我在使用Oracle 10g中最常用的表時遇到了麻煩。 我正在使用Oracle 10g版本10.2.0.4.0和EBS R12.1.3應用程序。如何找出哪些表訪問最多或經常在Oracle 10g中使用
請幫我整理我的數據庫中最常用的表格。
如果可能我希望得到TableName,所有者以及它在一個時間範圍內訪問的次數。
我需要這個用於調整目的。
請提供查詢以獲得相同的結果。
在此先感謝!
我在使用Oracle 10g中最常用的表時遇到了麻煩。 我正在使用Oracle 10g版本10.2.0.4.0和EBS R12.1.3應用程序。如何找出哪些表訪問最多或經常在Oracle 10g中使用
請幫我整理我的數據庫中最常用的表格。
如果可能我希望得到TableName,所有者以及它在一個時間範圍內訪問的次數。
我需要這個用於調整目的。
請提供查詢以獲得相同的結果。
在此先感謝!
我知道2種方式,其中之一是對所有表格進行監視,然後使用該統計信息,或使用v$segment_statistics
來分析塊訪問統計信息,類似這樣,按照訪問類型表的總值顯示前50 ,您可以在查詢中提供目標架構名稱<YOURSCHEMA>
。
select *
from (select rownum RN, T.*
from (select stat.OBJECT_NAME, stat.STATISTIC_NAME, stat.VALUE AcsValue,
sum(value) over(partition by stat.OBJECT_NAME) Total
from v$segment_statistics stat
where owner = <YOURSCHEMA>
and stat.OBJECT_TYPE = 'TABLE'
and stat.STATISTIC_NAME in
('logical reads', 'pptimized physical reads',
'physical read requests', 'physical reads',
'physical reads direct', 'physical write requests',
'physical writes', 'physical writes direct')
order by sum(value) over(partition by stat.OBJECT_NAME) desc) T) TOrd
where TOrd.RN < 50
如果您需要此調整一個Oracle EBS環境,我建議從應用程序啓動或SQL,而不是表,並用段層看着它。
例如,AWR包含特定日期範圍內IO密集度最高的查詢,如DBA AWR SQL Performance Summary所示。此SQL使用的函數xxen_util.responsibility和xxen_util.apps_module可以下載here。
select
decode(:order_by,
'elapsed time',x.elapsed_time/sum(x.elapsed_time) over()*100,
'IO',x.buffer_io/sum(x.buffer_io) over()*100,
'executions',x.executions/sum(x.executions) over()*100
) percentage,
xxen_util.responsibility(x.action) responsibility,
xxen_util.apps_module(x.module) apps_module,
x.module,
x.program,
x.program_line#,
x.sql_id,
x.plan_hash_value,
(select dhst.sql_text from dba_hist_sqltext dhst where x.dbid=dhst.dbid and x.sql_id=dhst.sql_id) sql_text,
x.executions,
x.elapsed_time,
xxen_util.time(x.elapsed_time) time,
x.user_io_wait_time,
x.cpu_time,
x.plsql_exec_time,
x.concurrency_wait_time,
x.application_wait_time,
x.elapsed_time/decode(x.executions,0,null,x.executions) time_exec,
x.buffer_io,
x.disk_io,
x.buffer_io/decode(x.executions,0,null,x.executions) io_exec,
x.rows_processed/decode(x.executions,0,null,x.executions) rows_exec,
x.buffer_io/decode(x.rows_processed,0,null,x.rows_processed) io_row,
x.buffer_io/decode(x.elapsed_time,0,null,x.elapsed_time) io_sec,
case when x.executions>100 then x.buffer_io/(decode(x.last_load_time,x.first_load_time,to_date(null),x.last_load_time)-x.first_load_time)/24/3600 end io_sec_avg,
(x.buffer_io-x.disk_io)/xxen_util.zero_to_null(x.cpu_time) buffer_rate,
x.disk_io/xxen_util.zero_to_null(x.user_io_wait_time) disk_rate,
100*x.disk_io/xxen_util.zero_to_null(x.buffer_io) disk_percentage,
case when x.executions>100 then x.executions/(decode(x.last_load_time,x.first_load_time,to_date(null),x.last_load_time)-x.first_load_time)/24 end execs_per_hour,
case when x.executions>100 then 100*x.elapsed_time/(decode(x.last_load_time,x.first_load_time,to_date(null),x.last_load_time)-x.first_load_time)/24/3600 end time_percentage,
x.is_bind_sensitive,
x.is_bind_aware,
x.parsing_schema_name,
x.parse_calls,
x.first_load_time,
x.last_load_time,
x.command_type,
x.action
from
(
select /*+ cardinality(dhs 100) */ distinct
case when :aggregate_level like '% per day' then dhs.date_ end date_,
case when :aggregate_level like 'SQL%' then max(dhss.module) over (partition by dhss.sql_id, dhss.plan_hash_value) else dhss.module end module,
case when :aggregate_level like 'SQL%' then max(dhss.action) over (partition by dhss.sql_id, dhss.plan_hash_value) else dhss.action end action,
sum(dhss.elapsed_time_delta) over (partition by dhss.sql_id, dhss.plan_hash_value)/1000000 elapsed_time,
