查询历史是否存储在一些日志文件中?如果有，你能告诉我怎么找到他们的位置吗?如果没有，你能给我一些建议吗?
当前回答
If the queries you are interested in are dynamic queries that fail intermittently, you could log the SQL and the datetime and user in a table at the time the dynamic statement is created. It would be done on a case-by case basis though as it requires specific programming to happen and it takes a littel extra processing time, so do it only for those few queries you are most concerned about. But having a log of the specific statements executed can really help when you are trying to find out why it fails once a month only. Dynamic queries are hard to thoroughly test and sometimes you get one specific input value that just won't work and doing this logging at the time the SQL is created is often the best way to see what specifically wasn in the sql that was built.
其他回答
查询历史可以通过系统视图查看:
sys.dm_exec_query_stats sys.dm_exec_sql_text sys.dm_exec_query_plan
例如，使用以下查询:
select top(100)
creation_time,
last_execution_time,
execution_count,
total_worker_time/1000 as CPU,
convert(money, (total_worker_time))/(execution_count*1000)as [AvgCPUTime],
qs.total_elapsed_time/1000 as TotDuration,
convert(money, (qs.total_elapsed_time))/(execution_count*1000)as [AvgDur],
total_logical_reads as [Reads],
total_logical_writes as [Writes],
total_logical_reads+total_logical_writes as [AggIO],
convert(money, (total_logical_reads+total_logical_writes)/(execution_count + 0.0)) as [AvgIO],
[sql_handle],
plan_handle,
statement_start_offset,
statement_end_offset,
plan_generation_num,
total_physical_reads,
convert(money, total_physical_reads/(execution_count + 0.0)) as [AvgIOPhysicalReads],
convert(money, total_logical_reads/(execution_count + 0.0)) as [AvgIOLogicalReads],
convert(money, total_logical_writes/(execution_count + 0.0)) as [AvgIOLogicalWrites],
query_hash,
query_plan_hash,
total_rows,
convert(money, total_rows/(execution_count + 0.0)) as [AvgRows],
total_dop,
convert(money, total_dop/(execution_count + 0.0)) as [AvgDop],
total_grant_kb,
convert(money, total_grant_kb/(execution_count + 0.0)) as [AvgGrantKb],
total_used_grant_kb,
convert(money, total_used_grant_kb/(execution_count + 0.0)) as [AvgUsedGrantKb],
total_ideal_grant_kb,
convert(money, total_ideal_grant_kb/(execution_count + 0.0)) as [AvgIdealGrantKb],
total_reserved_threads,
convert(money, total_reserved_threads/(execution_count + 0.0)) as [AvgReservedThreads],
total_used_threads,
convert(money, total_used_threads/(execution_count + 0.0)) as [AvgUsedThreads],
case
when sql_handle IS NULL then ' '
else(substring(st.text,(qs.statement_start_offset+2)/2,(
case
when qs.statement_end_offset =-1 then len(convert(nvarchar(MAX),st.text))*2
else qs.statement_end_offset
end - qs.statement_start_offset)/2 ))
end as query_text,
db_name(st.dbid) as database_name,
object_schema_name(st.objectid, st.dbid)+'.'+object_name(st.objectid, st.dbid) as [object_name],
sp.[query_plan]
from sys.dm_exec_query_stats as qs with(readuncommitted)
cross apply sys.dm_exec_sql_text(qs.[sql_handle]) as st
cross apply sys.dm_exec_query_plan(qs.[plan_handle]) as sp
WHERE st.[text] LIKE '%query%'
使用下面的脚本可以看到当前运行的查询:
select ES.[session_id]
,ER.[blocking_session_id]
,ER.[request_id]
,ER.[start_time]
,DateDiff(second, ER.[start_time], GetDate()) as [date_diffSec]
, COALESCE(
CAST(NULLIF(ER.[total_elapsed_time] / 1000, 0) as BIGINT)
