Partition List Iterator occasionally reading way too many partitions still

I’m triple posting this on oracle-l, my blog and on Oracle community to get some more help.
Apologies if you’ve tried to help before and it didn’t come to anything.

This is a redux of an old issue which I looked at 18 months ago but with a new example of the problem.
https://orastory.wordpress.com/2021/02/22/oracle-19c-upgrade-query-reading-way-more-partitions-than-it-should/
https://community.oracle.com/tech/developers/discussion/4480886/partition-list-iterator-reading-too-many-partitions/

When the problem originally surfaced it was after an upgrade from 11.2.0.4 to 19.6. Now version is 19.12.

Now I have one example which gets executed four or five times a day
The example has two sql ids involved in the process but both are almost identical and have identical sql plans.

Queries in question get executed after specific data loads.
For each data load where it gets executed, it will be doing pretty much the same workload day-on-day.
The query gets supplied a collection which tends to have one or a couple of rows row and each row in the collection provides the values to prune to a specific subpartition.

The issue is that about once a week, an execution will go slow.
Exactly the same sql plan each execution.
When it works, it runs in a couple of seconds max.
When it goes wrong, the partition list iterator decides to read every partition/subpartition.

This is the snippet of the plan in question:

|   4 |     NESTED LOOPS                          |                             |    39 |  4017 |   334   (2)| 00:00:01 |       |       |
|   5 |      COLLECTION ITERATOR PICKLER FETCH    |                             |     1 |     2 |    29   (0)| 00:00:01 |       |       |
|   6 |      PARTITION LIST ITERATOR              |                             |  3853 |   380K|   305   (2)| 00:00:01 |   KEY |   KEY |
|   7 |       PARTITION LIST ITERATOR             |                             |  3853 |   380K|   305   (2)| 00:00:01 |   KEY |   KEY |
|   8 |        TABLE ACCESS STORAGE FULL          | POSITION_BALANCE            |  3853 |   380K|   305   (2)| 00:00:01 |   KEY |   KEY |

There was some speculation about possible causes in the OTN thread.
The best guess was that there is some timeout or invalidation or event or contention which means Oracle decides that it cannot reliably prune.
There might be other data loads ongoing.
There could be a partition operation (add new or exchange) which coincides with the degraded iterator performance.
There are > 70k partitions / subpartitions.

select count(*) from dba_tab_partitions where table_name = 'POSITION_BALANCE';

  COUNT(*)
----------
     60941

select count(*), sum(case when segment_created = 'YES' then 1 else 0 end) from dba_tab_subpartitions where table_name = 'POSITION_BALANCE';

  COUNT(*) SUM(CASEWHENSEGMENT_CREATED='YES'THEN1ELSE0END)
---------- -----------------------------------------------
     78154                                           33705

I’m reasonably comfortable that what I’ve described is roughly what’s happening.
ASH confirms that it’s reading lots of subpartitions
Just got no idea why and how to figure that out.
The average-ish once-a-week occurence makes it tricker.

Even though when it runs in runs in a couple of seconds, I do have some of the ASH samples that show this.

select /*+ parallel(4) */ instance_number, sql_id, sql_plan_hash_value, sql_full_plan_hash_value, sql_exec_id, sql_exec_start, min(sample_time), max(sample_time), max(sample_time) - min(sample_time) duration, count(*) cnt_samples
, sum(case when in_sql_execution = 'Y' then 1 else 0 end) cnt_in_sql_execution
, sum(case when in_parse = 'Y' then 1 else 0 end) cnt_in_parse
, sum(case when in_hard_parse = 'Y' then 1 else 0 end) cnt_in_hard_parse
from dba_hist_active_sess_history h
where  1=1 
and h.user_id IN (select user_id from dba_users where username like '%TODS%')
and sql_id in ('fw985yayy1mfz','0gk5hj9wnp2vs')
--and sql_id = 'ft2prc1xx2hmd'
and sql_exec_id is not null
group by instance_number, sql_id, sql_plan_hash_value, sql_full_plan_hash_value, sql_exec_id, sql_exec_start
order by h.sql_exec_start;


INSTANCE_NUMBER SQL_ID        SQL_PLAN_HASH_VALUE SQL_FULL_PLAN_HASH_VALUE SQL_EXEC_ID SQL_EXEC_START       MIN(SAMPLE_TIME)                MAX(SAMPLE_TIME)                DURATION            CNT_SAMPLES CNT_IN_SQL_EXECUTION CNT_IN_PARSE CNT_IN_HARD_PARSE
--------------- ------------- ------------------- ------------------------ ----------- -------------------- ------------------------------- ------------------------------- ------------------- ----------- -------------------- ------------ -----------------
              4 0gk5hj9wnp2vs          2221895109               2867134094    67108864 23-MAY-2022 09:18:24 23-MAY-22 09.18.27.378000000 AM 23-MAY-22 09.18.27.378000000 AM +00 00:00:00.000000           1                    1            0                 0
              3 0gk5hj9wnp2vs          2221895109               2867134094    50331648 24-MAY-2022 07:59:49 24-MAY-22 07.59.50.659000000 AM 24-MAY-22 07.59.50.659000000 AM +00 00:00:00.000000           1                    1            0                 0
              2 0gk5hj9wnp2vs          2221895109               2867134094    33554432 25-MAY-2022 07:09:07 25-MAY-22 07.09.08.709000000 AM 25-MAY-22 07.09.08.709000000 AM +00 00:00:00.000000           1                    1            0                 0
              2 0gk5hj9wnp2vs          2221895109               2867134094    33554434 25-MAY-2022 09:41:53 25-MAY-22 09.41.59.718000000 AM 25-MAY-22 12.41.49.605000000 PM +00 02:59:49.887000        1054                 1054            0                 0
              2 fw985yayy1mfz          2221895109               2867134094    33554434 25-MAY-2022 10:57:41 25-MAY-22 10.57.49.221000000 AM 25-MAY-22 01.56.37.861000000 PM +00 02:58:48.640000        1048                 1048            0                 0
              3 0gk5hj9wnp2vs          2221895109               2867134094    50331648 25-MAY-2022 11:41:04 25-MAY-22 11.41.05.539000000 AM 25-MAY-22 11.41.05.539000000 AM +00 00:00:00.000000           1                    1            0                 0
              3 0gk5hj9wnp2vs          2221895109               2867134094    50331648 27-MAY-2022 08:01:28 27-MAY-22 08.01.30.371000000 AM 27-MAY-22 08.01.30.371000000 AM +00 00:00:00.000000           1                    1            0                 0
              3 fw985yayy1mfz          2221895109               2867134094    50331648 27-MAY-2022 08:01:38 27-MAY-22 08.01.40.611000000 AM 27-MAY-22 08.01.40.611000000 AM +00 00:00:00.000000           1                    1            0                 0
              1 0gk5hj9wnp2vs          2221895109               2867134094    16777218 01-JUN-2022 06:48:24 01-JUN-22 06.48.27.979000000 AM 01-JUN-22 09.48.17.547000000 AM +00 02:59:49.568000        1054                 1054            0                 0
              3 0gk5hj9wnp2vs          2221895109               2867134094    50331649 01-JUN-2022 09:27:03 01-JUN-22 09.27.10.915000000 AM 01-JUN-22 09.27.10.915000000 AM +00 00:00:00.000000           1                    1            0                 0
              3 fw985yayy1mfz          2221895109               2867134094    50331648 02-JUN-2022 07:11:55 02-JUN-22 07.11.57.315000000 AM 02-JUN-22 07.11.57.315000000 AM +00 00:00:00.000000           1                    1            0                 0
              3 0gk5hj9wnp2vs          2221895109               2867134094    50331648 07-JUN-2022 07:04:13 07-JUN-22 07.04.17.155000000 AM 07-JUN-22 07.04.17.155000000 AM +00 00:00:00.000000           1                    1            0                 0
              2 0gk5hj9wnp2vs          2221895109               2867134094    33554434 07-JUN-2022 08:17:56 07-JUN-22 08.17.58.693000000 AM 07-JUN-22 11.17.49.285000000 AM +00 02:59:50.592000        1054                 1054            0                 0
              1 0gk5hj9wnp2vs          2221895109               2867134094    16777216 08-JUN-2022 07:09:22 08-JUN-22 07.09.24.427000000 AM 08-JUN-22 07.09.24.427000000 AM +00 00:00:00.000000           1                    1            0                 0
              2 0gk5hj9wnp2vs          2221895109               2867134094    33554432 08-JUN-2022 08:14:25 08-JUN-22 08.14.26.278000000 AM 08-JUN-22 08.14.26.278000000 AM +00 00:00:00.000000           1                    1            0                 0
              3 fw985yayy1mfz          2221895109               2867134094    50331649 09-JUN-2022 06:51:27 09-JUN-22 06.51.29.219000000 AM 09-JUN-22 06.51.29.219000000 AM +00 00:00:00.000000           1                    1            0                 0
              3 fw985yayy1mfz          2221895109               2867134094    50331648 10-JUN-2022 11:10:13 10-JUN-22 11.10.14.595000000 AM 10-JUN-22 11.10.14.595000000 AM +00 00:00:00.000000           1                    1            0                 0
              2 0gk5hj9wnp2vs          2221895109               2867134094    33554433 13-JUN-2022 08:45:43 13-JUN-22 08.45.45.509000000 AM 13-JUN-22 08.45.45.509000000 AM +00 00:00:00.000000           1                    1            0                 0
              2 fw985yayy1mfz          2221895109               2867134094    33554433 13-JUN-2022 08:45:55 13-JUN-22 08.45.55.749000000 AM 13-JUN-22 08.45.55.749000000 AM +00 00:00:00.000000           1                    1            0                 0
              3 0gk5hj9wnp2vs          2221895109               2867134094    50331648 15-JUN-2022 07:08:19 15-JUN-22 07.08.22.275000000 AM 15-JUN-22 07.08.22.275000000 AM +00 00:00:00.000000           1                    1            0                 0
              3 0gk5hj9wnp2vs          2221895109               2867134094    50331649 15-JUN-2022 09:08:54 15-JUN-22 09.08.56.387000000 AM 15-JUN-22 12.08.46.083000000 PM +00 02:59:49.696000        1054                 1054            0                 0
              1 fw985yayy1mfz          2221895109               2867134094    16777216 16-JUN-2022 06:54:04 16-JUN-22 06.54.05.259000000 AM 16-JUN-22 06.54.05.259000000 AM +00 00:00:00.000000           1                    1            0                 0
              1 0gk5hj9wnp2vs          2221895109               2867134094    16777217 16-JUN-2022 08:54:13 16-JUN-22 08.54.18.891000000 AM 16-JUN-22 11.54.08.844000000 AM +00 02:59:49.953000        1054                 1054            0                 0
              3 fw985yayy1mfz          2221895109               2867134094    50331649 16-JUN-2022 11:16:29 16-JUN-22 11.16.31.491000000 AM 16-JUN-22 11.16.31.491000000 AM +00 00:00:00.000000           1                    1            0                 0
              4 0gk5hj9wnp2vs          2221895109               2867134094    67108865 17-JUN-2022 07:33:10 17-JUN-22 07.33.11.282000000 AM 17-JUN-22 07.33.11.282000000 AM +00 00:00:00.000000           1                    1            0                 0
              4 fw985yayy1mfz          2221895109               2867134094    67108865 17-JUN-2022 07:33:20 17-JUN-22 07.33.21.522000000 AM 17-JUN-22 07.33.21.522000000 AM +00 00:00:00.000000           1                    1            0                 0
              2 0gk5hj9wnp2vs          2221895109               2867134094    33554432 21-JUN-2022 06:59:24 21-JUN-22 06.59.25.728000000 AM 21-JUN-22 06.59.25.728000000 AM +00 00:00:00.000000           1                    1            0                 0
              2 0gk5hj9wnp2vs          2221895109               2867134094    33554433 21-JUN-2022 09:14:05 21-JUN-22 09.14.10.464000000 AM 21-JUN-22 12.14.00.096000000 PM +00 02:59:49.632000        1054                 1054            0                 0
              2 0gk5hj9wnp2vs          2221895109               2867134094    33554434 21-JUN-2022 11:07:36 21-JUN-22 11.07.44.480000000 AM 21-JUN-22 02.07.23.680000000 PM +00 02:59:39.200000        1053                 1053            0                 0
              4 fw985yayy1mfz          2221895109               2867134094    67108865 21-JUN-2022 11:43:04 21-JUN-22 11.43.13.010000000 AM 21-JUN-22 02.42.33.651000000 PM +00 02:59:20.641000        1051                 1051            0                 0
              4 fw985yayy1mfz          2221895109               2867134094    67108866 21-JUN-2022 12:06:49 21-JUN-22 12.06.57.586000000 PM 21-JUN-22 03.06.38.514000000 PM +00 02:59:40.928000        1053                 1053            0                 0
              3 fw985yayy1mfz          2221895109               2867134094    50331649 23-JUN-2022 10:05:02 23-JUN-22 10.05.05.667000000 AM 23-JUN-22 01.04.45.251000000 PM +00 02:59:39.584000        1053                 1053            0                 0
              1 0gk5hj9wnp2vs          2221895109               2867134094    16777216 23-JUN-2022 10:57:04 23-JUN-22 10.57.04.857000000 AM 23-JUN-22 10.57.04.857000000 AM +00 00:00:00.000000           1                    1            0                 0

