Previously I noted how I took my early steps in figuring out what Oracle was doing with my code when I ran it. My early attempts were a combination of code instrumentation and polling of v$sql to find what queries Oracle was running and when. The key limitation as far as polling goes is that it required me to be actively monitoring the process in real time. So, how can we work out what a process did after it has been executed?
Prior to Oracle 10g the answer was not easily unless you did something like run an SQL trace on the process. Oracle 10g introduced Active Session History, which changed things for process monitoring. From the Oracle 11g Release 2 documentation:
“The V$ACTIVE_SESSION_HISTORY view provides sampled session activity in the instance. Active sessions are sampled every second and are stored in a circular buffer in SGA. Any session that is connected to the database and is waiting for an event that does not belong to the Idle wait class is considered as an active session. This includes any session that was on the CPU at the time of sampling.”
So, with Active Session History (often abbreviated to ASH), Oracle samples the database every second and stores details of every session that is considered “active”, meaning that it is waiting on a non-idle wait event or is executing on a CPU. These details are exposed via the data dictionary view v$active_session_history (or gv$active_session_history if you’re operating a RAC environment).
A key detail to note is that the underlying data store for Active Session History is a circular memory buffer. Once the buffer is full then older entries are overwritten by new ones. The question that then arises is “how long will an entry remain in the buffer before being overwritten?”. Unfortunately there is no simple answer to that question as it depends on how many active sessions there have been in the database. You may find that it takes a day or more before details are overwritten or it could be a few hours or less. You can easily find out how much ASH history you have available by running the following query:
SELECT MIN(sample_time) AS min_sample_time FROM v$active_session_history
If you find that your process has aged out of Active Session History buffer then all is not quite lost. Every 10th sample from v$active_session_history is saved into the Active Workload Repository (AWR) and exposed via the view dba_hist_active_sess_history. From within v$active_session_history, you can tell which samples have been saved from the flag stored in the IS_AWR_SAMPLE column. Unfortunately, 10 second samples are rather too infrequent to obtain a good idea of what a process did.
So, assuming that your recently run process is somewhere in Active Session History, how do you go about getting its details. Well, similar to finding your process if it is currently being executed the first step is to identify the session that it’s running under. Again, there’s no single way to do this and all the suggestions for finding the process in v$session apply: find one or more attributes that you know about your session and filter the ASH data based on those. v$active_session_history has MODULE, ACTION, CLIENT_ID columns so if you’ve been making use of those (as I would encourage) then you’ll probably find it quite easy to locate the necessary session details.
Within v$active session_history the session SID is named SESSION_ID and the SERIAL# is named SESSION_SERIAL# (consistency in naming
with v$session would have been nice…). Once you’ve identified some session entries, obtained these two attributes and have an idea of when your process ran then you can quickly get all of the Active Session History details with the following query:
SELECT * FROM v$active_session_history WHERE sample_time BETWEEN :start_time and :end_time AND session_id = :session_id AND session_serial# = :session_serial# ORDER BY sample_time
Keep in mind that this query will give you an entry per second that your process was executing so there could be quite a few entries for a particularly long running process.
Analysing your process from Active Session History is quite simple once you’ve got a listing of it. The SQL_ID and SQL_CHILD_NUMBER columns give you the particular statement that executing when the sample was taken. As mentioned in the previous post, these details are sufficient to obtain the SQL statement and the execution plan used. Furthermore, Oracle 11.2 introduced the column SQL_EXEC_ID, which can be used to distinguish different executions of the same statement. This is particularly useful if your process runs the same statement frequently. Bear in mind however that it will not tell you how many times a statement has been run if your process executes it many times between the one second sample points.
The EVENT column and associated parameters are useful in determining what the process has spent time waiting on when it hasn’t been active on the CPU. However, I don’t intend to go into wait events here. You will find a listing of the various wait events in Appendix C of the Oracle Database Reference documentation.