,CASE WHEN (ES.[status] <> 'running' and isnull(ER.[status], '') <> 'running')
THEN DATEDIFF(ss,0,getdate() - nullif(ES.[last_request_end_time], '1900-01-01T00:00:00.000'))
END
) as [total_time, sec]
, CAST(NULLIF((CAST(ER.[total_elapsed_time] as BIGINT) - CAST(ER.[wait_time] AS BIGINT)) / 1000, 0 ) as bigint) as [work_time, sec]
, CASE WHEN (ER.[status] <> 'running' AND ISNULL(ER.[status],'') <> 'running')
THEN DATEDIFF(ss,0,getdate() - nullif(ES.[last_request_end_time], '1900-01-01T00:00:00.000'))
END as [sleep_time, sec] --Время сна в сек
, NULLIF( CAST((ER.[logical_reads] + ER.[writes]) * 8 / 1024 as numeric(38,2)), 0) as [IO, MB]
, CASE ER.transaction_isolation_level
WHEN 0 THEN 'Unspecified'
WHEN 1 THEN 'ReadUncommited'
WHEN 2 THEN 'ReadCommited'
WHEN 3 THEN 'Repetable'
WHEN 4 THEN 'Serializable'
WHEN 5 THEN 'Snapshot'
END as [transaction_isolation_level_desc]
,ER.[status]
,ES.[status] as [status_session]
,ER.[command]
,ER.[percent_complete]
,DB_Name(coalesce(ER.[database_id], ES.[database_id])) as [DBName]
, SUBSTRING(
(select top(1) [text] from sys.dm_exec_sql_text(ER.[sql_handle]))
, ER.[statement_start_offset]/2+1
, (
CASE WHEN ((ER.[statement_start_offset]<0) OR (ER.[statement_end_offset]<0))
THEN DATALENGTH ((select top(1) [text] from sys.dm_exec_sql_text(ER.[sql_handle])))
ELSE ER.[statement_end_offset]
END
- ER.[statement_start_offset]
)/2 +1
) as [CURRENT_REQUEST]
,(select top(1) [text] from sys.dm_exec_sql_text(ER.[sql_handle])) as [TSQL]
,(select top(1) [objectid] from sys.dm_exec_sql_text(ER.[sql_handle])) as [objectid]
,(select top(1) [query_plan] from sys.dm_exec_query_plan(ER.[plan_handle])) as [QueryPlan]
,NULL as [event_info]--(select top(1) [event_info] from sys.dm_exec_input_buffer(ES.[session_id], ER.[request_id])) as [event_info]
,ER.[wait_type]
,ES.[login_time]
,ES.[host_name]
,ES.[program_name]
,cast(ER.[wait_time]/1000 as decimal(18,3)) as [wait_timeSec]
,ER.[wait_time]
,ER.[last_wait_type]
,ER.[wait_resource]
,ER.[open_transaction_count]
,ER.[open_resultset_count]
,ER.[transaction_id]
,ER.[context_info]
,ER.[estimated_completion_time]
,ER.[cpu_time]
,ER.[total_elapsed_time]
,ER.[scheduler_id]
,ER.[task_address]
,ER.[reads]
,ER.[writes]
,ER.[logical_reads]
,ER.[text_size]
,ER.[language]
,ER.[date_format]
,ER.[date_first]
,ER.[quoted_identifier]
,ER.[arithabort]
,ER.[ansi_null_dflt_on]
,ER.[ansi_defaults]
,ER.[ansi_warnings]
,ER.[ansi_padding]
,ER.[ansi_nulls]
,ER.[concat_null_yields_null]
,ER.[transaction_isolation_level]
,ER.[lock_timeout]
,ER.[deadlock_priority]
,ER.[row_count]
,ER.[prev_error]
,ER.[nest_level]
,ER.[granted_query_memory]
,ER.[executing_managed_code]
,ER.[group_id]
,ER.[query_hash]
,ER.[query_plan_hash]
,EC.[most_recent_session_id]
,EC.[connect_time]
,EC.[net_transport]
,EC.[protocol_type]
,EC.[protocol_version]
,EC.[endpoint_id]
,EC.[encrypt_option]
,EC.[auth_scheme]
,EC.[node_affinity]
,EC.[num_reads]
,EC.[num_writes]
,EC.[last_read]
,EC.[last_write]
,EC.[net_packet_size]
,EC.[client_net_address]
,EC.[client_tcp_port]
,EC.[local_net_address]
,EC.[local_tcp_port]
,EC.[parent_connection_id]
,EC.[most_recent_sql_handle]
,ES.[host_process_id]
,ES.[client_version]
,ES.[client_interface_name]
,ES.[security_id]
,ES.[login_name]
,ES.[nt_domain]
,ES.[nt_user_name]
,ES.[memory_usage]
,ES.[total_scheduled_time]
,ES.[last_request_start_time]
,ES.[last_request_end_time]
,ES.[is_user_process]