This is a section of a RTSM report when it was ok:

Status                                 :  DONE (ALL ROWS)                                    
 SQL ID                                 :  0gk5hj9wnp2vs                                      
 SQL Execution ID                       :  16777216                                           
 Execution Started                      :  06/15/2022 10:45:41                                
 First Refresh Time                     :  06/15/2022 10:45:44                                
 Last Refresh Time                      :  06/15/2022 10:45:44   

SQL Plan Monitoring Details (Plan Hash Value=2221895109)
===============================================================================================================================================================================================
| Id |                  Operation                  |            Name             |  Rows   | Cost |   Time    | Start  | Execs |   Rows   | Read | Read  |  Mem  | Activity | Activity Detail |
|    |                                             |                             | (Estim) |      | Active(s) | Active |       | (Actual) | Reqs | Bytes | (Max) |   (%)    |   (# samples)   |
===============================================================================================================================================================================================
|  0 | SELECT STATEMENT                            |                             |         |      |         1 |     +3 |     1 |     2255 |      |       |     . |          |                 |
|  1 |   TEMP TABLE TRANSFORMATION                 |                             |         |      |         1 |     +3 |     1 |     2255 |      |       |     . |          |                 |
|  2 |    LOAD AS SELECT (CURSOR DURATION MEMORY)  | SYS_TEMP_5FD9DBC0F_97EDDA7B |         |      |         1 |     +3 |     1 |        1 |      |       |   1MB |          |                 |
|  3 |     FILTER                                  |                             |         |      |         1 |     +3 |     1 |     2255 |      |       |     . |          |                 |
|  4 |      NESTED LOOPS                           |                             |      39 |  713 |         1 |     +3 |     1 |     243K |      |       |     . |          |                 |
|  5 |       COLLECTION ITERATOR PICKLER FETCH     |                             |       1 |   29 |         1 |     +3 |     1 |        4 |      |       |     . |          |                 |
|  6 |       PARTITION LIST ITERATOR               |                             |    3853 |  684 |         1 |     +3 |     4 |     243K |      |       |     . |          |                 |
|  7 |        PARTITION LIST ITERATOR              |                             |    3853 |  684 |         1 |     +3 |     4 |     243K |      |       |     . |          |                 |
|  8 |         TABLE ACCESS STORAGE FULL           | POSITION_BALANCE            |    3853 |  684 |         1 |     +3 |     4 |     243K |   71 |  33MB |     . |          |                 |
|  9 |      NESTED LOOPS                           |                             |       1 |    9 |         1 |     +3 | 67382 |      140 |      |       |     . |          |                 |
| 10 |       NESTED LOOPS                          |                             |       1 |    7 |         1 |     +3 | 67382 |      140 |      |       |     . |          |                 |
| 11 |        NESTED LOOPS                         |                             |       1 |    3 |         1 |     +3 | 67382 |    67382 |      |       |     . |          |                 |
| 12 |         TABLE ACCESS BY INDEX ROWID         | CLASS_SCHEME                |       1 |    1 |         2 |     +2 | 67382 |    67382 |      |       |     . |          |                 |
| 13 |          INDEX UNIQUE SCAN                  | UK_CLASS_SCHEME_CODE        |       1 |      |         1 |     +3 | 67382 |    67382 |      |       |     . |          |                 |
| 14 |         TABLE ACCESS BY INDEX ROWID BATCHED | CLASS                       |       1 |    2 |         1 |     +3 | 67382 |    67382 |      |       |     . |          |                 |
| 15 |          INDEX RANGE SCAN                   | UK_CLASS_STATUS2            |       1 |    1 |         1 |     +3 | 67382 |    67382 |      |       |     . |          |                 |
| 16 |        TABLE ACCESS BY INDEX ROWID BATCHED  | BOOK_CLASS                  |       1 |    4 |         1 |     +3 | 67382 |      140 |      |       |     . |          |                 |
| 17 |         INDEX RANGE SCAN                    | UK_BOOK_CLASS_STATUS2       |       2 |    2 |         1 |     +3 | 67382 |     336K |  230 |   2MB |     . |          |                 |
| 18 |       INDEX RANGE SCAN                      | IDX_BOOK_STATUS_01          |       1 |    2 |         1 |     +3 |   140 |      140 |      |       |     . |          |                 |
| 19 |    VIEW                                     |                             |       1 |    2 |         1 |     +3 |     1 |     2255 |      |       |     . |          |                 |
| 20 |     TABLE ACCESS STORAGE FULL               | SYS_TEMP_5FD9DBC0F_97EDDA7B |       1 |    2 |           |        |     1 |          |      |       |     . |          |                 |
===============================================================================================================================================================================================

This is a section taken whilst running in the middle of the problem:

Status                                 :  EXECUTING                                          
 SQL ID                                 :  0gk5hj9wnp2vs                                      
 SQL Execution ID                       :  33554434                                           
 Execution Started                      :  06/21/2022 11:07:36                                
 First Refresh Time                     :  06/21/2022 11:07:41                                
 Last Refresh Time                      :  06/21/2022 13:55:15   

SQL Plan Monitoring Details (Plan Hash Value=2221895109)
================================================================================================================================================================================================================================
| Id   |                  Operation                  |            Name             |  Rows   | Cost |   Time    | Start  | Execs |   Rows   | Read | Read  | Mem | Activity |            Activity Detail            | Progress |
|      |                                             |                             | (Estim) |      | Active(s) | Active |       | (Actual) | Reqs | Bytes |     |   (%)    |              (# samples)              |          |
================================================================================================================================================================================================================================
|    0 | SELECT STATEMENT                            |                             |         |      |           |        |       |          |      |       |   . |          |                                       |          |
|    1 |   TEMP TABLE TRANSFORMATION                 |                             |         |      |           |        |       |          |      |       |   . |          |                                       |          |
|    2 |    LOAD AS SELECT (CURSOR DURATION MEMORY)  | SYS_TEMP_0FD9E59B6_25BEB636 |         |      |           |        |     1 |          |      |       |   . |          |                                       |          |
|    3 |     FILTER                                  |                             |         |      |           |        |     1 |          |      |       |   . |          |                                       |          |
|    4 |      NESTED LOOPS                           |                             |      39 |  710 |         1 |     +5 |     1 |        0 |      |       |   . |          |                                       |          |
| -> 5 |       COLLECTION ITERATOR PICKLER FETCH     |                             |       1 |   29 |     10061 |     +5 |     1 |        1 |      |       |   . |          |                                       |          |
|    6 |       PARTITION LIST ITERATOR               |                             |    3853 |  681 |           |        |     1 |          |      |       |   . |          |                                       |          |
|    7 |        PARTITION LIST ITERATOR              |                             |    3853 |  681 |           |        | 38175 |          |      |       |   . |          |                                       |          |
| -> 8 |         TABLE ACCESS STORAGE FULL           | POSITION_BALANCE            |    3853 |  681 |     10065 |     +1 | 44021 |        0 | 625K | 162GB |   . |   100.00 | gc cr block remote read (1)           |     100% |
|      |                                             |                             |         |      |           |        |       |          |      |       |     |          | gc cr grant 2-way (26)                |          |
|      |                                             |                             |         |      |           |        |       |          |      |       |     |          | gc cr multi block request (85)        |          |
|      |                                             |                             |         |      |           |        |       |          |      |       |     |          | gc current grant 2-way (1)            |          |
|      |                                             |                             |         |      |           |        |       |          |      |       |     |          | Cpu (7530)                            |          |
|      |                                             |                             |         |      |           |        |       |          |      |       |     |          | cell multiblock physical read (1946)  |          |
|      |                                             |                             |         |      |           |        |       |          |      |       |     |          | cell single block physical read (215) |          |
|      |                                             |                             |         |      |           |        |       |          |      |       |     |          | cell smart table scan (15)            |          |
|    9 |      NESTED LOOPS                           |                             |       1 |    9 |           |        |       |          |      |       |   . |          |                                       |          |
|   10 |       NESTED LOOPS                          |                             |       1 |    7 |           |        |       |          |      |       |   . |          |                                       |          |
|   11 |        NESTED LOOPS                         |                             |       1 |    3 |           |        |       |          |      |       |   . |          |                                       |          |
|   12 |         TABLE ACCESS BY INDEX ROWID         | CLASS_SCHEME                |       1 |    1 |           |        |       |          |      |       |   . |          |                                       |          |
|   13 |          INDEX UNIQUE SCAN                  | UK_CLASS_SCHEME_CODE        |       1 |      |           |        |       |          |      |       |   . |          |                                       |          |
|   14 |         TABLE ACCESS BY INDEX ROWID BATCHED | CLASS                       |       1 |    2 |           |        |       |          |      |       |   . |          |                                       |          |
|   15 |          INDEX RANGE SCAN                   | UK_CLASS_STATUS2            |       1 |    1 |           |        |       |          |      |       |   . |          |                                       |          |
|   16 |        TABLE ACCESS BY INDEX ROWID BATCHED  | BOOK_CLASS                  |       1 |    4 |           |        |       |          |      |       |   . |          |                                       |          |
|   17 |         INDEX RANGE SCAN                    | UK_BOOK_CLASS_STATUS2       |       2 |    2 |           |        |       |          |      |       |   . |          |                                       |          |
|   18 |       INDEX RANGE SCAN                      | IDX_BOOK_STATUS_01          |       1 |    2 |           |        |       |          |      |       |   . |          |                                       |          |
|   19 |    VIEW                                     |                             |       1 |    2 |           |        |       |          |      |       |   . |          |                                       |          |
|   20 |     TABLE ACCESS STORAGE FULL               | SYS_TEMP_0FD9E59B6_25BEB636 |       1 |    2 |           |        |       |          |      |       |   . |          |                                       |          |
================================================================================================================================================================================================================================

Potentially I could set system level trace for this sql id and wait for it to reoccur but what events would I be setting to try to capture what causes this runtime decision?
I presume it wouldn’t be an optimizer trace?

