我知道基于标题的这个问题主要与PREEMPTIVE_OS_DELETESECURITYCONTEXT等待类型有关，但是我认为这是对真正问题的误导，即“ 客户抱怨SQL Server上的CPU使用率过高 ”。
我认为专注于这种特定的等待类型是一种疯狂的追求，原因是它在每次建立连接时都会上升。我在笔记本电脑上运行以下查询（意味着我是唯一的用户）：
SELECT *
FROM sys.dm_os_wait_stats
WHERE wait_type = N'PREEMPTIVE_OS_DELETESECURITYCONTEXT'
然后，我执行以下任一操作，然后重新运行此查询：
- 打开一个新的查询标签
- 关闭新的查询标签
- 从DOS提示符下运行以下命令：
SQLCMD -E -Q "select 1"
现在，我们知道CPU很高，因此我们应该查看正在运行的进程以查看哪些会话具有较高的CPU：
SELECT req.session_id AS [SPID],
req.blocking_session_id AS [BlockedBy],
req.logical_reads AS [LogReads],
DB_NAME(req.database_id) AS [DatabaseName],
SUBSTRING(txt.[text],
(req.statement_start_offset / 2) + 1,
CASE
WHEN req.statement_end_offset > 0
THEN (req.statement_end_offset - req.statement_start_offset) / 2
ELSE LEN(txt.[text])
END
) AS [CurrentStatement],
txt.[text] AS [CurrentBatch],
CONVERT(XML, qplan.query_plan) AS [StatementQueryPlan],
OBJECT_NAME(qplan.objectid, qplan.[dbid]) AS [ObjectName],
sess.[program_name],
sess.[host_name],
sess.nt_user_name,
sess.total_scheduled_time,
sess.memory_usage,
req.*
FROM sys.dm_exec_requests req
INNER JOIN sys.dm_exec_sessions sess
ON sess.session_id = req.session_id
CROSS APPLY sys.dm_exec_sql_text(req.[sql_handle]) txt
OUTER APPLY sys.dm_exec_text_query_plan(req.plan_handle,
req.statement_start_offset,
req.statement_end_offset) qplan
WHERE req.session_id <> @@SPID
ORDER BY req.logical_reads DESC, req.cpu_time DESC
--ORDER BY req.cpu_time DESC, req.logical_reads DESC
我通常按原样运行上面的查询，但是您也可以切换注释掉了哪个ORDER BY子句，以查看是否给出了更有趣/有用的结果。
或者，您可以基于dm_exec_query_stats运行以下命令以查找成本最高的查询。下面的第一个查询将向您显示单个查询（即使它们有多个计划），并按平均CPU时间排序，但是您可以轻松地将其更改为平均逻辑读取。找到看起来占用大量资源的查询后，将“ sql_handle”和“ statement_start_offset”复制到下面第二个查询的WHERE条件中，以查看各个计划（可以大于1）。滚动到最右侧，并假设有一个XML计划，它将显示为链接（在网格模式下），如果您单击它，它将带您到计划查看器。
查询1：获取查询信息
;WITH cte AS
(
SELECT qstat.[sql_handle],
qstat.statement_start_offset,
qstat.statement_end_offset,
COUNT(*) AS [NumberOfPlans],
SUM(qstat.execution_count) AS [TotalExecutions],
SUM(qstat.total_worker_time) AS [TotalCPU],
(SUM(qstat.total_worker_time * 1.0) / SUM(qstat.execution_count)) AS [AvgCPUtime],
MAX(qstat.max_worker_time) AS [MaxCPU],
SUM(qstat.total_logical_reads) AS [TotalLogicalReads],
(SUM(qstat.total_logical_reads * 1.0) / SUM(qstat.execution_count)) AS [AvgLogicalReads],
MAX(qstat.max_logical_reads) AS [MaxLogicalReads],
SUM(qstat.total_rows) AS [TotalRows],
(SUM(qstat.total_rows * 1.0) / SUM(qstat.execution_count)) AS [AvgRows],
MAX(qstat.max_rows) AS [MaxRows]
FROM sys.dm_exec_query_stats qstat
GROUP BY qstat.[sql_handle], qstat.statement_start_offset, qstat.statement_end_offset
)
SELECT cte.*,
DB_NAME(txt.[dbid]) AS [DatabaseName],
SUBSTRING(txt.[text],
(cte.statement_start_offset / 2) + 1,
CASE
WHEN cte.statement_end_offset > 0
THEN (cte.statement_end_offset - cte.statement_start_offset) / 2
ELSE LEN(txt.[text])
END
) AS [CurrentStatement],
txt.[text] AS [CurrentBatch]
FROM cte
CROSS APPLY sys.dm_exec_sql_text(cte.[sql_handle]) txt
ORDER BY cte.AvgCPUtime DESC
查询2：获取计划信息
SELECT *,
DB_NAME(qplan.[dbid]) AS [DatabaseName],
CONVERT(XML, qplan.query_plan) AS [StatementQueryPlan],
SUBSTRING(txt.[text],
(qstat.statement_start_offset / 2) + 1,
CASE
WHEN qstat.statement_end_offset > 0
THEN (qstat.statement_end_offset - qstat.statement_start_offset) / 2
ELSE LEN(txt.[text])
END
) AS [CurrentStatement],
txt.[text] AS [CurrentBatch]
FROM sys.dm_exec_query_stats qstat
CROSS APPLY sys.dm_exec_sql_text(qstat.[sql_handle]) txt
OUTER APPLY sys.dm_exec_text_query_plan(qstat.plan_handle,
qstat.statement_start_offset,
qstat.statement_end_offset) qplan
-- paste info from Query #1 below
WHERE qstat.[sql_handle] = 0x020000001C70C614D261C85875D4EF3C90BD18D02D62453800....
AND qstat.statement_start_offset = 164
-- paste info from Query #1 above
ORDER BY qstat.total_worker_time DESC
