Lothar,
Snapper samples from another session, generally over a short period.
The suggestion I made was relevant for a job which is known to be a
long-running task. In particular it's appropriate as a framework to put
around any regular batch-like job where you might want better explanatory
information after the event than would otherwise be available.
I wrote a note some years ago about using the strategy to explain the
variation in performance of a "constant" job:
https://jonathanlewis.wordpress.com/2007/08/09/volatility/
Regards
Jonathan Lewis
.
On Wed, 10 Apr 2024 at 17:42, Lothar Flatz <l.flatz@xxxxxxxxxx> wrote:
Hi Jonathan,
would snapper work for that purpose?
I have very little experience with snapper . I have a case where such
option would be helpfull.
Thanks
Lothar
Am 10.04.2024 um 18:32 schrieb Jonathan Lewis:
One further point, since you've probably got AWR reports over the period
you could look at the Instance Activity stats. (Ideally a special task like
this might capture the change in v$session_event, v$sess_time_model and
v$sesstat for the session). Check for the statistics for "% - undo records
applied". This can give you some clues about why the UNDO was being
accessed
transaction tables consistent reads - undo records applied
data blocks consistent reads - undo records applied
rollback changes - undo records applied
If you're restarting the the last one will show a large number. If you're
dealing with competing transactions on the same table (or its indexes) the
second will show large numbers, if you're trying to check whether "recent"
changes from other session committed before or after your transaction
started the first will show large numbers.
Regards
Jonathan Lewis
On Wed, 10 Apr 2024 at 13:35, Petr Novak <dmarc-noreply@xxxxxxxxxxxxx>
wrote:
Hallo,
there is problem with increasing execution time of simple Insert
statement.
(insert into T_TARGET select * from T_SOURCE)
Execution time increased overproportionally to increased number of rows.
11 millions rows took 3,5 hours , 38 million rows 3 days.
T_TARGET is 1,5 TB range partitioned table , 1469 partitions and 5 local
indexes (same partitioned key as the table).
for shorter execution time there was one XID, but for long execution time
4 XIDs ??
select xid, SQL_EXEC_START,SESSION_ID,SESSION_SERIAL#,count(*)
,to_char(min(sample_time),'dd.mm hh24:mi:ss') mint,
to_char(max(sample_time),'dd.mm hh24:mi:ss') maxt
from dba_hist_active_sess_history where sql_id='fdq9c3q9jfavc'
and sample_time>to_date('2404052000','yymmddhh24mi') and sample_time<
to_date('2404082100','yymmddhh24mi')
group by xid,SQL_EXEC_START,SESSION_ID,SESSION_SERIAL# order by
SQL_EXEC_START,min(sample_time);
XID SQL_EXEC_START SESSION_ID SESSION_SERIAL#
COUNT(*) Min(IntervalEnd) Max(IntervalEnd)
---------------- ------------------- -------------- ---------------
-------------- -------------------- --------------------
05.04.2024 20:13:40 1141 11657
8 05.04 20:13:44 05.04 20:14:15
2E00180051D62200 05.04.2024 20:13:40 1141 11657
12532 05.04 20:14:25 06.04 14:04:03
05.04.2024 20:13:40 1064 35873
12 05.04 20:39:31 06.04 01:42:10
05.04.2024 20:13:40 1016 54350
8 05.04 20:49:35 05.04 22:16:08
05.04.2024 20:13:40 1103 5986
16 05.04 21:00:10 06.04 02:49:36
05.04.2024 20:13:40 986 61332
6 05.04 21:34:39 06.04 04:26:03
20001C0008633B00 06.04.2024 14:04:10 1141 11657
24486 06.04 14:04:13 08.04 00:55:20
06.04.2024 14:04:10 1057 63794
6 06.04 14:08:29 07.04 01:10:29
06.04.2024 14:04:10 1026 41466
8 06.04 14:21:17 06.04 23:58:37
06.04.2024 14:04:10 1103 51053
16 06.04 14:36:49 06.04 22:38:23
15001100CD95C100 08.04.2024 00:55:22 1141 11657
8986 08.04 00:55:31 08.04 13:42:29
08.04.2024 00:55:22 1026 1396
8 08.04 00:59:06 08.04 03:59:52
08.04.2024 00:55:22 1104 28322
8 08.04 01:05:14 08.04 02:51:25
08.04.2024 00:55:22 1005 29042
8 08.04 01:21:07 08.04 03:53:02
08.04.2024 00:55:22 1075 54721
4 08.04 02:05:30 08.04 02:20:00
03001200F4F1B600 08.04.2024 13:42:30 1141 11657
4178 08.04 13:42:39 08.04 19:39:05
08.04.2024 13:42:30 325 35023
10 08.04 13:48:48 08.04 16:16:38
08.04.2024 13:42:30 296 7915
2 08.04 14:30:27 08.04 14:30:27
08.04.2024 13:42:30 369 46540
4 08.04 14:55:12 08.04 16:05:22
08.04.2024 13:42:30 395 14967
8 08.04 15:38:13 08.04 18:20:44
03001200F4F1B600 1141 11657
16 08.04 19:39:15 08.04 19:40:27
In dba_hist_undostat are same 4 execution start times for this query
(maxquerylen,maxquerysqlid).
During the execution I checked the transaction_start and last_call_et in
the session 1141 and it loooked like TX started hours later since
last_call_et. TX start was one of these SQL_EXEC_STARTs
In dba_hist_sqlstat only one execution is shown, most time was spend with
CPU.
most ASH samples are related to UNDO TS.
select tablespace_name,count(*)
from dba_hist_active_sess_history ,dba_data_files where
sql_id='fdq9c3q9jfavc'
and CURRENT_FILE#=file_id
and sample_time>to_date('2404052000','yymmddhh24mi') and sample_time<
to_date('2404082100','yymmddhh24mi')
group by tablespace_name order by count(*) desc;
TABLESPACE_NAME COUNT(*)
------------------------------ --------------
UNDOTBS1 32746
RB_STAGING_TAB 17576
There are also some intervals with increased commit times (2->100ms) ,
but for me it looks like another issue.
I have two main questions :
- how it is possible to have for one execution 4 XIDs ?
- where the statements spends the time ?
Any ideas ?
Best Regards,
Petr