Any thoughts or ideas?

Reluctant Local Index

I have a couple of performance issues at the moment which link back to queries against large tables choosing to do a FULL segment scan rather than using a non-prefixed local index.

The problems right now are not currently reproducible in or outside of production.

But when I look at a specific point in time at the reproduction of a problem, the system state is not necessarily as it was when the problem was occurring.

My main theory is that somewhere on these large partitioned tables there is intermittently an unusable partition of the index perhaps due some aspect of a data load, data movement or other maintenance operation on a different subpartition (where each partition represents a different day of a specific feed and each subpartition represents a version of that daily load).

However I have no evidence currently to support that theory.

If this theory was in the right ballpark, what would it mean?

That a query using bind variables (tick) would not use the index by default as the optimizer would not be able to guarantee that that shareable plan would not be accessing the unusable.

A query using literals would not be subject to the same restrictions as the optimizer would know, if an unusable subpartition was relevant, that the unusable subpartition was not relevant to this specific query (and any DDL which might make a relevant partition unusable would invalidate the shared cursor).

Whilst I was musing over this yesterday, I had a vague sense of familiarity and I found these previous posts to job my memory:

Unusable unique constraint

An example of where the optimizer should ignore a hint

But just to illustrate my theory…

Let’s start with a roughly representative table:

create table  t1
(pkey         varchar2(24) not null
,spkey        number       not null
,id           varchar2(24) not null
,version      number       not null
,status       varchar2(24) not null
,filler       varchar2(255))
partition by list (pkey)
subpartition by list (spkey)
subpartition template
(subpartition sp_1 values (1))
(partition p_0 values ('X'));

alter table t1 add partition p_abc values ('ABC');
alter table t1 add partition p_def values ('DEF');
alter table t1 add partition p_ghi values ('GHI');

create index i1 on t1 (id) local;

create sequence s1 start with 10000000;
create type o1 is object
(pkey  varchar2(24)
,spkey        number
,id           varchar2(24));
/
create type c1 is table of o1;
/

select object_name, subobject_name, object_type from user_objects where object_name = 'T1' order by object_name, subobject_name nulls first;

OBJECT_NAM SUBOBJECT_ OBJECT_TYPE            
---------- ---------- -----------------------
T1                    TABLE                  
T1         P_0        TABLE PARTITION        
T1         P_0_SP_1   TABLE SUBPARTITION     
T1         P_ABC      TABLE PARTITION        
T1         P_ABC_SP_1 TABLE SUBPARTITION     
T1         P_DEF      TABLE PARTITION        
T1         P_DEF_SP_1 TABLE SUBPARTITION     
T1         P_GHI      TABLE PARTITION        
T1         P_GHI_SP_1 TABLE SUBPARTITION    

select object_name, subobject_name, object_type from user_objects where object_name = 'I1' order by object_name, subobject_name nulls first;

OBJECT_NAM SUBOBJECT_ OBJECT_TYPE            
---------- ---------- -----------------------
I1                    INDEX                  
I1         P_0        INDEX PARTITION        
I1         P_0_SP_1   INDEX SUBPARTITION     
I1         P_ABC      INDEX PARTITION        
I1         P_ABC_SP_1 INDEX SUBPARTITION     
I1         P_DEF      INDEX PARTITION        
I1         P_DEF_SP_1 INDEX SUBPARTITION     
I1         P_GHI      INDEX PARTITION        
I1         P_GHI_SP_1 INDEX SUBPARTITION     

And I’m going to seed some data simply:

declare
 p sys.odcivarchar2list := sys.odcivarchar2list('ABC','DEF','GHI');
begin
 for i in 1 .. p.count
 loop
     for j in 1 .. 10000
     loop
         insert into t1
         values (p(i), 1, 'PB:'||s1.nextval, 1, 'LATEST', rpad('X',255,'X'));
     end loop;
 end loop;
commit;
end;
/

select pkey, spkey, count(*), min(id), max(id) from t1 group by pkey, spkey;

PKEY      SPKEY   COUNT(*) MIN(ID)                  MAX(ID)                 
---- ---------- ---------- ------------------------ ------------------------
ABC           1      10000 PB:10000000              PB:10009999             
DEF           1      10000 PB:10010000              PB:10019999             
GHI           1      10000 PB:10020000              PB:10029999    

And then just to keep it representative to my real world problem, I’m going to run a bulk update to set the status of some of the rows to SUPERSEDED (and which is then in the real world followed by the INSERT of some LATEST versions of those rows supplied by the client but no need to do that here):

declare
 v1 c1 := c1(o1('DEF',1,'PB:10010001'),
             o1('DEF',1,'PB:10010002'),
             o1('DEF',1,'PB:10010003'),
             o1('DEF',1,'PB:10010004'),
             o1('DEF',1,'PB:10010005'));
begin
   forall i in 1 .. v1.count
      update /*+ find_me_dom */
             t1
      set    status = 'SUPERSEDED'
      where  pkey   = v1(i).pkey
      and    spkey  = v1(i).spkey
      and    id     = v1(i).id;
end;
/

And I’m going to lookup my sql id from v$sql and plug it into DBMS_XPLAN to see how my UPDATE performed:

select * from table(dbms_xplan.display_cursor('bjddz8c4jrk3y',0));

-------------------------------------------------------------
| Id  | Operation                                    | Name |
-------------------------------------------------------------
|   0 | UPDATE STATEMENT                             |      |
|   1 |  UPDATE                                      | T1   |
|   2 |   PARTITION LIST SINGLE                      |      |
|   3 |    PARTITION LIST SINGLE                     |      |
|   4 |     TABLE ACCESS BY LOCAL INDEX ROWID BATCHED| T1   |
|   5 |      INDEX RANGE SCAN                        | I1   |
-------------------------------------------------------------

Range Scan of I1 as desired

Now I will mark one subpartition of the index unusable (different subpartition from one affected by the update) and repeat the update, the getting of the SQL and the fetching of the plan (different child number):

alter index i1 modify subpartition P_ABC_SP_1 unusable;
--Repeat dml
--lookup sql

select * from table(dbms_xplan.display_cursor('bjddz8c4jrk3y',1));
-- ^ different child cursor number because marking the index subpartition as unusable
-- has invalidated the previous child cursor 0

---------------------------------------------
| Id  | Operation                    | Name |
---------------------------------------------
|   0 | UPDATE STATEMENT             |      |
|   1 |  UPDATE                      | T1   |
|   2 |   PARTITION LIST SINGLE      |      |
|   3 |    PARTITION LIST SINGLE     |      |
|   4 |     TABLE ACCESS STORAGE FULL| T1   |
---------------------------------------------

The access method is no longer an index range scan.

As I covered initially, as part of the parse process the execution plan has to be good for all possible ranges of supplied values in the event that that SQL child cursor is shared for executions with different binds than those initially parsed with. Because an update (or select etc, etc) against rows for table subpartition (ABC,1) cannot use the index because that index subpartition is unusable, the optimizer has to discount it.

We can force the index:

declare
 v1 c1 := c1(o1('DEF',1,'PB:10010001'),
             o1('DEF',1,'PB:10010002'),
             o1('DEF',1,'PB:10010003'),
             o1('DEF',1,'PB:10010004'),
             o1('DEF',1,'PB:10010005'));
begin
   forall i in 1 .. v1.count
      update /*+ find_me_dom index(t1 (id))*/
             t1
      set    status = 'SUPERSEDED'
      where  pkey   = v1(i).pkey
      and    spkey  = v1(i).spkey
      and    id     = v1(i).id;
end;
/

select * from table(dbms_xplan.display_cursor('3m2xyxgruxkpr',0));

-------------------------------------------------------------
| Id  | Operation                                    | Name |
-------------------------------------------------------------
|   0 | UPDATE STATEMENT                             |      |
|   1 |  UPDATE                                      | T1   |
|   2 |   PARTITION LIST SINGLE                      |      |
|   3 |    PARTITION LIST SINGLE                     |      |
|   4 |     TABLE ACCESS BY LOCAL INDEX ROWID BATCHED| T1   |
|   5 |      INDEX RANGE SCAN                        | I1   |
-------------------------------------------------------------

But note, as covered in my earlier link, if we force the index in a situation where it can’t be used, it will error in current versions:

alter index i1 modify subpartition P_DEF_SP_1 unusable;
declare
 v1 c1 := c1(o1('DEF',1,'PB:10010001'),
             o1('DEF',1,'PB:10010002'),
             o1('DEF',1,'PB:10010003'),
             o1('DEF',1,'PB:10010004'),
             o1('DEF',1,'PB:10010005'));
begin
   forall i in 1 .. v1.count
      update /*+ find_me_dom index(t1 (id))*/
             t1
      set    status = 'SUPERSEDED'
      where  pkey   = v1(i).pkey
      and    spkey  = v1(i).spkey
      and    id     = v1(i).id;
end;
/
ORA-01502: index 'DOM.I1' or partition of such index is in unusable state
ORA-06512: at line 8
01502. 00000 -  "index '%s.%s' or partition of such index is in unusable state"
*Cause:    An attempt has been made to access an index or index partition
           that has been marked unusable by a direct load or by a DDL
           operation
*Action:   DROP the specified index, or REBUILD the specified index, or
           REBUILD the unusable index partition

If I rebuild that second partition again, then I can look at my second option – using literals not binds, at least for the partition keys, but really we then lose the option of FORALL.

alter index i1 rebuild subpartition P_DEF_SP_1;

declare
 v1 c1 := c1(o1('DEF',1,'PB:10010001'),
             o1('DEF',1,'PB:10010002'),
             o1('DEF',1,'PB:10010003'),
             o1('DEF',1,'PB:10010004'),
             o1('DEF',1,'PB:10010005'));
begin
   for i in 1 .. v1.count
   loop
     execute immediate 
     'update /*+ find_me_dom */
             t1
      set    status = ''SUPERSEDED''
      where  pkey   = '''||v1(i).pkey||''''||'
      and    spkey  = '||v1(i).spkey||'
      and    id     = :1' using v1(i).id;
   end loop;
end;
/


select * from table(dbms_xplan.display_cursor('5a3vcac58x32q',0));

----------------------------------------
| Id  | Operation               | Name |
----------------------------------------
|   0 | UPDATE STATEMENT        |      |
|   1 |  UPDATE                 | T1   |
|   2 |   PARTITION LIST SINGLE |      |
|   3 |    PARTITION LIST SINGLE|      |
|   4 |     INDEX RANGE SCAN    | I1   |
----------------------------------------

At least we have options whilst playing a waiting game to see if we can observe a problem state which might cause such an issue…. or wait for other possibilities to make themselves known…

Performance Issue with inline view, UNION ALL and Virtual Column

This is the distillation of a performance problem in some regulatory reporting where a mistake in the optimizer cardinality estimates causes all sorts of knock-on performance issues. This post does not look at those knock-on effects but examines what is happening with the optimizer in this case. Most of the digging in the issue belongs to Valerii Satybaldyev and thanks to Sayan Malakshinov, notably for the contributions on the oracle-l thread.