The columns starting with BLOCKING are useful in determining if your process was blocked by another session. This can happen for various reasons, such as if another process obtained locks on rows that your process was attempting to modify. The wait event for your session will give you an idea of why your process was being blocked. You can use the blocking session details provided to re-query Active Session History to find what session was blocking your process and what it was doing.
Some other columns that I’ve found useful when using Active Session History are:
- CURRENT_OBJ# – the OBJECT_ID from the DBA_OBJECTS view of the object being referenced when the sample was taken. If this is constant across a number of samples then it can give you an idea of which area of a query Oracle is spending its time. Keep in mind that SQL monitoring may give better information in this case.
- TOP_LEVEL_SQL_ID – the SQL_ID of the top level statement that is executing, which could be the stored procedure call from the application initiating the process.
- IN_HARD_PARSE – this flags whether the process was performing a hard parse when the sample was taken. This can be useful for determining if your process is spending too much time hard parsing queries.
- SEQ# – a unique wait event identifier, which can be used to track whether a wait event is a continuation of the same event from the previous sample, i.e. the wait has lasted more than 1 second, or if it is a new wait event.
There is a wealth of information available within Active Session History and it is possible to construct all sorts of informative queries. As an example, the following query will list the SQL details of a session in the order that they executed, showing their general duration as measured by the samples:
SELECT ash.sql_id , ash.sql_child_number , s.sql_text , ash.sql_exec_start , ash.sql_exec_id , TO_CHAR(MIN(ash.sample_time),'hh24:mi:ss') AS min_sample_time , TO_CHAR(MAX(ash.sample_time),'hh24:mi:ss') AS max_sample_time FROM v$active_session_history ash , v$sql s WHERE ash.sql_id = s.sql_id (+) AND ash.sql_child_number = s.child_number (+) AND ash.session_id = :session_id AND ash.session_serial# = :session_serial# GROUP BY ash.sql_id , ash.sql_child_number , s.sql_text , ash.sql_exec_start , ash.sql_exec_id ORDER BY MIN(ash.sample_time)
When run after the following rather simplistic script:
DECLARE TYPE t_dba_extents_tab IS TABLE OF dba_extents%ROWTYPE; TYPE t_dba_objects_tab IS TABLE OF dba_objects%ROWTYPE; TYPE t_dba_users_tab IS TABLE OF dba_users%ROWTYPE; l_dba_extents_tab t_dba_extents_tab; l_dba_objects_tab t_dba_objects_tab; l_dba_users_tab t_dba_users_tab; l_sid v$session.sid%TYPE; l_serial# v$session.serial#%TYPE; BEGIN SELECT sid , serial# INTO l_sid , l_serial# FROM v$session WHERE sid = SYS_CONTEXT('userenv','sid'); dbms_output.enable(null); dbms_output.put_line ('Session ID: ' || TO_CHAR(l_sid) || ', Serial#: ' || TO_CHAR(l_serial#)); -- run a few queries in a loop so we can use up some time FOR i IN 1..5 LOOP SELECT * BULK COLLECT INTO l_dba_extents_tab FROM dba_extents ORDER BY owner , segment_name , partition_name; SELECT * BULK COLLECT INTO l_dba_objects_tab FROM dba_objects ORDER BY owner , object_type , object_name; SELECT * BULK COLLECT INTO l_dba_users_tab FROM dba_users ORDER BY username; END LOOP; END; /
