SQL Server 2005부터 추가된 DMV를 통해 여러 가지 유용한 스크립트를 만들 수 있습니다.
이번에는 특정 DB 또는 모든 DB에 대해 SELECT, DELETE, INSERT 또는 UPDATE Statmemt가
어떠한 비율로 발생하는지 그리고 리소스별 어떠한 비율로 사용하는지 쉽게 확인 할 수 있는 쿼리 입니다.
지금까지 막연하게 "이 DB는 대부분이 SELECT가 발생하는 것이야."
이러한 생각을 구체적이고 명확하게 보여줄 수 있습니다.
처음 접하는 시스템을 분석시 위와 같은 자료가 있으면 보다 쉽게 파악 할 수 있을 것입니다.
제 생각에는 ~ 꽤 DB관련 업무에 유용하게 사용될 수 있을 것 같습니다.ㅎㅎ
Statement.sql아래는 수행한 결과 입니다.
ExecutionCount는 분당 실행한 횟수 입니다.
[로그성 DB시스템]
[일반 OLTP DB시스템]
with XMLNAMESPACES ('http://schemas.microsoft.com/sqlserver/2004/07/showplan' as sql)
SELECT
StatementType
,ExecutionCount
,cast((ExecutionCount*1.0/total_ExecutionCount)*100 as Decimal(18,2)) as [% ExecutionCount]
,cast((Elapsed_Time/total_Elapsed_Time)*100 as Decimal(18,2)) as [% Elapsed_Time]
,cast((Worker_Time/total_Worker_Time)*100 as Decimal(18,2)) as [% Worker_Time]
,cast((logical_reads/total_logical_reads)*100 as Decimal(18,2)) as [% logical_reads]
,cast((logical_writes/total_logical_writes)*100 as Decimal(18,2)) as [% logical_writes]
,cast((physical_reads/total_physical_reads)*100 as Decimal(18,2)) as [% physical_reads]
FROM
(
SELECT
StatementType
,sum(avg_ExecutionCount) over(partition by StatementType) as ExecutionCount
,sum(avg_ExecutionCount) over(partition by 1) as total_ExecutionCount
,sum(avg_total_Elapsed_Time) over(partition by StatementType) as Elapsed_Time
,sum(avg_total_Elapsed_Time) over(partition by 1) as total_Elapsed_Time
,sum(avg_total_Worker_Time) over(partition by StatementType) as Worker_Time
,sum(avg_total_Worker_Time) over(partition by 1) as total_Worker_Time
,sum(avg_total_logical_reads) over(partition by StatementType) as logical_reads
,sum(avg_total_logical_reads) over(partition by 1) as total_logical_reads
,sum(avg_total_logical_writes) over(partition by StatementType) as logical_writes
,sum(avg_total_logical_writes) over(partition by 1) as total_logical_writes
,sum(avg_total_physical_reads) over(partition by StatementType) as physical_reads
,case when
sum(avg_total_physical_reads) over(partition by 1) = 0
THEN NULL ELSE sum(avg_total_physical_reads) over(partition by 1)
END as total_physical_reads
FROM(
SELECT StatementType
,count(*) as cnt
,sum(ISNULL(ExecutionCount/DATEDIFF(MINUTE , creation_time,GetDate()),0)) as avg_ExecutionCount
,cast(sum(ISNULL([total_Elapsed_Time(sec)]/DATEDIFF(MINUTE , creation_time, GetDate()), 0)) as Decimal(18,2)) as avg_total_Elapsed_Time
,cast(sum(ISNULL([total_Worker_Time(ms)]/DATEDIFF(MINUTE , creation_time, GetDate()), 0)) as Decimal(18,2)) as avg_total_Worker_Time
,cast(sum(ISNULL([total_logical_reads]/DATEDIFF(MINUTE , creation_time, GetDate()), 0)) as Decimal(18,2)) as avg_total_logical_reads
,cast(sum(ISNULL([total_logical_writes]/DATEDIFF(MINUTE , creation_time, GetDate()), 0)) as Decimal(18,2)) as avg_total_logical_writes
,cast(sum(ISNULL(total_physical_reads/DATEDIFF(MINUTE , creation_time, GetDate()), 0)) as Decimal(18,2)) as avg_total_physical_reads
FROM (
SELECT
db_name
,ISNULL([StatementType],StatementType2) as StatementType
--,[statement_text]
,[creation_time]
,[ExecutionCount]
,[total_Elapsed_Time(sec)]
,[total_Worker_Time(ms)]
,[total_logical_reads]
,[total_logical_writes]
,[total_physical_reads]
FROM (
SELECT
db_name(qp.dbid) AS 'db_name'
, qs.creation_time
, qs.execution_count AS 'ExecutionCount'
, qs.total_elapsed_time/1000.0/1000.0 AS 'total_Elapsed_Time(sec)'
, qs.total_worker_time/1000.0 AS 'total_Worker_Time(ms)'
, total_logical_reads
, qs.total_logical_writes
, total_physical_reads
, cast(qp.query_plan as xml) as query_plan
FROM sys.dm_exec_query_stats AS qs
CROSS APPLY sys.dm_exec_text_query_plan(qs.plan_handle,qs.statement_start_offset,qs.statement_end_offset) qp
)X
OUTER APPLY
(
SELECT
c.value('(//sql:StmtSimple/@StatementType)[1]','VARCHAR(100)') AS "StatementType"
,c.value('(//sql:StmtCond/@StatementType)[1]','VARCHAR(100)') AS "StatementType2"
FROM query_plan.nodes('//sql:QueryPlan')B(C)
)xp
WHERE db_id(db_name) > 4
AND DATEDIFF(MINUTE,creation_time, GetDate()) > 0
AND StatementType is not null
)X
group by StatementType
)Y
)Z
송 혁, SQL Server MVP
hyoksong.tistory.com
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