Script to reproduce (currently on 19.6):

drop table t1;


create table t1
(id            number not null
,version       number not null
,create_ts     timestamp not null
,modify_ts     timestamp
,status        varchar2(24) generated always as (NVL2("MODIFY_TS",'SUPERSEDED','LATEST'))
,id2           number not null
,yn            varchar2(1) not null
,business_date date not null);

insert into t1
(id, version, create_ts, id2, yn, business_date)
select rownum
,      1
,      systimestamp
,      rownum
,      case when mod(rownum,2) = 1 then 'Y' else 'N' end
,      trunc(sysdate,'MON') + mod(rownum,10)
from   dual
connect by level <= 1000;

exec dbms_stats.gather_table_stats(USER,'T1');
 

explain plan for
with x as
(select * from t1
 union all
 select * from t1)
select *
from x
where yn = 'Y';

select * from table(dbms_xplan.display);

The problem comes with the estimate of 1 row in the outermost SELECT, particularly for subsequent joins this cardinality estimate causes significant performance problems.

------------------------------------------------------------------------------------
| Id  | Operation                   | Name | Rows  | Bytes | Cost (%CPU)| Time     |
------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT            |      |     1 |    42 |   547   (0)| 00:00:01 |
|   1 |  VIEW                       |      |  1000 | 40000 |   548   (0)| 00:00:01 |
|   2 |   UNION-ALL                 |      |       |       |            |          |
|*  3 |    TABLE ACCESS STORAGE FULL| T1   |   500 | 20000 |   274   (0)| 00:00:01 |
|*  4 |    TABLE ACCESS STORAGE FULL| T1   |   500 | 20000 |   274   (0)| 00:00:01 |
------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------
   3 - storage("T1"."YN"='Y')
       filter("T1"."YN"='Y')
   4 - storage("T1"."YN"='Y')
       filter("T1"."YN"='Y')

If we look at the 10053 trace, we can see the root cause of the problem.
Compare the BASE STATISTICAL INFORMATION snippets for T1 and for the inline view X.
Note in particular the numbers for column YN which is the predicate as well as for ID2 and BUSINESS_DATE.
Note that these are columns which appear after the virtual column STATUS.
(in the original trace file, the entry under T1 for column #8 comes before column #7, I have reordered below just to make the correlation between T1 and X more obvious)

Table Stats::
  Table: T1  Alias: T1
  #Rows: 1000  SSZ: 0  LGR: 0  #Blks:  1006  AvgRowLen:  40.00  NEB: 0  ChainCnt:  0.00  ScanRate:  0.00  SPC: 0  RFL: 0  RNF: 0  CBK: 0  CHR: 0  KQDFLG: 1
  #IMCUs: 0  IMCRowCnt: 0  IMCJournalRowCnt: 0  #IMCBlocks: 0  IMCQuotient: 0.000000
  Column (#8): BUSINESS_DATE(DATE)
    AvgLen: 8 NDV: 10 Nulls: 0 Density: 0.100000 Min: 2459336.000000 Max: 2459345.000000
  Column (#7): YN(VARCHAR2)
    AvgLen: 2 NDV: 2 Nulls: 0 Density: 0.500000
  Column (#6): ID2(NUMBER)
    AvgLen: 4 NDV: 1000 Nulls: 0 Density: 0.001000 Min: 1.000000 Max: 1000.000000
  Column (#4): MODIFY_TS(TIMESTAMP)
    AvgLen: 1 NDV: 0 Nulls: 1000 Density: 0.000000
  Column (#3): CREATE_TS(TIMESTAMP)
    AvgLen: 11 NDV: 1 Nulls: 0 Density: 1.000000 Min: 2459347.407141 Max: 2459347.407141
  Column (#2): VERSION(NUMBER)
    AvgLen: 3 NDV: 1 Nulls: 0 Density: 1.000000 Min: 1.000000 Max: 1.000000
  Column (#1): ID(NUMBER)
    AvgLen: 4 NDV: 1000 Nulls: 0 Density: 0.001000 Min: 1.000000 Max: 1000.000000

Table Stats::
  Table:  X  Alias:  X  (NOT ANALYZED)
  #Rows: 2000  SSZ: 0  LGR: 0  #Blks:  2012  AvgRowLen:  40.00  NEB: 0  ChainCnt:  0.00  ScanRate:  0.00  SPC: 0  RFL: 0  RNF: 0  CBK: 0  CHR: 0  KQDFLG: 1
  #IMCUs: 0  IMCRowCnt: 0  IMCJournalRowCnt: 0  #IMCBlocks: 0  IMCQuotient: 0.000000
  Column (#8): BUSINESS_DATE(DATE)  NO STATISTICS (using defaults)
    AvgLen: 7 NDV: 0 Nulls: 0 Density: 0.000000
  Column (#7): YN(VARCHAR2)
    AvgLen: 8 NDV: 10 Nulls: 0 Density: 0.100000 Min: 2459336.000000 Max: 2459345.000000
  Column (#6): ID2(NUMBER)
    AvgLen: 2 NDV: 2 Nulls: 0 Density: 0.500000
  Column (#5): STATUS(VARCHAR2)
    AvgLen: 4 NDV: 1000 Nulls: 0 Density: 0.001000 Min: 1.000000 Max: 1000.000000
  Column (#4): MODIFY_TS(TIMESTAMP)
    AvgLen: 1 NDV: 0 Nulls: 2000 Density: 0.000000 Min: 0.000000 Max: 0.000000
  Column (#3): CREATE_TS(TIMESTAMP)
    AvgLen: 11 NDV: 1 Nulls: 0 Density: 1.000000 Min: 2459347.407141 Max: 2459347.407141
  Column (#2): VERSION(NUMBER)
    AvgLen: 3 NDV: 1 Nulls: 0 Density: 1.000000 Min: 1.000000 Max: 1.000000
  Column (#1): ID(NUMBER)
    AvgLen: 4 NDV: 1000 Nulls: 0 Density: 0.001000 Min: 1.000000 Max: 1000.000000

For inline view X, column STATUS inherits the stats for ID2, ID2 gets those of YN, YN those of BUSINESS_DATE and BUSINESS_DATE gets NO STATISTICS.
So for our predicate on YN we get completely the wrong base statistics.
Then in addition, because the supplied value is out of range from the wrong statistics, estimates get further pro-rated.

Potential workaround is not risk-free as it moves the implicit order of the selected columns which could affect certain code.

alter table t1 modify status invisible;
alter table t1 modify status visible;

explain plan for
with x as
(select * from t1
 union all
 select * from t1)
select *
from x
where yn = 'Y';

select * from table(dbms_xplan.display);

Plan hash value: 3505968351
------------------------------------------------------------------------------------
| Id  | Operation                   | Name | Rows  | Bytes | Cost (%CPU)| Time     |
------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT            |      |  1000 | 90000 |   548   (0)| 00:00:01 |
|   1 |  VIEW                       |      |  1000 | 90000 |   548   (0)| 00:00:01 |
|   2 |   UNION-ALL                 |      |       |       |            |          |
|*  3 |    TABLE ACCESS STORAGE FULL| T1   |   500 | 20000 |   274   (0)| 00:00:01 |
|*  4 |    TABLE ACCESS STORAGE FULL| T1   |   500 | 20000 |   274   (0)| 00:00:01 |
------------------------------------------------------------------------------------

Reason it works is that the virtual column is now logically at the end of the column definitions.

If we compare the trace once “fixed”, then we see the following in the X section:

 Table:  X  Alias:  X  (NOT ANALYZED)
...
  Column (#8): STATUS(VARCHAR2)  NO STATISTICS (using defaults)

Online Statistics Gathering

Online Statistics Gathering, https://sqlmaria.com/2017/01/03/online-statistics-gathering/, is a pretty cool feature for the ages-old version that is Oracle 12.1, especially data warehouses.

As a recap, when you do direct path load into an empty segment, Oracle will take advantage of gathering statistics on the data whilst it is loading it, i.e no need to go back and re-read in an explicit stats gathering.

Note that, per Maria’s note, only base table and column statistics are gathered, not histograms but those can be gathered without re-gathering base column statistics via GATHER AUTO.

Old news.

We have only recently upgraded a complex application from 11.2.0.4 and hit an issue which is really obvious in hindsight but just worth pointing out, particular in combination with another feature?

I’m sure the behaviour below will come as no surprise in 11.2.0.4

drop table t1;
create global temporary table t1
on commit preserve rows
as
select * from user_objects where rownum <= 100;

explain plan for
select * from t1;

select * from table(dbms_xplan.display);
select num_rows from user_tables where table_name = 'T1';
select column_name, num_nulls, num_distinct from user_tab_columns where table_name = 'T1';

The output of note:

Plan hash value: 3617692013
----------------------------------------------------------------------------------
| Id | Operation                      | Name | Rows | Bytes | Cost (%CPU)| Time  |
----------------------------------------------------------------------------------
|  0 | SELECT STATEMENT               |      |  100 | 19000 |   2  (0)| 00:00:01 |
|  1 | TABLE ACCESS STORAGE FULL      | T1   |  100 | 19000 |   2  (0)| 00:00:01 |
----------------------------------------------------------------------------------

Note
-----
  - dynamic sampling used for this statement (level=2)


 NUM_ROWS
----------
      

COLUMN_NAME           NUM_NULLS NUM_DISTINCT
-------------------- ---------- ------------
GENERATED                       
SECONDARY                       
NAMESPACE                       
EDITION_NAME                      
OBJECT_NAME                      
SUBOBJECT_NAME                     
OBJECT_ID                       
DATA_OBJECT_ID                     
OBJECT_TYPE                      
CREATED                        
LAST_DDL_TIME                     
TIMESTAMP                       
STATUS                         
TEMPORARY                       
                 

We load 100 rows, there are no stats, dynamic sampling kicks in, bingo the optimizer expects 100 rows.