sum(dhss.iowait_delta) over (partition by dhss.sql_id, dhss.plan_hash_value)/1000000 user_io_wait_time,
sum(dhss.cpu_time_delta) over (partition by dhss.sql_id, dhss.plan_hash_value)/1000000 cpu_time,
sum(dhss.plsexec_time_delta) over (partition by dhss.sql_id, dhss.plan_hash_value)/1000000 plsql_exec_time,
sum(dhss.ccwait_delta) over (partition by dhss.sql_id, dhss.plan_hash_value)/1000000 concurrency_wait_time,
sum(dhss.apwait_delta) over (partition by dhss.sql_id, dhss.plan_hash_value)/1000000 application_wait_time,
vp.value*sum(dhss.buffer_gets_delta) over (partition by dhss.sql_id, dhss.plan_hash_value)/1000000 buffer_io,
sum(dhss.physical_read_bytes_delta) over (partition by dhss.sql_id, dhss.plan_hash_value)/1000000 disk_io,
sum(dhss.executions_delta) over (partition by dhss.sql_id, dhss.plan_hash_value) executions,
sum(dhss.rows_processed_delta) over (partition by dhss.sql_id, dhss.plan_hash_value) rows_processed,
min(dhss.parsing_schema_name) over (partition by dhss.sql_id, dhss.plan_hash_value) parsing_schema_name,
sum(dhss.parse_calls_delta) over (partition by dhss.sql_id, dhss.plan_hash_value) parse_calls,
min(dhs.begin_interval_time_) over (partition by dhss.sql_id, dhss.plan_hash_value) first_load_time,
max(dhs.end_interval_time_) over (partition by dhss.sql_id, dhss.plan_hash_value) last_load_time,
case when :aggregate_level like 'SQL%' then dhss.sql_id end sql_id,
case when :aggregate_level like 'SQL%' then dhss.plan_hash_value end plan_hash_value,
case when :aggregate_level like 'SQL%' then decode(dhst.command_type,1,'create table',2,'insert',3,'select',6,'update',7,'delete',9,'create index',11,'alter index',26,'lock table',42,'alter session',44,'commit',45,'rollback',46,'savepoint',47,'pl/sql block',48,'set transaction',50,'explain',62,'analyze table',90,'set constraints',170,'call',189,'merge','other') end command_type,
case when :aggregate_level like 'SQL%' then gsa.is_bind_sensitive end is_bind_sensitive,
case when :aggregate_level like 'SQL%' then gsa.is_bind_aware end is_bind_aware,
case when :aggregate_level like 'SQL%' then gsa.object_name end program,
case when :aggregate_level like 'SQL%' then gsa.program_line# end program_line#,
dhs.dbid
from
(
select trunc(dhs.begin_interval_time) date_,
cast(dhs.begin_interval_time as date) begin_interval_time_,
cast(dhs.end_interval_time as date) end_interval_time_,
dhs.*
from
dba_hist_snapshot dhs
) dhs,
dba_hist_sqlstat dhss,
dba_hist_sqltext dhst,
(
select
gsa.sql_id,
gsa.plan_hash_value,
gsa.is_bind_sensitive,
gsa.is_bind_aware,
do.object_name,
case when gsa.program_line#>0 then gsa.program_line# end program_line#
from
gv$sqlarea gsa,
dba_objects do
where
2=2 and
'Y'='Y' and
gsa.program_id=do.object_id(+)
) gsa,
(select vp.value from v$parameter vp where vp.name like 'db_block_size') vp
where
dhs.begin_interval_time>=:date_from and
dhst.command_type not in (47) and
1=1 and
dhs.dbid=(select vd.dbid from v$database vd) and
dhs.dbid=dhss.dbid and
dhs.instance_number=dhss.instance_number and
dhs.snap_id=dhss.snap_id and
dhss.dbid=dhst.dbid and
dhss.sql_id=dhst.sql_id and
dhss.sql_id=gsa.sql_id(+) and
dhss.plan_hash_value=gsa.plan_hash_value(+)
) x
order by
case when :aggregate_level in ('Module per day','SQL per day') then x.date_ end desc,
decode(:order_by,'elapsed time',x.elapsed_time,'IO',x.buffer_io,'executions',x.executions) desc
-- binds --
:aggregate_level = SQL
:order_by = IO
http://ulfet.blogspot.com/2015/11/list-of-most-used-tables.html – user75ponic
您確定要調整基於表被訪問的次數?如果一個表只訪問一次,但需要幾個小時的處理時間,那麼比起每秒鐘訪問一千次的表更重要嗎?在Oracle中,根據等待時間調整通常會更有幫助。很容易成爲強迫性調諧障礙的受害者,浪費時間優化不相關的查詢。你想把重點放在最重要的指標上,這通常是花在做某件事上的時間。 –