New sql Scripts from Karen and Carlos
This commit is contained in:
Franz Rustler
parent
0dbe8613b3
commit
8d62b2f21c
25
Mortan/Rep_sql_monitor.sql
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25
Mortan/Rep_sql_monitor.sql
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@ -0,0 +1,25 @@
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SET LONG 1000000
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SET LONGCHUNKSIZE 1000000
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SET LINESIZE 1000
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SET PAGESIZE 0
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SET TRIM ON
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SET TRIMSPOOL ON
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SET ECHO OFF
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SET FEEDBACK OFF
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set termout on
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accept psqlid prompt 'Enter the sql_id: '
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define p_sql_id = '&psqlid'
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SPOOL D:\work\scripte\oracle\sql_monitor_reports\report_sql_monitor.htm
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SELECT DBMS_SQLTUNE.report_sql_monitor(
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sql_id => '&p_sql_id',
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type => 'HTML') AS report
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FROM dual;
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SPOOL OFF
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51
Mortan/awr_sqlid_perf_trend.sql
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51
Mortan/awr_sqlid_perf_trend.sql
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-- Maris Elsins / Pythian / 2013
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-- SQL performance trends from AWR
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-- Usage: @awr_sqlid_perf_trend.sql <sql_id> <number of days to report> <interval in hours>
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-- i.e. @awr_sqlid_perf_trend.sql 46ah673phw02j 2 4
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-- i.e. The example above summarizes the execution statistics for sql_id 46ah673phw02j in last 2 days breaking down the statistics by 4 hours.
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-- v1.0 - inital version
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-- v1.1 - Adding instance_number to the outputs
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set ver off pages 50000 lines 260 tab off
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undef sql_id
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undef days_history
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undef interval_hours
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def sql_id="&1"
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def days_history="&2"
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def interval_hours="&3"
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col inst for 9999
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col time for a19
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col executions for 9999999999
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col rows_processed_1exec for 9999999.999
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col elapsed_time_s_1exec for 9999999.999
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col cpu_time_s_1exec for 9999999.999
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col iowait_s_1exec for 9999999.999
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col clwait_s_1exec for 9999999.999
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col apwait_s_1exec for 9999999.999
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col ccwait_s_1exec for 9999999.999
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col plsexec_time_s_1exec for 9999999.999
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col javexec_time_s_1exec for 9999999.999
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col buffer_gets_1exec for 999999999999.999
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col disk_reads_1exec for 999999999999.999
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col direct_writes_1exec for 999999999999.999
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BREAK ON inst SKIP 1
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select hss.instance_number inst,
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to_char(trunc(sysdate-&days_history+1)+trunc((cast(hs.begin_interval_time as date)-(trunc(sysdate-&days_history+1)))*24/(&interval_hours))*(&interval_hours)/24,'dd.mm.yyyy hh24:mi:ss') time,
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sum(hss.executions_delta) executions,
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round(sum(hss.elapsed_time_delta)/1000000/decode(sum(hss.executions_delta),0,null,sum(hss.executions_delta)),3) elapsed_time_s_1exec,
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round(sum(hss.cpu_time_delta)/1000000/decode(sum(hss.executions_delta),0,null,sum(hss.executions_delta)),3) cpu_time_s_1exec,
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round(sum(hss.iowait_delta)/1000000/decode(sum(hss.executions_delta),0,null,sum(hss.executions_delta)),3) iowait_s_1exec,
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round(sum(hss.clwait_delta)/1000000/decode(sum(hss.executions_delta),0,null,sum(hss.executions_delta)),3) clwait_s_1exec,
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round(sum(hss.apwait_delta)/1000000/decode(sum(hss.executions_delta),0,null,sum(hss.executions_delta)),3) apwait_s_1exec,
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round(sum(hss.ccwait_delta)/1000000/decode(sum(hss.executions_delta),0,null,sum(hss.executions_delta)),3) ccwait_s_1exec,
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--round(sum(hss.plsexec_time_delta)/1000000/decode(sum(hss.executions_delta),0,null,sum(hss.executions_delta)),3) plsexec_time_s_1exec,
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--round(sum(hss.javexec_time_delta)/1000000/decode(sum(hss.executions_delta),0,null,sum(hss.executions_delta)),3) javexec_time_s_1exec,
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round(sum(hss.rows_processed_delta)/decode(sum(hss.executions_delta),0,null,sum(hss.executions_delta)),3) rows_processed_1exec,
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round(sum(hss.buffer_gets_delta)/decode(sum(hss.executions_delta),0,null,sum(hss.executions_delta)),3) buffer_gets_1exec,
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round(sum(hss.disk_reads_delta)/decode(sum(hss.executions_delta),0,null,sum(hss.executions_delta)),3) disk_reads_1exec,
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round(sum(hss.direct_writes_delta)/decode(sum(hss.executions_delta),0,null,sum(hss.executions_delta)),3) direct_writes_1exec
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from dba_hist_sqlstat hss, dba_hist_snapshot hs
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where hss.sql_id='&sql_id'
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and hss.snap_id=hs.snap_id