Then for > 11.2.0.4 ( in this case 19.6), with the addition of SCOPE column in the script for 19c, we see that we now have table and column statistics after the load despite no explicit stats gathering call. Which, given the feature we’re discussing, should be completely obvious and expected.

I’ve used a temporary table here deliberately purely to facilitate a comment at the end. Clearly this could be a normal heap table – but the SCOPE in the output is specific to the new feature of temporary table private statistics.

Plan hash value: 3617692013
----------------------------------------------------------------------------------
| Id | Operation                   | Name | Rows | Bytes | Cost (%CPU)|     Time |
----------------------------------------------------------------------------------
|  0 | SELECT STATEMENT            |      |  100 | 11300 |      2  (0)| 00:00:01 |
|  1 | TABLE ACCESS STORAGE FULL   | T1   |  100 | 11300 |      2  (0)| 00:00:01 |
----------------------------------------------------------------------------------

Note
-----
  - Global temporary table session private statistics used


  NUM_ROWS SCOPE  
---------- -------
           SHARED 
       100 SESSION

COLUMN_NAME            NUM_NULLS NUM_DISTINCT SCOPE  
--------------------- ---------- ------------ -------
OBJECT_NAME                    0            7 SESSION
SUBOBJECT_NAME                 7           93 SESSION
OBJECT_ID                      0          100 SESSION
DATA_OBJECT_ID                 3           97 SESSION
OBJECT_TYPE                    0            3 SESSION
CREATED                        0           95 SESSION
LAST_DDL_TIME                  0           97 SESSION
TIMESTAMP                      0           96 SESSION
STATUS                         0            1 SESSION
TEMPORARY                      0            1 SESSION
GENERATED                      0            2 SESSION
SECONDARY                      0            1 SESSION
NAMESPACE                      0            1 SESSION
EDITION_NAME                 100            0 SESSION
SHARING                        0            1 SESSION
EDITIONABLE                  100            0 SESSION
ORACLE_MAINTAINED              0            1 SESSION
APPLICATION                    0            1 SESSION
DEFAULT_COLLATION             94            1 SESSION
DUPLICATED                     0            1 SESSION
SHARDED                        0            1 SESSION
CREATED_APPID                100            0 SESSION
CREATED_VSNID                100            0 SESSION
MODIFIED_APPID               100            0 SESSION
MODIFIED_VSNID               100            0 SESSION

Again, we’ve loaded 100 rows, as part of the direct path load, we have some base & column statstics, the optimizer expects 100 rows. No dynamic sampling necessary

But what if our data is loaded in multiple steps, might this new online statistics gathering cause us a bit of a problem?

It only gathers the stats when the segment is empty.

I’m not going to repeat the output above for the table & column statistics, just the execution plan detail.

drop table t1;
create global temporary table t1
on commit preserve rows
as
select * from user_objects where rownum <= 100;
insert /*+ append */ into t1
select * from user_objects
commit;

insert /*+ append */ into t1
select * from user_objects
commit;

explain plan for
select * from t1;

Which in 11.2.0.4 gives:

Plan hash value: 3617692013
---------------------------------------------------------------------------------------
| Id | Operation                      | Name |   Rows | Bytes | Cost (%CPU)|    Time  |
---------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT               |      |  32376 | 6007K |    93   (0)| 00:00:01 |
|  1 | TABLE ACCESS STORAGE FULL      | T1   |  32376 | 6007K |    93   (0)| 00:00:01 |
---------------------------------------------------------------------------------------

Note
-----
  - dynamic sampling used for this statement (level=2)

select count(*) from t1;

  COUNT(*)
----------
     34392

And in 19.6

Plan hash value: 3617692013
----------------------------------------------------------------------------------
| Id | Operation                   | Name | Rows | Bytes | Cost (%CPU)|     Time |
----------------------------------------------------------------------------------
|  0 | SELECT STATEMENT            |      |  100 | 11300 |      2  (0)| 00:00:01 |
|  1 | TABLE ACCESS STORAGE FULL   | T1   |  100 | 11300 |      2  (0)| 00:00:01 |
----------------------------------------------------------------------------------

Note
-----
  - Global temporary table session private statistics used

select count(*) from t1;

  COUNT(*)
----------
     59712*

*With an obvious difference in actual rows, because these are different environments on different versions.

The problem now is that our subsequent processing code which drives off a table populated with different volumes of data in multiple stages used to work fine in 11.2.0.4 but is now at risk of some serious consequences from having cardinality mis-estimates thanks to inaccurate statistics from our new feature which is behaving as it should.

In our real-world example, it was not always the case that there was a big skew between the first load and the subsequent loads and actually this consequence, obvious in hindsight, took a few weeks to reveal itself until that first load into an empty segment happened to be very small followed by some other loads which were much larger.

Furthermore, this also involved the private temporary table aspect and so when you’re looking at solutions, you might consider whether some explicit stats gathering at the end of the load is the solution – in which case should it be private stats or shared stats or whether it even matters when quite possibly the easiest solution is to just use dynamic sampling in the subsequent select/s.

I was reminded of this issue when writing this other article earlier on a more serious problem that online statistics gathering was causing:

Oracle 19c Upgrade: Query hanging on PX Deq: Join Ack Part 2

Oracle 19c Upgrade: Bug 31602782 – Same Instance Slave Parse Failure Flood Control

It’s almost a universal truth that for any non-trivial application you can expect to hit one or two serious incidents in production post-upgrade, most often due to some combination of workload and/or timing which just didn’t happen in testing beforehand.

In this instance (/these instances), it was the bug 31602782, the patch for which has the above title, the doc id description being “Contention on CURSOR: Pin S wait on X when PQ slave’s execution plan does not match with QC.

This has been around since 12.2 and is first included in 20.1. The doc describes it as

When a parallel query is executed, QC sends parse message to all slaves in all instances…. if the slave could not build the cursor with the same plan as QC and could not join, another slave tries the same and so on until all slaves get exhausted

In practice, what this meant for us was avery large and significant contention on library cache lock and cursor: pin s wait for x affecting all data loads, large parsing backlogs, issues with anything then wanting library cache lock on the same underlying objects – e.g.partition maintenance operations, etc

There were two specific processes involved and had we not got a bug diagnosis when we did, I would have started to rewrite those processes. It is not uncommon that the flows which end up hitting bugs and performance issues have mileage left in them in terms of optimisation. In hindsight, I believe we did hit this problem in UAT but not in this area and in UAT I had rewritten the process in question as it was problematic anyway,

Certainly once this patch was applied, our most urgent post-upgrade issues were largely resolved.

As an aside, I would urge anyone looking at an upgrade to review beforehand the list of Important Recommended One-off Patches which for 19c is Doc Id: 2720807.1

Oracle 19c Upgrade: Query hanging on PX Deq: Join Ack

Next installment of issues observed post Oracle Upgrade (11.2.0.4 to 19.6)

Intermittent query affecting a number of SQL statement, but one particular SQL more than any other.

Event PX Deq: Join Ack is usually seen briefly when the QC (Query Co-ordinator) has to build the slave sets in order to execute a SQL statement in parallel. A message is sent to each slave and then the QC waits for acknowledgement (reference Doc Id: 250960.1)

On my application, when this problem occurs, the QC will hang forever waiting for the acknowledgement from one or a slow sequence of slaves. Longest I saw before intervention was 3 days.

Per that note, possible reason for prolonged wait times is that something happened to the PQ slave process. Unless/until PMON cleans up the internal structures, any new QC will assume the process is alive. Another possible cause is depletion of SGA memory such that the slave cannot establish its response channel.

With us, this issue is currently under investigation with Oracle Support but is believed to correlate to memory corruption errors:

ORA-00600: internal error code, arguments: [17182]

which ties back to bug 31045929: PGA Memory Corruption Caused By Cursor Frame Overrun

Oracle 19c Upgrade: Query reading way more partitions than it should

Still a work in progress… but despite a query plan which details that partition pruning should be happening, evidence (both physical reads and obvious timing) suggest that an OLTP-style query is reading all table partitions.

There is no evidence to suggest that this was happening before the upgrade (11.2.0.4 to 19.6) and plenty of evidence of it afterwards. Not consistent suggesting some significant triggering event.

Oracle: Groundbreakers Developer Community https://community.oracle.com/tech/developers/discussion/4480886/partition-list-iterator-reading-too-many-partitions/ currently has all the latest information. If I ever get to a conclusion, then I might collate & summarise here.

Exchange Partition Validation

Testing an upgrade from 11.2.0.4 to 19.6, we observed a very significant degradation in partition exchange performance.

Is it a case of expected behaviour or not?

The documentation is quite clear in both 11.2 and 19c:

https://docs.oracle.com/cd/E11882_01/server.112/e25523/part_admin002.htm#i1107555

https://docs.oracle.com/en/database/oracle/oracle-database/19/vldbg/maintenance-partition-tables-indexes.html#GUID-E08650B4-06B1-43F9-91B0-FBF685A3B848

When you specify WITHOUT VALIDATION for the exchange partition operation, this is normally a fast operation because it involves only data dictionary updates. However, if the table or partitioned table involved in the exchange operation has a primary key or unique constraint enabled, then the exchange operation is performed as if WITH VALIDATION were specified to maintain the integrity of the constraints.

Personally, in a data warehouse with exchange partition I would tend to have defined such a constraint as ENABLE NOVALIDATE if it was even required.

The CONSTRAINT is a PK constraint backed up a local index, partition keys as leading columns.

The trace file points to a clear culprit:

 select /*+ first_rows(1) ordered */ 1 
 from "X"."FB_P_161261_SP_9" A? ,"X"."FACILITY_BALANCE" B 
 where "A"."SNAPSHOT_ID" = "B"."SNAPSHOT_ID" and "A"."SNAPSHOT_VERSION" = "B"."SNAPSHOT_VERSION" and "A"."FACILITY_BALANCE_ID" = "B"."FACILITY_BALANCE_ID" and "A"."VERSION" = "B"."VERSION" 
 and ( tbl$or$idx$part$num("X"."FACILITY_BALANCE",0,0,0 ,B? .rowid )  <  62358 or  tbl$or$idx$part$num("X"."FACILITY_BALANCE",0,0,0 ,B? .rowid )  >  62358 ) 
 and tbl$or$idx$part$num("X"."FACILITY_BALANCE",0,0,0 ,A? ."SNAPSHOT_ID" ,A? ."SNAPSHOT_VERSION" )  <>  62358 and rownum < 2


call     count       cpu    elapsed       disk      query    current        rows
------- ------  -------- ---------- ---------- ---------- ----------  ----------
Parse        1      8.40       8.46          0          0          0           0
Execute      1      0.00       0.00          0          0          0           0
Fetch        1   4229.27    5278.73   27688674   27783294          0           0
------- ------  -------- ---------- ---------- ---------- ----------  ----------
total        3   4237.67    5287.20   27688674   27783294          0           0 

We know from Jonathan Lewis’s work on http://www.nocoug.org/download/2008-11/partitioning_NOCOUG.pdf that this is expected internal SQL from a ENABLE VALIDATE constraint in an EXCHANGE WITHOUT VALIDATION scenario

So why the big change in performance?