the results were:
SQL_ID SQL_CHILD_NUMBER SQL_TEXT SQL_EXEC_ SQL_EXEC_ID MIN_SAMP MAX_SAMP ------------- ---------------- -------------------- --------- ----------- -------- -------- 7mb45hj1u38dk 1 SELECT * FROM DBA_EX 02-MAY-12 16777227 06:56:48 06:56:52 TENTS ORDER BY OWNER , SEGMENT_NAME , PA RTITION_NAME 5f4b3676kpnh3 1 SELECT * FROM DBA_OB 02-MAY-12 16777229 06:56:53 06:56:53 JECTS ORDER BY OWNER , OBJECT_TYPE , OBJ ECT_NAME 7mb45hj1u38dk 1 SELECT * FROM DBA_EX 02-MAY-12 16777228 06:56:54 06:56:58 TENTS ORDER BY OWNER , SEGMENT_NAME , PA RTITION_NAME 7mb45hj1u38dk 1 SELECT * FROM DBA_EX 02-MAY-12 16777229 06:56:59 06:57:03 TENTS ORDER BY OWNER , SEGMENT_NAME , PA RTITION_NAME 5f4b3676kpnh3 1 SELECT * FROM DBA_OB 02-MAY-12 16777231 06:57:04 06:57:04 JECTS ORDER BY OWNER , OBJECT_TYPE , OBJ ECT_NAME 7mb45hj1u38dk 1 SELECT * FROM DBA_EX 02-MAY-12 16777230 06:57:05 06:57:09 TENTS ORDER BY OWNER , SEGMENT_NAME , PA RTITION_NAME 7mb45hj1u38dk 1 SELECT * FROM DBA_EX 02-MAY-12 16777231 06:57:10 06:57:14 TENTS ORDER BY OWNER , SEGMENT_NAME , PA RTITION_NAME 5f4b3676kpnh3 1 SELECT * FROM DBA_OB 02-MAY-12 16777233 06:57:15 06:57:15 JECTS ORDER BY OWNER , OBJECT_TYPE , OBJ ECT_NAME
From the above we can see that the query against DBA_EXTENTS used up most of the time and that all 5 executions of it appeared in Active Session History. The query against DBA_OBJECTS shows up 3 times while the query against DBA_USERS doesn’t even appear once. This illustrates rather nicely the fact that the Active Session History details are sample based; if a query happens to be running when a sample is taken then its details get recorded, if not then it will not appear and you may not even be aware that it has been run.
So, what are the drawbacks to Active Session History? From a process monitoring perspective it is important to realise that Oracle records details of what a session is doing as at the point it takes the sample, as illustrated in the previous example. So, if in the one second since the previous sample your process has run half a dozen SQL statements then only the one that was being executed at the moment the sample was taken will be picked up. This means that for fast OLTP-type processes it is unlikely that you will obtain details of every statement issued by your process. If you require an in-depth analysis of what your process is doing then obtaining an SQL Trace might be the way to go… but this will have to be set-up prior to the execution of your process.
Probably the bigger drawback for Active Session History is that it requires the Oracle Diagnostics Pack license, which is only available for Enterprise Edition of the database. If you are using Standard Edition or Express Edition then Active Session History simply isn’t available to you.
Thanks for sharing the information and help me to clear many doubts with respect to RCA. One question, i had incident when processes and sessions were spiked in my DB and i do have all the details but i look for dba_active_session_history and v$active_session_history, my session counts are not matching. They have big difference in counts across views. What is the best way to find out the sessions and/or process details from the past incident say 2-3 days ago.
Below code outputs are not same.