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and hs.begin_interval_time>=trunc(sysdate)-&days_history+1
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group by hss.instance_number, trunc(sysdate-&days_history+1)+trunc((cast(hs.begin_interval_time as date)-(trunc(sysdate-&days_history+1)))*24/(&interval_hours))*(&interval_hours)/24
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order by hss.instance_number,trunc(sysdate-&days_history+1)+trunc((cast(hs.begin_interval_time as date)-(trunc(sysdate-&days_history+1)))*24/(&interval_hours))*(&interval_hours)/24;
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31
Mortan/fsaj.sql
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31
Mortan/fsaj.sql
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@ -0,0 +1,31 @@
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break on sql_id on child_number on plan_hash on execs on avg_etime on avg_lio on avg_rows on sql_text
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col sql_text for a60 wrap
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set verify off
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set pagesize 999
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set lines 165
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col username format a13
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col prog format a22
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col sid format 999
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col child_number format 99999 heading CHILD
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col ocategory format a10
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col avg_etime format 9,999,999.99
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col avg_pio format 9,999,999.99
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col avg_lio format 999,999,999
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col etime format 9,999,999.99
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col join for a20
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select distinct s.sql_id, s.child_number, s.plan_hash_value plan_hash, executions execs,
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(elapsed_time/1000000)/decode(nvl(executions,0),0,1,executions) avg_etime,
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buffer_gets/decode(nvl(executions,0),0,1,executions) avg_lio,
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(rows_processed)/decode(nvl(executions,0),0,1,executions) avg_rows,
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sql_text,
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-- decode(options,'ANTI',operation||' '||options,null) join
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case when options like '%ANTI%' then operation||' '||options end join
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from v$sql s, v$sql_plan p
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where s.sql_id = p.sql_id
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and s.child_number = p.child_number
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and upper(sql_text) like upper(nvl('&sql_text','%department%'))
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and sql_text not like '%from v$sql where sql_text like nvl(%'
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and s.sql_id like nvl('&sql_id',s.sql_id)
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order by 1, 2, 3
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/
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34
Mortan/fsp.sql
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34
Mortan/fsp.sql
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@ -0,0 +1,34 @@
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break on sql_id on child_number on plan_hash on execs on avg_etime on avg_lio on avg_rows on sql_text
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col sql_text for a45 wrap
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set verify off
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set pagesize 999
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set lines 165
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col username format a13
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col prog format a22
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col sid format 999
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col child_number format 9999 heading CHILD
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col ocategory format a10
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col avg_etime format 999.99
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col avg_rows format 999,999
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col avg_lio format 99,999
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col etime format 9,999,999.99
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col execs format 9999
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col join for a20
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-- col child_no noprint
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select distinct s.sql_id, s.child_number, s.plan_hash_value plan_hash, executions execs,
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(elapsed_time/1000000)/decode(nvl(executions,0),0,1,executions) avg_etime,
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buffer_gets/decode(nvl(executions,0),0,1,executions) avg_lio,
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(rows_processed)/decode(nvl(executions,0),0,1,executions) avg_rows,
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sql_text,
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-- decode(options,'SEMI',operation||' '||options,null) join
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case when options like '%SEMI%' or options like '%ANTI%' then
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operation||' '||options end join
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from v$sql s, v$sql_plan p
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where s.sql_id = p.sql_id
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and s.child_number = p.child_number
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and upper(sql_text) like upper(nvl('&sql_text','%department%'))
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and sql_text not like '%from v$sql where sql_text like nvl(%'
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and s.sql_id like nvl('&sql_id',s.sql_id)
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order by 1, 2, 3
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/
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31
Mortan/fssj.sql
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31
Mortan/fssj.sql
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break on sql_id on child_number on plan_hash on execs on avg_etime on avg_lio on avg_rows on sql_text
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col sql_text for a60 wrap
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set verify off
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set pagesize 999
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set lines 165
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col username format a13