,ES.[original_security_id]
,ES.[original_login_name]
,ES.[last_successful_logon]
,ES.[last_unsuccessful_logon]
,ES.[unsuccessful_logons]
,ES.[authenticating_database_id]
,ER.[sql_handle]
,ER.[statement_start_offset]
,ER.[statement_end_offset]
,ER.[plan_handle]
,NULL as [dop]--ER.[dop]
,coalesce(ER.[database_id], ES.[database_id]) as [database_id]
,ER.[user_id]
,ER.[connection_id]
from sys.dm_exec_requests ER with(readuncommitted)
right join sys.dm_exec_sessions ES with(readuncommitted)
on ES.session_id = ER.session_id
left join sys.dm_exec_connections EC with(readuncommitted)
on EC.session_id = ES.session_id
where ER.[status] in ('suspended', 'running', 'runnable')
or exists (select top(1) 1 from sys.dm_exec_requests as ER0 where ER0.[blocking_session_id]=ES.[session_id])
该请求显示所有活动请求和显式阻止活动请求的所有请求。
所有这些和其他有用的脚本都作为SRV数据库中的表示形式实现，该数据库是免费分发的。 例如，第一个脚本来自视图[inf]。[vBigQuery]，第二个来自视图[inf].[vRequests]。
对于查询历史，也有各种第三方解决方案。 我使用Dbeaver的查询管理器: 和SSMS内嵌的SQL Tools中的查询执行历史:
晚一点，但希望有用，因为它增加了更多的细节…
在默认情况下，无法查看在SSMS中执行的查询。不过也有几种选择。
读取事务日志-这不是一件容易的事情，因为它是私有格式。但是，如果您需要查看历史上执行的查询(除了SELECT)，这是唯一的方法。
您可以使用第三方工具，如ApexSQL日志和SQL日志救援(免费，但仅限SQL 2000)。查看这个线程的更多细节在这里SQL Server事务日志资源管理器/分析器
SQL Server分析器-最适合如果你只是想开始审计，你不感兴趣之前发生了什么。确保使用筛选器只选择您需要的事务。否则你很快就会得到大量的数据。
SQL Server跟踪—如果您想捕获所有或大部分命令，并将它们保存在跟踪文件中，以便稍后进行解析，则最适合。
触发器—如果您想捕获DML(除了select)并将它们存储在数据库中的某个地方，那么最适合使用它
如果需要，可以通过SQL Profiler监视SQL查询
如果您需要通过SMSS执行的查询的历史记录。
你可能想试试SSMSPlus。
https://github.com/akarzazi/SSMSPlus
这个特性在SSMS中并不是现成的。
您需要SSMS 18或更新版本。
声明:我是作者。
正如其他人所指出的，您可以使用SQL Profiler，但也可以通过sp_trace_*系统存储过程来利用它的功能。例如，这个SQL片段将(至少在2000年;我认为这对SQL 2008是一样的，但你必须仔细检查)捕获RPC:Completed和SQL:BatchCompleted事件的所有查询需要超过10秒运行，并将输出保存到一个跟踪文件，您可以在稍后的日期在SQL分析器中打开:
DECLARE @TraceID INT
DECLARE @ON BIT
DECLARE @RetVal INT
SET @ON = 1
exec @RetVal = sp_trace_create @TraceID OUTPUT, 2, N'Y:\TraceFile.trc'
print 'This trace is Trace ID = ' + CAST(@TraceID AS NVARCHAR)
print 'Return value = ' + CAST(@RetVal AS NVARCHAR)
-- 10 = RPC:Completed
exec sp_trace_setevent @TraceID, 10, 1, @ON -- Textdata
exec sp_trace_setevent @TraceID, 10, 3, @ON -- DatabaseID
exec sp_trace_setevent @TraceID, 10, 12, @ON -- SPID
exec sp_trace_setevent @TraceID, 10, 13, @ON -- Duration
exec sp_trace_setevent @TraceID, 10, 14, @ON -- StartTime
exec sp_trace_setevent @TraceID, 10, 15, @ON -- EndTime
-- 12 = SQL:BatchCompleted
exec sp_trace_setevent @TraceID, 12, 1, @ON -- Textdata
exec sp_trace_setevent @TraceID, 12, 3, @ON -- DatabaseID
exec sp_trace_setevent @TraceID, 12, 12, @ON -- SPID
exec sp_trace_setevent @TraceID, 12, 13, @ON -- Duration
exec sp_trace_setevent @TraceID, 12, 14, @ON -- StartTime
exec sp_trace_setevent @TraceID, 12, 15, @ON -- EndTime
-- Filter for duration [column 13] greater than [operation 2] 10 seconds (= 10,000ms)
declare @duration bigint
set @duration = 10000
exec sp_trace_setfilter @TraceID, 13, 0, 2, @duration
您可以从Books Online中找到每个跟踪事件、列等的ID;只需搜索sp_trace_create、sp_trace_setevent和sp_trace_setfiler sppros即可。然后，您可以像下面这样控制跟踪:
exec sp_trace_setstatus 15, 0 -- Stop the trace
exec sp_trace_setstatus 15, 1 -- Start the trace
exec sp_trace_setstatus 15, 2 -- Close the trace file and delete the trace settings
.．.其中'15'是跟踪ID(如上面的第一个脚本所删除的sp_trace_create所报告的)。
您可以查看哪些跟踪正在运行:
select * from ::fn_trace_getinfo(default)
我唯一要谨慎说的是——我不知道这会给你的系统带来多少负载;它将添加一些，但“一些”的大小可能取决于您的服务器有多忙。
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