Saturday, December 1, 2012

ASH and AWR Performance Tuning Scripts

ASH and AWR Performance Tuning Scripts

Ref: http://gavinsoorma.com/2012/11/ash-and-awr-performance-tuning-scripts/


Top Recent Wait Events

 col EVENT format a60

select * from (
select active_session_history.event,
sum(active_session_history.wait_time +
active_session_history.time_waited) ttl_wait_time
from v$active_session_history active_session_history
where active_session_history.event is not null
group by active_session_history.event
order by 2 desc)
where rownum < 6
/


Top Wait Events Since Instance Startup


 col event format a60

select event, total_waits, time_waited
from v$system_event e, v$event_name n
where n.event_id = e.event_id
and n.wait_class !='Idle'
and n.wait_class = (select wait_class from v$session_wait_class
 where wait_class !='Idle'
 group by wait_class having
sum(time_waited) = (select max(sum(time_waited)) from v$session_wait_class
where wait_class !='Idle'
group by (wait_class)))
order by 3;
List Of Users Currently Waiting
 col username format a12
col sid format 9999
col state format a15
col event format a50
col wait_time format 99999999
set pagesize 100
set linesize 120

select s.sid, s.username, se.event, se.state, se.wait_time
from v$session s, v$session_wait se
where s.sid=se.sid
and se.event not like 'SQL*Net%'
and se.event not like '%rdbms%'
and s.username is not null
order by se.wait_time;


Find The Main Database Wait Events In A Particular Time Interval

First determine the snapshot id values for the period in question.


In this example we need to find the SNAP_ID for the period 10 PM to 11 PM on the 14th of November, 2012.
 select snap_id,begin_interval_time,end_interval_time
from dba_hist_snapshot
where to_char(begin_interval_time,'DD-MON-YYYY')='14-NOV-2012'
and EXTRACT(HOUR FROM begin_interval_time) between 22 and 23;
set verify off
 select * from (
 select active_session_history.event,
 sum(active_session_history.wait_time +
 active_session_history.time_waited) ttl_wait_time
 from dba_hist_active_sess_history active_session_history
 where event is not null
 and SNAP_ID between &ssnapid and &esnapid
 group by active_session_history.event
 order by 2 desc)
 where rownum

Top CPU Consuming SQL During A Certain Time Period


Note – in this case we are finding the Top 5 CPU intensive SQL statements executed between 9.00 AM and 11.00 AM


 select * from (
select
SQL_ID,
 sum(CPU_TIME_DELTA),
sum(DISK_READS_DELTA),
count(*)
from
DBA_HIST_SQLSTAT a, dba_hist_snapshot s
where
s.snap_id = a.snap_id
and s.begin_interval_time > sysdate -1
and EXTRACT(HOUR FROM S.END_INTERVAL_TIME) between 9 and 11
group by
SQL_ID
order by
sum(CPU_TIME_DELTA) desc)
where rownum


Which Database Objects Experienced the Most Number of Waits in the Past One Hour


 set linesize 120
col event format a40
col object_name format a40

select * from
(
  select dba_objects.object_name,
 dba_objects.object_type,
active_session_history.event,
 sum(active_session_history.wait_time +
  active_session_history.time_waited) ttl_wait_time
from v$active_session_history active_session_history,
    dba_objects
 where
active_session_history.sample_time between sysdate - 1/24 and sysdate
and active_session_history.current_obj# = dba_objects.object_id
 group by dba_objects.object_name, dba_objects.object_type, active_session_history.event
 order by 4 desc)
where rownum < 6;
Top Segments ordered by Physical Reads
 col segment_name format a20
col owner format a10
select segment_name,object_type,total_physical_reads
 from ( select owner||'.'||object_name as segment_name,object_type,
value as total_physical_reads
from v$segment_statistics
 where statistic_name in ('physical reads')
 order by total_physical_reads desc)
 where rownum
Top 5 SQL statements in the past one hour
 select * from (
select active_session_history.sql_id,
 dba_users.username,
 sqlarea.sql_text,
sum(active_session_history.wait_time +
active_session_history.time_waited) ttl_wait_time
from v$active_session_history active_session_history,
v$sqlarea sqlarea,
 dba_users
where
active_session_history.sample_time between sysdate -  1/24  and sysdate
  and active_session_history.sql_id = sqlarea.sql_id
and active_session_history.user_id = dba_users.user_id
 group by active_session_history.sql_id,sqlarea.sql_text, dba_users.username
 order by 4 desc )
where rownum
SQL with the highest I/O in the past one day
 select * from
(
SELECT /*+LEADING(x h) USE_NL(h)*/
       h.sql_id
,      SUM(10) ash_secs
FROM   dba_hist_snapshot x
,      dba_hist_active_sess_history h
WHERE   x.begin_interval_time > sysdate -1
AND    h.SNAP_id = X.SNAP_id
AND    h.dbid = x.dbid
AND    h.instance_number = x.instance_number
AND    h.event in  ('db file sequential read','db file scattered read')
GROUP BY h.sql_id
ORDER BY ash_secs desc )
where rownum
Top CPU consuming queries since past one day
 select * from (
select
 SQL_ID,
 sum(CPU_TIME_DELTA),
 sum(DISK_READS_DELTA),
 count(*)
from
 DBA_HIST_SQLSTAT a, dba_hist_snapshot s
where
 s.snap_id = a.snap_id
 and s.begin_interval_time > sysdate -1
 group by
 SQL_ID
order by
 sum(CPU_TIME_DELTA) desc)
where rownum
Find what the top SQL was at a particular reported time of day