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col prog format a22
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col sid format 999
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col child_number format 99999 heading CHILD
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col ocategory format a10
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col avg_etime format 9,999,999.99
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col avg_pio format 9,999,999.99
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col avg_lio format 999,999,999
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col etime format 9,999,999.99
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col join for a20
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select distinct s.sql_id, s.child_number, s.plan_hash_value plan_hash, executions execs,
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(elapsed_time/1000000)/decode(nvl(executions,0),0,1,executions) avg_etime,
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buffer_gets/decode(nvl(executions,0),0,1,executions) avg_lio,
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(rows_processed)/decode(nvl(executions,0),0,1,executions) avg_rows,
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sql_text,
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-- decode(options,'SEMI',operation||' '||options,null) join
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case when options like '%SEMI%' then operation||' '||options end join
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from v$sql s, v$sql_plan p
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where s.sql_id = p.sql_id
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and s.child_number = p.child_number
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and upper(sql_text) like upper(nvl('&sql_text','%department%'))
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and sql_text not like '%from v$sql where sql_text like nvl(%'
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and s.sql_id like nvl('&sql_id',s.sql_id)
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order by 1, 2, 3
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/
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73
Mortan/one_sql_time_series.sql
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73
Mortan/one_sql_time_series.sql
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----------------------------------------------------------------------------------------
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--
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-- File name: one_sql_time_series.sql
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--
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-- Purpose: Performance History for one SQL
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--
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-- Author: Carlos Sierra
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--
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-- Version: 2014/10/31
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--
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-- Usage: Script sql_performance_changed.sql lists SQL Statements with performance
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-- improvement or regressed over some History.
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-- This script one_sql_time_series.sql lists the Performance Time Series for
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-- one SQL.
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--
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-- Parameters: SQL_ID
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--
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-- Example: @one_sql_time_series.sql
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--
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-- Notes: Developed and tested on 11.2.0.3.
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--
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-- Requires an Oracle Diagnostics Pack License since AWR data is accessed.
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--
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-- To further investigate poorly performing SQL use sqltxplain.sql or sqlhc
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-- (or planx.sql or sqlmon.sql or sqlash.sql).
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--
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---------------------------------------------------------------------------------------
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--
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SPO one_sql_time_series.txt;
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SET lin 200 ver OFF;
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COL instance_number FOR 9999 HEA 'Inst';
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COL end_time HEA 'End Time';
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COL plan_hash_value HEA 'Plan|Hash Value';
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COL executions_total FOR 999,999 HEA 'Execs|Total';
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COL rows_per_exec HEA 'Rows Per Exec';
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COL et_secs_per_exec HEA 'Elap Secs|Per Exec';
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COL cpu_secs_per_exec HEA 'CPU Secs|Per Exec';
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COL io_secs_per_exec HEA 'IO Secs|Per Exec';
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COL cl_secs_per_exec HEA 'Clus Secs|Per Exec';
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COL ap_secs_per_exec HEA 'App Secs|Per Exec';
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COL cc_secs_per_exec HEA 'Conc Secs|Per Exec';
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COL pl_secs_per_exec HEA 'PLSQL Secs|Per Exec';
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COL ja_secs_per_exec HEA 'Java Secs|Per Exec';
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SELECT h.instance_number,
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TO_CHAR(CAST(s.end_interval_time AS DATE), 'YYYY-MM-DD HH24:MI') end_time,
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h.plan_hash_value,
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h.executions_total,
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TO_CHAR(ROUND(h.rows_processed_total / h.executions_total), '999,999,999,999') rows_per_exec,
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TO_CHAR(ROUND(h.elapsed_time_total / h.executions_total / 1e6, 3), '999,990.000') et_secs_per_exec,
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TO_CHAR(ROUND(h.cpu_time_total / h.executions_total / 1e6, 3), '999,990.000') cpu_secs_per_exec,
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TO_CHAR(ROUND(h.iowait_total / h.executions_total / 1e6, 3), '999,990.000') io_secs_per_exec,
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TO_CHAR(ROUND(h.clwait_total / h.executions_total / 1e6, 3), '999,990.000') cl_secs_per_exec,
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TO_CHAR(ROUND(h.apwait_total / h.executions_total / 1e6, 3), '999,990.000') ap_secs_per_exec,