Probably this is an indication of just a simple execution plan issue. I would need to trace the same in 11g to confirm which is easier said than done under the circumstances.

This is the info from the 19c tkprof at least:

Rows (1st) Rows (avg) Rows (max) Row Source Operation

---------- ---------- ---------- ---------------------------------------------------
         0          0          0 COUNT STOPKEY (cr=27783294 pr=27688674 pw=0 time=287636041 us starts=1)
         0          0          0  NESTED LOOPS (cr=27783294 pr=27688674 pw=0 time=287636035 us starts=1 cost=4 size=1061 card=1)
 238651024  238651024  238651024   VIEW VW_JF_SET$91EDBF25 (cr=27783288 pr=27688673 pw=0 time=3245932610 us starts=1 cost=4 size=62 card=2)
 238651024  238651024  238651024    UNION-ALL (cr=27783288 pr=27688673 pw=0 time=2708356160 us starts=1)
  11351302   11351302   11351302     PARTITION COMBINED ITERATOR PARTITION: KEY KEY (cr=69570 pr=69469 pw=0 time=5491712 us starts=1 cost=2 size=43 card=1)
  11351302   11351302   11351302      INDEX STORAGE FAST FULL SCAN FIRST ROWS PK_FACILITY_BALANCE PARTITION: KEY KEY (cr=69570 pr=69469 pw=0 time=4380693 us starts=20 cost=2 size=43 card=1)(object id 42709299)
 227299722  227299722  227299722     PARTITION COMBINED ITERATOR PARTITION: KEY KEY (cr=27713718 pr=27619204 pw=0 time=2376271490 us starts=1 cost=2 size=43 card=1)
 227299722  227299722  227299722      INDEX STORAGE FAST FULL SCAN FIRST ROWS PK_FACILITY_BALANCE PARTITION: KEY KEY (cr=27713718 pr=27619204 pw=0 time=1916674628 us starts=62357 cost=2 size=43 card=1)(object id 42709299)
         0          0          0   INDEX UNIQUE SCAN FB_P_161261_SP_9$C3 (cr=6 pr=1 pw=0 time=1734545604 us starts=238651024 cost=0 size=1030 card=1)(object id 72993779)  
		

What is clear is that if the constraint definition is changed to ENABLE NOVALIDATE then the exchange partition takes about 1 minute. Which still feels a bit slow but a heck of a lot better than 90 minutes.

If you see Mohamed Houri’s comment below, this experience is not isolated and in his case, they went for EXCHANGE PARTITION (WITH VALIDATION). After the Christmas break, I will re-evaluate the choice I made.

Parallel Window Consolidator Calls The Stops

Sharing observations of performance issue arising out of testing 19.6 upgrade from 11.2.0.4 (bug possibly from 12+ looking at the fixes which work).

Sharing this one in particular as it doesn’t seem that common from anecdotal evidence (forums, blogs, support), it doesn’t appear fixed yet, progress with support has been disappointing, however circumstances don’t seem particularly niche.

We’ve had a few issues with a number of parallel queries just “hanging” forever.

Issue seems to be related to WINDOW CONSOLIDATOR and the parallel distribution method.

Haven’t been able to find a good matching bug via Oracle Support (nor happy with the progress of SR with them) but found a good match on a Lothar Flatz blog post which led me to the PQ_DISTRIBUTE_WINDOW as cause.

SQL contains parallel + join to view, view contains analytic
SQL Executes in under a second “normally”.

Without a fix, the SQL will just hang for a long time. The longest I’ve left it is 3 days but given the wait states of the sessions involved, there’s no reason to think it would stop of its own accord.

Jumping ahead to the workarounds which work, any of the following:

• Turn off fix_control 13345888 via alter session or opt_param
• Turn off “_adaptive_window_consolidator_enabled” via alter session/system or opt_param
• Hint a PQ distribution method other than 2. 3 doesn’t work here so 1 is the other option – PQ_DISTRIBUTE_WINDOW(@query_block 1)

Here we see some evidence from just now, running for nearly 30 minutes:

select s.inst_id i,s.sid,s.serial#,s.module
 ,      s.blocking_session blks,s.blocking_instance bi,s.final_blocking_session f_blk_s, s.final_blocking_instance fbi
 ,      CASE WHEN state != 'WAITING' THEN 'WORKING' ELSE 'WAITING' END AS state
 ,      CASE WHEN state != 'WAITING' THEN 'On CPU / runqueue' ELSE event END AS sw_event, s.seconds_in_wait wait
 ,      s.sql_id,s.sql_exec_id,to_char(s.sql_exec_start,'DD-MON-YYYY HH24:MI:SS') exec_start
 from   gv$session    s
 where  sql_id = '5xyrp7v4djagv';

         I        SID    SERIAL# MODULE                     BLKS         BI    F_BLK_S        FBI STATE   SW_EVENT                        WAIT SQL_ID        SQL_EXEC_ID EXEC_START                   
---------- ---------- ---------- -------------------- ---------- ---------- ---------- ---------- ------- ------------------------- ---------- ------------- ----------- -----------------------------
         2       2805      15947 SQL Developer                                                    WAITING PX Deq: Execution Msg           1492 5xyrp7v4djagv    33554434 26-OCT-2020 12:18:59         
         2       3095       3608 SQL Developer                                                    WAITING PX Deq: Execution Msg           1492 5xyrp7v4djagv    33554434 26-OCT-2020 12:18:59         
         2       3367      28066 SQL Developer                                                    WAITING PX Deq: Execution Msg           1492 5xyrp7v4djagv    33554434 26-OCT-2020 12:18:59         
         2       5610       8452 SQL Developer                                                    WAITING PX Deq: Table Q Normal          1492 5xyrp7v4djagv    33554434 26-OCT-2020 12:18:59         
         2       5885      54481 SQL Developer              9672          2       9672          2 WAITING PX Deq: Execute Reply           1492 5xyrp7v4djagv    33554434 26-OCT-2020 12:18:59         
         2       8828      57832 SQL Developer                                                    WAITING PX Deq: Execution Msg           1492 5xyrp7v4djagv    33554434 26-OCT-2020 12:18:59         
         2       9111      37143 SQL Developer                                                    WAITING PX Deq: Execution Msg           1492 5xyrp7v4djagv    33554434 26-OCT-2020 12:18:59         
         2       9383      50792 SQL Developer                                                    WAITING PX Deq: Execution Msg           1492 5xyrp7v4djagv    33554434 26-OCT-2020 12:18:59         
         2       9672      29993 SQL Developer                                                    WAITING PX Deq: Execution Msg           1492 5xyrp7v4djagv    33554434 26-OCT-2020 12:18:59         

Real-time SQL Monitoring report looks per below (note Duration compared to any other progress/metrics)… note that in later versions of Oracle, RTSM has a habit of timing out and reporting DONE(ERROR) even though the SQL is still going:

 Global Information
 ------------------------------
 Status              :  EXECUTING                  
 Instance ID         :  2                          
 SQL ID              :  5xyrp7v4djagv              
 SQL Execution ID    :  33554434                   
 Execution Started   :  10/26/2020 12:18:59        
 First Refresh Time  :  10/26/2020 12:18:59        
 Last Refresh Time   :  10/26/2020 12:18:59        
 Duration            :  1592s                      
 Module/Action       :  SQL Developer/-            
 Service             :  LNTDH8U.UK.DB.COM          
 Program             :  SQL Developer              


Global Stats
=========================================
| Elapsed |   Cpu   |  Other   | Buffer |
| Time(s) | Time(s) | Waits(s) |  Gets  |
=========================================
|    0.00 |    0.00 |     0.00 |      3 |
=========================================

Parallel Execution Details (DOP=4 , Servers Allocated=8)
==========================================================================================
|      Name      | Type  | Server# | Elapsed |   Cpu   |  Other   | Buffer | Wait Events |
|                |       |         | Time(s) | Time(s) | Waits(s) |  Gets  | (sample #)  |
==========================================================================================
| PX Coordinator | QC    |         |    0.00 |    0.00 |     0.00 |      3 |             |
| p000           | Set 1 |       1 |         |         |          |        |             |
| p001           | Set 1 |       2 |         |         |          |        |             |
| p002           | Set 1 |       3 |         |         |          |        |             |
| p003           | Set 1 |       4 |         |         |          |        |             |
| p004           | Set 2 |       1 |         |         |          |        |             |
| p005           | Set 2 |       2 |         |         |          |        |             |
| p006           | Set 2 |       3 |         |         |          |        |             |
| p007           | Set 2 |       4 |         |         |          |        |             |
==========================================================================================