col snap_id for 99999
col BEGIN_TIME form a20
col END_TIME form a20
col INST_NO form 99
col NAME form a13
col CURR_UTIL form 9999
col MAX_UTIL form 9999
col LIMIT_VAL form 9999
set lines 132
SELECT a.SNAP_ID,
TO_CHAR (b.BEGIN_INTERVAL_TIME, ‘dd-mon-yyyy hh24:mi’) BEGIN_TIME,
TO_CHAR (b.END_INTERVAL_TIME, ‘dd-mon-yyyy hh24:mi’) END_TIME,
a.INSTANCE_NUMBER INST_NO,
a.RESOURCE_NAME NAME,
a.CURRENT_UTILIZATION CURR_UTIL,
a.MAX_UTILIZATION MAX_UTIL,
a.LIMIT_VALUE LIMIT_VAL
FROM DBA_HIST_RESOURCE_LIMIT a, DBA_HIST_SNAPSHOT b
WHERE a.RESOURCE_NAME = ‘sessions’
AND b.snap_id = a.snap_id
AND b.INSTANCE_NUMBER = a.INSTANCE_NUMBER
ORDER BY b.SNAP_ID, b.INSTANCE_NUMBER;
SELECT
to_char(sample_time,’DD-MON-YYYY HH24:MI’) as Sample_Time,COUNT(*)
FROM
gv$active_session_history h,
DBA_USERS u
WHERE
to_char(sample_time,’DD-MON-YYYY HH24:MI’) BETWEEN ’21-JAN-2014 22:50′ AND ’22-JAN-2014 00:00′
AND
INST_ID=1
AND
h.user_id=u.user_id
GROUP BY to_char(sample_time,’DD-MON-YYYY HH24:MI’)
ORDER BY 1
/
ELECT
to_char(sample_time,’DD-MON-YYYY HH24:MI’) as Sample_Time,u.username,COUNT(*)
FROM
DBA_HIST_ACTIVE_SESS_HISTORY h,
DBA_USERS u
WHERE
to_char(sample_time,’DD-MON-YYYY HH24:MI’) BETWEEN ’21-JAN-2014 22:00′ AND ’21-JAN-2014 23:00′
AND
INSTANCE_NUMBER=1
AND
h.user_id=u.user_id
GROUP BY to_char(sample_time,’DD-MON-YYYY HH24:MI’),u.username
ORDER BY 1
/
Please help me to find out the cause for connection spikes.
Regards,
Pan
Hi Pan,
There will always be a difference between the GV$ACTIVE_SESSION_HISTORY view and the DBA_HIST_ACTIVE_SESS_HIST as the latter only contain every 10th entry from the former. GV$ACTIVE_SESSION_HISTORY contains the column IS_AWR_SAMPLE, which is set to ‘Y’ for the entries that make their way into DBA_HIST_ACTIVE_SESS_HIST. Adding this to your GV$ACTIVE_SESSION_HISTORY query will produce a result exactly like the DBA_HIST_ACTIVE_SESS_HIST query:
IS_AWR_SAMPLE = ‘Y’
If you had a spike in database connections rather than a spike in activity, you may get better information by querying DBA_AUDIT_TRAIL. In most databases logins are automatically audited so a query like the following may help:
SELECT os_username
, username
, userhost
, terminal
, timestamp
, action
, action_name
FROM dba_audit_trail
WHERE timestamp >= TO_TIMESTAMP(’21-JAN-2014 22:50′,’dd-MON-YYYY hh24:mi’)
AND timestamp <= TO_TIMESTAMP(’22-JAN-2014 00:00′,’dd-MON-YYYY hh24:mi’)
AND action = 100
ORDER BY
timestamp
Regards
Mark
Hi Mark,
Really Nice article, Could you please let me understand the below point from drawback’s section indetail..!
” if in the one second since the previous sample your process has run half a dozen SQL statements then only the one that was being executed at the moment the sample was taken will be picked up. This means that for fast OLTP-type processes it is unlikely that you will obtain details of every statement issued by your process.”
Does it mean, ASH will not capture the SQL statements which can be completed less than a second?
Also, could you please let me find the way to capture execution plans for all the SQL statements for period of time(ASH report)!
Thanks,
Anil
Hi Anil,
Yes, you’re correct, ASH will not capture details for a statement that is not executing precisely at its sampling point. So, suppose that we are executing a process of 100 statements and each statement takes exactly 0.1 seconds to run then ASH will contain details for just 10 of these statements.
TO see execution plans of queries from ASH you can use the dbms_xplan.display_cursor routine. TO get the plans for multiple statements you could join this to the ASH details via a lateral join:
Although be careful how many statements you seek to capture this way as the listing will be rather long.
Mark
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