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TO_CHAR(ROUND(h.ccwait_total / h.executions_total / 1e6, 3), '999,990.000') cc_secs_per_exec,
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TO_CHAR(ROUND(h.plsexec_time_total / h.executions_total / 1e6, 3), '999,990.000') pl_secs_per_exec,
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TO_CHAR(ROUND(h.javexec_time_total / h.executions_total / 1e6, 3), '999,990.000') ja_secs_per_exec
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FROM dba_hist_sqlstat h,
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dba_hist_snapshot s
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WHERE h.sql_id = '&sql_id.'
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AND h.executions_total > 0
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AND s.snap_id = h.snap_id
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AND s.dbid = h.dbid
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AND s.instance_number = h.instance_number
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ORDER BY
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h.sql_id,
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h.instance_number,
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s.end_interval_time,
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h.plan_hash_value
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/
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SPO OFF;
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44
Mortan/parms.sql
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44
Mortan/parms.sql
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me: parms.sql
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-- Purpose: Display parameters and values.
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-
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-- Author: Kerry Osborne
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--
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-- Usage: This scripts prompts for three values, all of which can be left blank.
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--
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-- name: the name (or piece of a name) of the parameter(s) you wish to see
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--
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-- isset: "TRUE" or "T" to see only nondefault parameters
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--
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-- show_hidden: "Y" to show hidden parameters as well
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--
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---------------------------------------------------------------------------------------
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set lines 155
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col name for a50
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col value for a70
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col isdefault for a8
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col ismodified for a10
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col isset for a10
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select name, value, isdefault, ismodified, isset
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from
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(
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select flag,name,value,isdefault,ismodified,
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case when isdefault||ismodified = 'TRUEFALSE' then 'FALSE' else 'TRUE' end isset
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from
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(
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select
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decode(substr(i.ksppinm,1,1),'_',2,1) flag
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, i.ksppinm name
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, sv.ksppstvl value
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, sv.ksppstdf isdefault
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-- , decode(bitand(sv.ksppstvf,7),1,'MODIFIED',4,'SYSTEM_MOD','FALSE') ismodified
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, decode(bitand(sv.ksppstvf,7),1,'TRUE',4,'TRUE','FALSE') ismodified
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from x$ksppi i
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, x$ksppsv sv
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where i.indx = sv.indx
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)
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)
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where name like nvl('%¶meter%',name)
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and upper(isset) like upper(nvl('%&isset%',isset))
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and flag not in (decode('&show_hidden','Y',3,2))
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order by flag,replace(name,'_','')
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/
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131
Mortan/sql_performance_changed.sql
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131
Mortan/sql_performance_changed.sql
Normal file
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----------------------------------------------------------------------------------------
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--
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-- File name: sql_performance_changed.sql
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--
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-- Purpose: Lists SQL Statements with Elapsed Time per Execution changing over time
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--
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-- Author: Carlos Sierra
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--
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-- Version: 2014/10/31
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--
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-- Usage: Lists statements that have changed their elapsed time per execution over
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-- some history.
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-- Uses the ration between "elapsed time per execution" and the median of
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-- this metric for SQL statements within the sampled history, and using
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-- linear regression identifies those that have changed the most. In other
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-- words where the slope of the linear regression is larger. Positive slopes
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-- are considered "improving" while negative are "regressing".
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--
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-- Example: @sql_performance_changed.sql
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--
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-- Notes: Developed and tested on 11.2.0.3.