First determine the snapshot id values for the period in question.

In thos example we need to find the SNAP_ID for the period 10 PM to 11 PM on the 14th of November, 2012.
 select snap_id,begin_interval_time,end_interval_time
from dba_hist_snapshot
where to_char(begin_interval_time,'DD-MON-YYYY')='14-NOV-2012'
and EXTRACT(HOUR FROM begin_interval_time) between 22 and 23; select * from
 (
select
 sql.sql_id c1,
sql.buffer_gets_delta c2,
sql.disk_reads_delta c3,
sql.iowait_delta c4
 from
dba_hist_sqlstat sql,
dba_hist_snapshot s
 where
 s.snap_id = sql.snap_id
and
 s.snap_id= &snapid
 order by
 c3 desc)
 where rownum < 6
/
Analyse a particular SQL ID and see the trends for the past day
 select
 s.snap_id,
 to_char(s.begin_interval_time,'HH24:MI') c1,
 sql.executions_delta c2,
 sql.buffer_gets_delta c3,
 sql.disk_reads_delta c4,
 sql.iowait_delta c5,
sql.cpu_time_delta c6,
 sql.elapsed_time_delta c7
 from
 dba_hist_sqlstat sql,
 dba_hist_snapshot s
 where
 s.snap_id = sql.snap_id
 and s.begin_interval_time > sysdate -1
 and
sql.sql_id='&sqlid'
 order by c7
 /
Do we have multiple plan hash values for the same SQL ID – in that case may be changed plan is causing bad performance
 select
  SQL_ID
, PLAN_HASH_VALUE
, sum(EXECUTIONS_DELTA) EXECUTIONS
, sum(ROWS_PROCESSED_DELTA) CROWS
, trunc(sum(CPU_TIME_DELTA)/1000000/60) CPU_MINS
, trunc(sum(ELAPSED_TIME_DELTA)/1000000/60)  ELA_MINS
from DBA_HIST_SQLSTAT
where SQL_ID in (
'&sqlid')
group by SQL_ID , PLAN_HASH_VALUE
order by SQL_ID, CPU_MINS;
Top 5 Queries for past week based on ADDM recommendations
 /*
Top 10 SQL_ID's for the last 7 days as identified by ADDM
from DBA_ADVISOR_RECOMMENDATIONS and dba_advisor_log
*/

col SQL_ID form a16
col Benefit form 9999999999999
select * from (
select b.ATTR1 as SQL_ID, max(a.BENEFIT) as "Benefit"
from DBA_ADVISOR_RECOMMENDATIONS a, DBA_ADVISOR_OBJECTS b
where a.REC_ID = b.OBJECT_ID
and a.TASK_ID = b.TASK_ID
and a.TASK_ID in (select distinct b.task_id
from dba_hist_snapshot a, dba_advisor_tasks b, dba_advisor_log l
where a.begin_interval_time > sysdate - 7
and  a.dbid = (select dbid from v$database)
and a.INSTANCE_NUMBER = (select INSTANCE_NUMBER from v$instance)
and to_char(a.begin_interval_time, 'yyyymmddHH24') = to_char(b.created, 'yyyymmddHH24')
and b.advisor_name = 'ADDM'
and b.task_id = l.task_id
and l.status = 'COMPLETED')
and length(b.ATTR4) > 1 group by b.ATTR1
order by max(a.BENEFIT) desc) where rownum < 6;

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Sydney, NSW, Australia
An experienced IT professional (14+ years) worked in multiple industries such as consulting, education, financial, retail sectors. Carries good work experience in relational database design, analysis, modeling, development, administration, implementation, trouble shooting, support etc. Experienced in Oracle/SQL Server/MySQL DBA involving setup, configuration, tuning, backups, disaster recovery, high availability Oracle 11g/12C/19C RAC clusters; SQL server 2008/2012/2016 clusters, Oracle Engineered Systems such as EXADATA, ODA and Oracle and Azure Cloud. Performed Software Installations, Migrations, Database Capacity Planning, Automation of backup implementation, Cloud migration Tuning Oracle in windows/Unix platforms. In addition, experienced in UNIX administration, Shell scripting. PowerShell scripting A team player with communication skills.