Below are some useful Performance Tuning SQL queries. These are based on the Active Session History V$ View to get a current perspective of performance and the DBA_HIST_* AWR history tables for obtaining performance data pertaining to a period of time in the past.
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$session_wait se where s.sid=se.sid and se.event not like 'SQL*Net%' and se.event not like '%rdbms%' and s.username is not null order by se.wait_time;
Find The Main Database Wait Events In A Particular Time Interval
First determine the snapshot id values for the period in question.
In this example we need to find the SNAP_ID for the period 10 PM to 11 PM on the 22 Feb, 2023.
select snap_id,begin_interval_time,end_interval_time from dba_hist_snapshot where to_char(begin_interval_time,'DD-MON-YYYY')='22-FEB-2023' and EXTRACT(HOUR FROM begin_interval_time) between 22 and 23;
set verify off
select * from (
select active_session_history.event,
sum(active_session_history.wait_time +
active_session_history.time_waited) ttl_wait_time
from dba_hist_active_sess_history active_session_history
where event is not null
and SNAP_ID between &ssnapid and &esnapid
group by active_session_history.event
order by 2 desc)
where rownum
Top CPU Consuming SQL During A Certain Time Period
Note – in this case we are finding the Top 5 CPU intensive SQL statements executed between 9.00 AM and 11.00 AM
select * from ( select SQL_ID, sum(CPU_TIME_DELTA), sum(DISK_READS_DELTA), count(*) from DBA_HIST_SQLSTAT a, dba_hist_snapshot s where s.snap_id = a.snap_id and s.begin_interval_time > sysdate -1 and EXTRACT(HOUR FROM S.END_INTERVAL_TIME) between 9 and 11 group by SQL_ID order by sum(CPU_TIME_DELTA) desc) where rownum
Which Database Objects Experienced the Most Number of Waits in the Past One Hour
set linesize 120 col event format a40 col object_name format a40 select * from ( select dba_objects.object_name, dba_objects.object_type, active_session_history.event, sum(active_session_history.wait_time + active_session_history.time_waited) ttl_wait_time from v$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 22nd of February, 2023.
select snap_id,begin_interval_time,end_interval_time from dba_hist_snapshot where to_char(begin_interval_time,'DD-MON-YYYY')='22-FEB-2023' 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;