转载地址：https://www.cnblogs.com/tianqing/p/11152799.html
今天线上SQLServer数据库的CPU被打爆了，紧急情况下，分析了数据库阻塞、连接分布、最耗CPU的TOP10 SQL、查询SQL并行度配置、查询SQL 重编译的原因等等
整理了一些常用的SQL
1. 查询数据库阻塞
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1
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SELECT
*
FROM
sys.sysprocesses
WHERE
blocked<>0
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查询结果中，重点看Blocked这一列，先找出最多的SID，然后循环找出Root的阻塞根源SID
查询阻塞根源Session的SQL
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DBCC Inputbuffer(sid)
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2. 查询SQL连接分布
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SELECT
Hostname
FROM
sys.sysprocesses
WHERE
hostname<>
''
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1，查看连接到‘TestDB2’数据库的连接
select * from master.dbo.sysprocesses
where dbid = DB_ID('TestDB2')
*查询某个数据库用户的连接情况
sp_who 'sa'
2，查看数据库允许的最大连接
select @@MAX_CONNECTIONS
3，查看数据库自上次启动以来的连接次数
SELECT @@CONNECTIONS
4，关闭连接
上面的查询可以得到spid，根据spid，关闭进程就可以了。
kill 54
3. 查询最消耗CPU的SQL Top10
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select
top
(10) st.text
as
Query, qs.total_worker_time, qs.execution_count
from
sys.dm_exec_query_stats
as
qs
CROSS
Apply sys.dm_exec_sql_text(qs.sql_handle)
AS
st
order
by
qs.total_worker_time
desc
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4. 查看SQLServer并行度
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SELECT
value_in_use
FROM
sys.configurations
WHERE
name
=
'max degree of parallelism'
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并行度如果设置为1，To suppress parallel plan generation, set max degree of parallelism to 1
将阻止并行编译生成SQL执行计划，最大并行度设置为1
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USE DatabaseName ;
GO
EXEC
sp_configure
'show advanced options'
, 1;
GO
RECONFIGURE
WITH
OVERRIDE;
GO
EXEC
sp_configure
'max degree of parallelism'
, 16;
GO
RECONFIGURE
WITH
OVERRIDE;
GO
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5. 查询SQL Server Recompilation Reasons
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select
dxmv.
name
, dxmv.map_key,dxmv.map_value
from
sys.dm_xe_map_values
as
dxmv
where
dxmv.
name
=
'statement_recompile_cause'
order
by
dxmv.map_key
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6. 将SQL Trace文件存入一张表，做聚合分析（CPU、IO、执行时间等）
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SELECT
*
INTO
TabSQL
FROM
fn_trace_gettable(
'C:\Users\***\Desktop\Trace\sql05trace20180606-业务.trc'
,
default
);
GO
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对上述表数据进行聚合分析最耗时的SQL
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select
top
100
replace
(
replace
(
replace
(
substring
(Textdata,1,6600) ,
char
(10),
' '
),
char
(13),
' '
) ,
char
(9),
' '
)
as
'名称'
,
--substring(Textdata,1,6600) as old,
count
(*)
as
'数量'
,
sum
(duration/1000)
as
'总执行时间ms'
,
avg
(duration/1000)
as
'平均执行时间ms'
,
avg
(cpu)
as
'平均CPU时间ms'
,
avg
(reads)
as
'平均读次数'
,
avg
(writes)
as
'平均写次数'
, LoginName
from
TabSQL t
group
by
replace
(
replace
(
replace
(
substring
(Textdata,1,6600) ,
char
(10),
' '
),
char
(13),
' '
) ,
char
(9),
' '
) , LoginName
order
by
sum
(duration)
desc
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最耗IO的SQL
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7
8
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10
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12
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select
TOP
100
replace
(
replace
(
replace
(
substring
(Textdata,1,6600) ,
char
(10),
' '
),
char
(13),
' '
) ,
char
(9),
' '
)
as
'名称'
,LoginName,
count
(*)
as
'数量'
,
sum
(duration/1000)
as
'总执行时间ms'
,
avg
(duration/1000)
as
'平均执行时间ms'
,
sum
(cpu)
as
'总CPU时间ms'
,
avg
(cpu)
as
'平均CPU时间ms'
,
sum
(reads)
as
'总读次数'
,
avg
(reads)
as
'平均读次数'
,
avg
(writes)
as
'平均写次数'
from
TabSQL
group
by
replace
(
replace
(
replace
(
substring
(Textdata,1,6600) ,
char
(10),
' '
),
char
(13),
' '
) ,
char
(9),
' '
) ,LoginName
order
by
sum
(reads)
desc
|
最耗CPU的SQL
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SELECT
TOP
100
replace
(
replace
(
replace
(
substring
(Textdata,1,6600) ,
char
(10),
' '
),
char
(13),
' '
) ,
char
(9),
' '
)
as
'名称'
,LoginName,
count
(*)
as
'数量'
,
sum
(duration/1000)
as
'总执行时间ms'
,
avg
(duration/1000)
as
'平均执行时间ms'
,
sum
(cpu)
as
'总CPU时间'
,
avg
(cpu)
as
'平均CPU时间'
,
avg
(reads)
as
'平均读次数'
,
avg
(writes)
as
'平均写次数'
from
TabSQL
group
by
replace
(
replace
(
replace
(
substring
(Textdata,1,6600) ,
char
(10),
' '
),
char
(13),
' '
) ,
char
(9),
' '
) ,LoginName
order
by
avg
(cpu)
desc
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