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--
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-- Requires an Oracle Diagnostics Pack License since AWR data is accessed.
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--
|
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-- To further investigate poorly performing SQL use sqltxplain.sql or sqlhc
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-- (or planx.sql or sqlmon.sql or sqlash.sql).
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--
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---------------------------------------------------------------------------------------
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--
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SPO sql_performance_changed.txt;
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DEF days_of_history_accessed = '31';
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DEF captured_at_least_x_times = '10';
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DEF captured_at_least_x_days_apart = '5';
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DEF med_elap_microsecs_threshold = '1e4';
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DEF min_slope_threshold = '0.1';
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DEF max_num_rows = '20';
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SET lin 200 ver OFF;
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COL row_n FOR A2 HEA '#';
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COL med_secs_per_exec HEA 'Median Secs|Per Exec';
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COL std_secs_per_exec HEA 'Std Dev Secs|Per Exec';
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COL avg_secs_per_exec HEA 'Avg Secs|Per Exec';
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COL min_secs_per_exec HEA 'Min Secs|Per Exec';
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COL max_secs_per_exec HEA 'Max Secs|Per Exec';
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COL plans FOR 9999;
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COL sql_text_80 FOR A80;
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PRO SQL Statements with "Elapsed Time per Execution" changing over time
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WITH
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per_time AS (
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SELECT h.dbid,
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h.sql_id,
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SYSDATE - CAST(s.end_interval_time AS DATE) days_ago,
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SUM(h.elapsed_time_total) / SUM(h.executions_total) time_per_exec
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FROM dba_hist_sqlstat h,
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dba_hist_snapshot s
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WHERE h.executions_total > 0
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AND s.snap_id = h.snap_id
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AND s.dbid = h.dbid
|
||||
AND s.instance_number = h.instance_number
|
||||
AND CAST(s.end_interval_time AS DATE) > SYSDATE - &&days_of_history_accessed.
|
||||
GROUP BY
|
||||
h.dbid,
|
||||
h.sql_id,
|
||||
SYSDATE - CAST(s.end_interval_time AS DATE)
|
||||
),
|
||||
avg_time AS (
|
||||
SELECT dbid,
|
||||
sql_id,
|
||||
MEDIAN(time_per_exec) med_time_per_exec,
|
||||
STDDEV(time_per_exec) std_time_per_exec,
|
||||
AVG(time_per_exec) avg_time_per_exec,
|
||||
MIN(time_per_exec) min_time_per_exec,
|
||||
MAX(time_per_exec) max_time_per_exec
|
||||
FROM per_time
|
||||
GROUP BY
|
||||
dbid,
|
||||
sql_id
|
||||
HAVING COUNT(*) >= &&captured_at_least_x_times.
|
||||
AND MAX(days_ago) - MIN(days_ago) >= &&captured_at_least_x_days_apart.
|
||||
AND MEDIAN(time_per_exec) > &&med_elap_microsecs_threshold.
|
||||
),
|
||||
time_over_median AS (
|
||||
SELECT h.dbid,
|
||||
h.sql_id,
|
||||
h.days_ago,
|
||||
(h.time_per_exec / a.med_time_per_exec) time_per_exec_over_med,
|
||||
a.med_time_per_exec,
|
||||
a.std_time_per_exec,
|
||||
a.avg_time_per_exec,
|
||||
a.min_time_per_exec,
|
||||
a.max_time_per_exec
|
||||
FROM per_time h, avg_time a
|
||||
WHERE a.sql_id = h.sql_id
|
||||
),
|
||||
ranked AS (
|
||||
SELECT RANK () OVER (ORDER BY ABS(REGR_SLOPE(t.time_per_exec_over_med, t.days_ago)) DESC) rank_num,
|
||||
t.dbid,
|
||||
t.sql_id,
|
||||
CASE WHEN REGR_SLOPE(t.time_per_exec_over_med, t.days_ago) > 0 THEN 'IMPROVING' ELSE 'REGRESSING' END change,
|
||||
ROUND(REGR_SLOPE(t.time_per_exec_over_med, t.days_ago), 3) slope,
|
||||
ROUND(AVG(t.med_time_per_exec)/1e6, 3) med_secs_per_exec,
|
||||
ROUND(AVG(t.std_time_per_exec)/1e6, 3) std_secs_per_exec,
|
||||
ROUND(AVG(t.avg_time_per_exec)/1e6, 3) avg_secs_per_exec,
|
||||
ROUND(MIN(t.min_time_per_exec)/1e6, 3) min_secs_per_exec,
|
||||
ROUND(MAX(t.max_time_per_exec)/1e6, 3) max_secs_per_exec
|
||||
FROM time_over_median t
|
||||
GROUP BY
|
||||
t.dbid,
|
||||
t.sql_id
|
||||
HAVING ABS(REGR_SLOPE(t.time_per_exec_over_med, t.days_ago)) > &&min_slope_threshold.