SQL Plan Monitoring Details (Plan Hash Value=3844894891)
===============================================================================================================================================================================================
| Id   |                           Operation                           |              Name              |  Rows   | Cost |   Time    | Start  | Execs |   Rows   | Activity | Activity Detail |
|      |                                                               |                                | (Estim) |      | Active(s) | Active |       | (Actual) |   (%)    |   (# samples)   |
===============================================================================================================================================================================================
|    0 | SELECT STATEMENT                                              |                                |         |      |           |        |     1 |          |          |                 |
| -> 1 |   PX COORDINATOR                                              |                                |         |      |         1 |     +0 |     1 |        0 |   100.00 | Cpu (1)         |
|    2 |    PX SEND QC (RANDOM)                                        | :TQ20006                       |      2M |  445 |           |        |       |          |          |                 |
|    3 |     HASH JOIN                                                 |                                |      2M |  445 |           |        |       |          |          |                 |
|    4 |      PART JOIN FILTER CREATE                                  | :BF0000                        |     232 |  441 |           |        |       |          |          |                 |
|    5 |       PX RECEIVE                                              |                                |     232 |  441 |           |        |       |          |          |                 |
|    6 |        PX SEND BROADCAST                                      | :TQ20005                       |     232 |  441 |           |        |       |          |          |                 |
|    7 |         VIEW                                                  |                                |     232 |  441 |           |        |       |          |          |                 |
|    8 |          WINDOW CONSOLIDATOR BUFFER                           |                                |     232 |  441 |           |        |       |          |          |                 |
|    9 |           PX RECEIVE                                          |                                |     232 |  441 |           |        |       |          |          |                 |
|   10 |            PX SEND HASH                                       | :TQ20004                       |     232 |  441 |           |        |       |          |          |                 |
|   11 |             WINDOW BUFFER                                     |                                |     232 |  441 |           |        |       |          |          |                 |
|   12 |              HASH JOIN                                        |                                |     232 |  441 |           |        |       |          |          |                 |
|   13 |               NESTED LOOPS                                    |                                |     505 |    4 |           |        |       |          |          |                 |
|   14 |                TABLE ACCESS BY GLOBAL INDEX ROWID             | D_B                            |       1 |    3 |           |        |       |          |          |                 |
|   15 |                 PX RECEIVE                                    |                                |       1 |    2 |           |        |       |          |          |                 |
|   16 |                  PX SEND HASH (BLOCK ADDRESS)                 | :TQ20002                       |       1 |    2 |           |        |       |          |          |                 |
|   17 |                   PX SELECTOR                                 |                                |         |      |           |        |       |          |          |                 |
|   18 |                    INDEX UNIQUE SCAN                          | D_B_PK                         |       1 |    2 |           |        |       |          |          |                 |
|   19 |                INDEX FULL SCAN                                | D_R_UK01                       |     505 |    1 |           |        |       |          |          |                 |
|   20 |               PX RECEIVE                                      |                                |     108 |  437 |           |        |       |          |          |                 |
|   21 |                PX SEND BROADCAST                              | :TQ20003                       |     108 |  437 |           |        |       |          |          |                 |
|   22 |                 VIEW                                          | V_V2                           |     108 |  437 |           |        |       |          |          |                 |
|   23 |                  WINDOW CONSOLIDATOR BUFFER                   |                                |     108 |  437 |           |        |       |          |          |                 |
|   24 |                   PX RECEIVE                                  |                                |     108 |  437 |           |        |       |          |          |                 |
|   25 |                    PX SEND HASH                               | :TQ20001                       |     108 |  437 |           |        |       |          |          |                 |
|   26 |                     WINDOW SORT                               |                                |     108 |  437 |           |        |       |          |          |                 |
|   27 |                      NESTED LOOPS                             |                                |     108 |  436 |           |        |       |          |          |                 |
|   28 |                       NESTED LOOPS                            |                                |     108 |    4 |           |        |       |          |          |                 |
|   29 |                        TABLE ACCESS BY GLOBAL INDEX ROWID     | D_B                            |       1 |    3 |           |        |       |          |          |                 |
|   30 |                         PX RECEIVE                            |                                |       1 |    2 |           |        |       |          |          |                 |
|   31 |                          PX SEND HASH (BLOCK ADDRESS)         | :TQ20000                       |       1 |    2 |           |        |       |          |          |                 |
|   32 |                           PX SELECTOR                         |                                |         |      |           |        |       |          |          |                 |
|   33 |                            INDEX UNIQUE SCAN                  | D_B_PK                         |       1 |    2 |           |        |       |          |          |                 |
|   34 |                        INDEX RANGE SCAN                       | D_BS_UK01                      |     108 |    1 |           |        |       |          |          |                 |
|   35 |                       PX COORDINATOR                          |                                |         |      |           |        |       |          |          |                 |
|   36 |                        PX SEND QC (RANDOM)                    | :TQ10002                       |       1 |    4 |           |        |       |          |          |                 |
|   37 |                         BUFFER SORT                           |                                |      2M |      |           |        |       |          |          |                 |
|   38 |                          VIEW                                 | V_V1                           |       1 |    4 |           |        |       |          |          |                 |
|   39 |                           UNION ALL PUSHED PREDICATE          |                                |         |      |           |        |       |          |          |                 |
|   40 |                            TABLE ACCESS BY GLOBAL INDEX ROWID | D_S                            |       1 |    2 |           |        |       |          |          |                 |
|   41 |                             BUFFER SORT                       |                                |         |      |           |        |       |          |          |                 |
|   42 |                              PX RECEIVE                       |                                |       1 |    1 |           |        |       |          |          |                 |
|   43 |                               PX SEND HASH (BLOCK ADDRESS)    | :TQ10000                       |       1 |    1 |           |        |       |          |          |                 |
|   44 |                                PX SELECTOR                    |                                |         |      |           |        |       |          |          |                 |
|   45 |                                 INDEX UNIQUE SCAN             | D_S_PK                         |       1 |    1 |           |        |       |          |          |                 |
|   46 |                            TABLE ACCESS BY INDEX ROWID        | D_S                            |       1 |    2 |           |        |       |          |          |                 |
|   47 |                             BUFFER SORT                       |                                |         |      |           |        |       |          |          |                 |
|   48 |                              PX RECEIVE                       |                                |       1 |    1 |           |        |       |          |          |                 |
|   49 |                               PX SEND HASH (BLOCK ADDRESS)    | :TQ10001                       |       1 |    1 |           |        |       |          |          |                 |
|   50 |                                PX SELECTOR                    |                                |         |      |           |        |       |          |          |                 |
|   51 |                                 INDEX UNIQUE SCAN             | D_S                            |       1 |    1 |           |        |       |          |          |                 |
|   52 |      PX BLOCK ITERATOR ADAPTIVE                               |                                |    8255 |    3 |           |        |       |          |          |                 |
|   53 |       TABLE ACCESS STORAGE FULL                               | F_FACT                         |    8255 |    3 |           |        |       |          |          |                 |
===============================================================================================================================================================================================

ASH says it’s not doing anything (as we’d expect it to, being consistent with RTSM report above).

select count(*), min(sample_time), max(sample_time), sysdate from gv$active_session_history where sql_id = '5xyrp7v4djagv';

  COUNT(*) MIN(SAMPLE_TIME)             MAX(SAMPLE_TIME)             SYSDATE             
---------- ---------------------------- ---------------------------- --------------------
         1 26-OCT-20 12.18.59.828000000 26-OCT-20 12.18.59.828000000 26-OCT-2020 12:50:29

Miscellaneous Slave Info

select
decode(px.qcinst_id,NULL,'QC',
' - '||lower(substr(pp.SERVER_NAME,
length(pp.SERVER_NAME)-4,4) ) )"Username",
decode(px.qcinst_id,NULL, 'QC', '(Slave)') "QC/Slave" ,
to_char( px.server_set) "SlaveSet",
to_char(s.sid) "SID",
to_char(px.inst_id) "Slave INST",
decode(px.qcinst_id, NULL ,to_char(s.sid) ,px.qcsid) "QC SID",
to_char(px.qcinst_id) "QC INST",
px.req_degree "Req. DOP",
px.degree "Actual DOP"
from gv$px_session px,
gv$session s ,
gv$px_process pp
where px.sid=s.sid (+)
and px.serial#=s.serial#(+)
and px.inst_id = s.inst_id(+)
and px.sid = pp.sid (+)
and px.serial#=pp.serial#(+)
and s.sql_id = '5xyrp7v4djagv'
order by 6 , 1 desc
/

Usernam QC/Slav SlaveSet   SID       Slave INST QC SID     QC INST      Req. DOP  Actual DOP
------- ------- ---------- --------- ---------- ---------- -------- ------------- -----------
QC      QC                 5885       2          5885         
 - p007 (Slave) 2          9672       2          5885       2                   4          4
 - p006 (Slave) 2          3367       2          5885       2                   4          4
 - p005 (Slave) 2          9395       2          5885       2                   4          4
 - p004 (Slave) 2          3095       2          5885       2                   4          4
 - p003 (Slave) 1          9111       2          5885       2                   4          4
 - p002 (Slave) 1          2805       2          5885       2                   4          4
 - p001 (Slave) 1          8828       2          5885       2                   4          4
 - p000 (Slave) 1          5610       2          5885       2                   4          4

Detail! And don’t forget the notes…

…and how sparse tables can mess up your dynamic sampling.

A little lesson to self about paying attention to the detail, the obvious frickin’ detail. Getting older and slower.

We had one of those problems where a multitude of things were slow and yet there were no significant system-level problems (e.g. no general slow IO, no setting of the fast=false parameter, etc)

In such situations, if you check the high level system level metrics – AWR etc – and nothing is obvious then it makes sense to narrow the scope & drill into a specific problem, and distill that problem/statement as small as you can. If you can find the issue there then you might hope to find that that is the same as the wider problem and if not well you can just take that approach to every individual area,

I had a problem across a number of reporting modules, I picked on one module and from there I picked on the statement which was currently running and which was running for much longer than expected, I picked out one of the obvious problem joins within the problem statement and started looking at a simple two table join where the cardinality estimates were going wrong.

Most of the specific details of this plan and SQL can be ignored. It’s not important.

What is important is the cardinality difference.

And in fact, in this particular cut down example, the cardinality difference does not have the plan impact it does in the original setting.

 
set pages 999
explain plan for
SELECT /*+ parallel(4)*/
	   count(*)
FROM   psbal
LEFT OUTER JOIN
       prdct
ON    (prdct.d_product_id                        = psbal.d_product_id
AND    prdct.create_ts                           TO_TIMESTAMP('14.10.2020 08:16:34.822981', 'DD.MM.YYYY HH24:MI:SS.FF6'));

select * from table(dbms_xplan.display);

