id]) AS [Object Name]

,i.[name] AS [Index Name]

,ps.index_id

,ps.index_type_desc

,ps.avg_fragmentation_in_percent

,ps.fragment_count

,ps.page_count

,i.fill_factor

,i.has_filter

,i.filter_definition

FROM sys.dm_db_index_physical_stats(DB_ID(), NULL, NULL, NULL, N'LIMITED') AS ps

INNER JOIN sys.indexes AS i WITH (NOLOCK) ON ps.[object_id] = i.[object_id]

AND ps.index_id = i.index_id

WHERE ps.database_id = DB_ID()

AND ps.page_count > 2500

ORDER BY ps.avg_fragmentation_in_percent desc;

 

 7. 查询前 10 个可能是性能最差的 SQL 语句

SELECT TOP 10 TEXT AS 'SQL Statement'
,last_execution_time AS 'Last Execution Time'
,(total_logical_reads + total_physical_reads + total_logical_writes) / execution_count AS [Average IO]
,(total_worker_time / execution_count) / 1000000.0 AS [Average CPU Time (sec)]
,(total_elapsed_time / execution_count) / 1000000.0 AS [Average Elapsed Time (sec)]
,execution_count AS "Execution Count"
,qp.query_plan AS "Query Plan"
FROM sys.dm_exec_query_stats qs
CROSS APPLY sys.dm_exec_sql_text(qs.plan_handle) st
CROSS APPLY sys.dm_exec_query_plan(qs.plan_handle) qp
ORDER BY total_elapsed_time / execution_count DESC