|
||||
)
|
||||
SELECT LPAD(ROWNUM, 2) row_n,
|
||||
r.sql_id,
|
||||
r.change,
|
||||
TO_CHAR(r.slope, '990.000MI') slope,
|
||||
TO_CHAR(r.med_secs_per_exec, '999,990.000') med_secs_per_exec,
|
||||
TO_CHAR(r.std_secs_per_exec, '999,990.000') std_secs_per_exec,
|
||||
TO_CHAR(r.avg_secs_per_exec, '999,990.000') avg_secs_per_exec,
|
||||
TO_CHAR(r.min_secs_per_exec, '999,990.000') min_secs_per_exec,
|
||||
TO_CHAR(r.max_secs_per_exec, '999,990.000') max_secs_per_exec,
|
||||
(SELECT COUNT(DISTINCT p.plan_hash_value) FROM dba_hist_sql_plan p WHERE p.dbid = r.dbid AND p.sql_id = r.sql_id) plans,
|
||||
REPLACE((SELECT DBMS_LOB.SUBSTR(s.sql_text, 80) FROM dba_hist_sqltext s WHERE s.dbid = r.dbid AND s.sql_id = r.sql_id), CHR(10)) sql_text_80
|
||||
FROM ranked r
|
||||
WHERE r.rank_num <= &&max_num_rows.
|
||||
ORDER BY
|
||||
r.rank_num
|
||||
/
|
||||
|
||||
SPO OFF;
|
||||
37
Mortan/valid_parms.sql
Normal file
37
Mortan/valid_parms.sql
Normal file
@ -0,0 +1,37 @@
|
||||
--------------------------------------------------------------------------------
|
||||
--
|
||||
-- File name: pvalid.sql
|
||||
-- Purpose: Show valid parameter values from V$PARAMETER_VALID_VALUES
|
||||
-- underlying X$ table X$KSPVLD_VALUES
|
||||
--
|
||||
-- Author: Tanel Poder
|
||||
-- Copyright: (c) http://www.tanelpoder.com
|
||||
--
|
||||
-- Modified by Kerry Osborne to prompt for value instead of using coommand line parameter.
|
||||
--
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
set lines 155
|
||||
COL pvalid_default HEAD DEFAULT FOR A7
|
||||
COL pvalid_value HEAD VALUE FOR A30
|
||||
COL pvalid_name HEAD PARAMETER FOR A50
|
||||
COL pvalid_par# HEAD PAR# FOR 99999
|
||||
|
||||
BREAK ON pvalid_par# skip 1
|
||||
|
||||
SELECT
|
||||
-- INST_ID,
|
||||
PARNO_KSPVLD_VALUES pvalid_par#,
|
||||
NAME_KSPVLD_VALUES pvalid_name,
|
||||
-- ORDINAL_KSPVLD_VALUES,
|
||||
VALUE_KSPVLD_VALUES pvalid_value,
|
||||
DECODE(ISDEFAULT_KSPVLD_VALUES, 'FALSE', '', 'DEFAULT' ) pvalid_default
|
||||
FROM
|
||||
X$KSPVLD_VALUES
|
||||
WHERE
|
||||
LOWER(NAME_KSPVLD_VALUES) LIKE '%'||LOWER(nvl('&pname',name_kspvld_values))||'%'
|
||||
ORDER BY
|
||||
pvalid_par#,
|
||||
pvalid_default,
|
||||
pvalid_Value
|
||||
/
|
||||
Loading…
x
Reference in New Issue
Block a user