Plan hash value: 3885851338
--------------------------------------------------------------------------------------------------------------------------------------------------
|  Id | Operation                             | Name          | Rows | Bytes | Cost (%CPU)| Time     | Pstart| Pstop |  TQ   |IN-OUT| PQ Distrib |
--------------------------------------------------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT                      |               |    1 |    72 |   3430K (3)| 01:54:22 |       |       |       |      |            |
|   1 |  SORT AGGREGATE                       |               |    1 |    72 |            |          |       |       |       |      |            |
|   2 |   PX COORDINATOR                      |               |      |       |            |          |       |       |       |      |            |
|   3 |    PX SEND QC (RANDOM)                | :TQ10003      |    1 |    72 |            |          |       |       | Q1,03 | P->S |  QC (RAND) |
|   4 |     SORT AGGREGATE                    |               |    1 |    72 |            |          |       |       | Q1,03 | PCWP |            |
|*  5 |      HASH JOIN                        |               | 7466M|   500G|   3430K (3)| 01:54:22 |       |       | Q1,03 | PCWP |            |
|   6 |       PART JOIN FILTER CREATE         | :BF0000       |  286K|  1680K|     56  (0)| 00:00:01 |       |       | Q1,03 | PCWP |            |
|   7 |        PX RECEIVE                     |               |  286K|  1680K|     56  (0)| 00:00:01 |       |       | Q1,03 | PCWP |            |
|   8 |         PX SEND BROADCAST             | :TQ10000      |  286K|  1680K|     56  (0)| 00:00:01 |       |       | Q1,00 | P->P |  BROADCAST |
|   9 |          PX BLOCK ITERATOR            |               |  286K|  1680K|     56  (0)| 00:00:01 |       |       | Q1,00 | PCWC |            |
|  10 |           INDEX STORAGE FAST FULL SCAN| S_PK          |  286K|  1680K|     56  (0)| 00:00:01 |       |       | Q1,00 | PCWP |            |
|* 11 |       HASH JOIN RIGHT OUTER           |               | 7466M|   458G|   3425K (3)| 01:54:12 |       |       | Q1,03 | PCWP |            |
|  12 |        PX RECEIVE                     |               |    1 |    30 |    306  (0)| 00:00:01 |       |       | Q1,03 | PCWP |            |
|  13 |         PX SEND BROADCAST             | :TQ10001      |    1 |    30 |    306  (0)| 00:00:01 |       |       | Q1,01 | P->P |  BROADCAST |
|  14 |          PX BLOCK ITERATOR            |               |    1 |    30 |    306  (0)| 00:00:01 |     1 |     3 | Q1,01 | PCWC |            |
|* 15 |           TABLE ACCESS STORAGE FULL   | PRODUCT       |    1 |    30 |    306  (0)| 00:00:01 |     1 |     3 | Q1,01 | PCWP |            |
|* 16 |        HASH JOIN                      |               | 7466M|   250G|   3420K (3)| 01:54:01 |       |       | Q1,03 | PCWP |            |
|  17 |         PX RECEIVE                    |               | 6903K|   118M|  16379  (1)| 00:00:33 |       |       | Q1,03 | PCWP |            |
|  18 |          PX SEND BROADCAST            | :TQ10002      | 6903K|   118M|  16379  (1)| 00:00:33 |       |       | Q1,02 | P->P |  BROADCAST |
|  19 |           PX BLOCK ITERATOR           |               | 6903K|   118M|  16379  (1)| 00:00:33 |     1 |     3 | Q1,02 | PCWC |            |
|* 20 |            TABLE ACCESS STORAGE FULL  | BOOK          | 6903K|   118M|  16379  (1)| 00:00:33 |     1 |     3 | Q1,02 | PCWP |            |
|  21 |         PX PARTITION LIST JOIN-FILTER |               | 8064M|   135G|   3398K (3)| 01:53:17 |:BF0000|:BF0000| Q1,03 | PCWC |            |
|  22 |          TABLE ACCESS STORAGE FULL    | BALANCE       | 8064M|   135G|   3398K (3)| 01:53:17 |:BF0000|:BF0000| Q1,03 | PCWP |            |
--------------------------------------------------------------------------------------------------------------------------------------------------
 
Predicate Information (identified by operation id):
---------------------------------------------------
  5 - access("FCT"."S_VID"="DNSP"."S_VID")
 11 - access("PRDCT"."PRODUCT_ID"(+)="FCT"."PRODUCT_ID")
 15 - storage(NVL("PRDCT"."MODIFY_TS"(+),TIMESTAMP' 9999-12-31 00:00:00')>TIMESTAMP' 2020-10-14 08:16:34.822981000' AND 
          "PRDCT"."CREATE_TS"(+)TIMESTAMP' 2020-10-14 08:16:34.822981000' AND 
         "PRDCT"."CREATE_TS"(+)<=TIMESTAMP' 2020-10-14 08:16:34.822981000')
 16 - access("BOOK_ID"="FCT"."BOOK_ID" AND "VERSION"="FCT"."BOOK_VERSION")
 20 - storage("COLUMN1" IS NULL OR "D_BOOK_VID"=(-2) OR "D_BOOK_VID"=(-1))
    filter("COLUMN1" IS NULL OR "D_BOOK_VID"=(-2) OR "D_BOOK_VID"=(-1))
 
Note
-----
  - dynamic sampling used for this statement (level=7)
  - Degree of Parallelism is 4 because of hint

and this:

set pages 999
explain plan for
select count(*)
FROM   prdct
WHERE  prdct.create_ts  <= TO_TIMESTAMP('14.10.2020 08:16:34.822981', 'DD.MM.YYYY HH24:MI:SS.FF6')
AND    NVL(prdct.modify_ts, DATE '9999-12-31')  > TO_TIMESTAMP('14.10.2020 08:16:34.822981', 'DD.MM.YYYY HH24:MI:SS.FF6');
   
select * from table(dbms_xplan.display);

Plan hash value: 2639949168
----------------------------------------------------------------------------------------------------
| Id | Operation                 | Name     | Rows | Bytes | Cost (%CPU)| Time     | Pstart| Pstop |
----------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT          |          |    1 |    14 |   1103  (1)| 00:00:14 |       |       |
|  1 | SORT AGGREGATE            |          |    1 |    14 |            |          |       |       |
|  2 |  PARTITION LIST ALL       |          |  399 |  5586 |   1103  (1)| 00:00:14 |     1 |     3 |
|* 3 |  TABLE ACCESS STORAGE FULL| PRODUCT  |  399 |  5586 |   1103  (1)| 00:00:14 |     1 |     3 |
----------------------------------------------------------------------------------------------------
 
Predicate Information (identified by operation id):
---------------------------------------------------
  3 - storage(NVL("MODIFY_TS",TIMESTAMP' 9999-12-31 00:00:00')>TIMESTAMP' 2020-10-14 
       08:16:34.822981000' AND "CREATE_TS"<=TIMESTAMP' 2020-10-14 08:16:34.822981000')
    filter(NVL("MODIFY_TS",TIMESTAMP' 9999-12-31 00:00:00')>TIMESTAMP' 2020-10-14 
       08:16:34.822981000' AND "CREATE_TS"<=TIMESTAMP' 2020-10-14 08:16:34.822981000')

Once you see the problem, you can’t unsee it but for whatever reason, for ages, I was focusing on why there would be such a cardinality difference between A and B for what are basically the single table cardinality estimates for the same table without seeing the explanation right there in front of me.

Note
-----
  - dynamic sampling used for this statement (level=7)

I then got distracted and spent some time investigating why dynamic sampling was kicking in. Parallel query has different rules about when it can kick in. And I found reasons why it might.

But then I put that thought to one side.

Why is dynamic sampling saying this will return 1 row?

This is a small table and the estimate should be accurate and we like dynamic sampling so we want to show the feature to its full capability whenever and wherever it kicks in

Sure enough, as we might expect, if I hint dynamic sampling on the single table, estimate is one.

set pages 999
explain plan for
select /*+ dynamic_sampling(4) */ count(*)
FROM  prdct
WHERE prdct.create_ts                  <= TO_TIMESTAMP('14.10.2020 08:16:34.822981', 'DD.MM.YYYY HH24:MI:SS.FF6')
AND  NVL(prdct.modify_ts, DATE '9999-12-31')      > TO_TIMESTAMP('14.10.2020 08:16:34.822981', 'DD.MM.YYYY HH24:MI:SS.FF6');
   
select * from table(dbms_xplan.display);

----------------------------------------------------------------------------------------------------
| Id | Operation                 | Name     | Rows | Bytes | Cost (%CPU)| Time     | Pstart| Pstop |
----------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT          |          |    1 |    14 |   1103  (1)| 00:00:14 |       |       |
|  1 | SORT AGGREGATE            |          |    1 |    14 |            |          |       |       |
|  2 |  PARTITION LIST ALL       |          |    1 |    14 |   1103  (1)| 00:00:14 |     1 |     3 |
|* 3 |  TABLE ACCESS STORAGE FULL| PRODUCT  |    1 |    14 |   1103  (1)| 00:00:14 |     1 |     3 |
----------------------------------------------------------------------------------------------------
 
Predicate Information (identified by operation id):
---------------------------------------------------
  3 - storage(NVL("MODIFY_TS",TIMESTAMP' 9999-12-31 00:00:00')>TIMESTAMP' 2020-10-14 
       08:16:34.822981000' AND "CREATE_TS"<=TIMESTAMP' 2020-10-14 08:16:34.822981000')
    filter(NVL("MODIFY_TS",TIMESTAMP' 9999-12-31 00:00:00')>TIMESTAMP' 2020-10-14 
       08:16:34.822981000' AND "CREATE_TS"<=TIMESTAMP' 2020-10-14 08:16:34.822981000')
 
Note
-----
  - dynamic sampling used for this statement (level=4)

Without access to the sample statements, what suggestive evidence can we find?

select table_name, num_rows, blocks, avg_row_len
from  user_tables
where table_name = 'PRODUCT';

TABLE_NAME                       NUM_ROWS     BLOCKS AVG_ROW_LEN
------------------------------ ---------- ---------- -----------
PRODUCT                               462       4064         193

So that’s not a lot of rows in a lot more blocks than should be necessary.

At this point, we should go off and find out what the reasons might be.

For what it’s worth, for this application, my suspicions are historic direct path maintenance code coupled with table partitioning on status (LATEST/SUPERSEDED) and therefore row movement means an update is a delete + insert, coupled with periods of very low rate of change and small row sizes.

So we end up with old rows moving partition – using a new block for the updated version and leaving behind an empty block where the version was before the update and then relatively few new version rows per run which are using new blocks, and so lots of empty blocks.

i.e. sparsely populated table.

And then dynamic sampling kicks in and samples a bunch of blocks, and finds few actual rows from those samples and comes up with a low estimate and then the whole problem starts. And these were shared tables across the reporting modules so it had a reasonable wide impact.

It would be nice to back this up with some trace files detailing any of the dynamic sampling numbers but I don’t have access by default and mocking this all up outside of work is always a worthwhile exercise but just takes up so much time.

Anyway… move some partitions, rebuild some indexes and 4000 blocks becomes just over 40.

Now our dynamic sampling is looking much better:

----------------------------------------------------------------------------------------------------
| Id | Operation                 | Name     | Rows | Bytes | Cost (%CPU)| Time     | Pstart| Pstop |
----------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT          |          |   1 |     14 |   1103  (1)| 00:00:14 |       |       |
|  1 | SORT AGGREGATE            |          |   1 |     14 |            |          |       |       |
|  2 |  PARTITION LIST ALL       |          | 297 |     14 |   1103  (1)| 00:00:14 |     1 |     3 |
|* 3 |  TABLE ACCESS STORAGE FULL| PRODUCT  | 297 |     14 |   1103  (1)| 00:00:14 |     1 |     3 |
----------------------------------------------------------------------------------------------------
 
Predicate Information (identified by operation id):
---------------------------------------------------
  3 - storage(NVL("MODIFY_TS",TIMESTAMP' 9999-12-31 00:00:00')>TIMESTAMP' 2020-10-14 
       08:16:34.822981000' AND "CREATE_TS"<=TIMESTAMP' 2020-10-14 08:16:34.822981000')
    filter(NVL("MODIFY_TS",TIMESTAMP' 9999-12-31 00:00:00')>TIMESTAMP' 2020-10-14 
       08:16:34.822981000' AND "CREATE_TS"<=TIMESTAMP' 2020-10-14 08:16:34.822981000')
 
Note
-----
  - dynamic sampling used for this statement (level=4)

Exercise repeated for a whole bunch of tables in a similar situation and everything across the board is a lot healthier.