We have a Oracle 19C database (19.0.0.0.ru-2021-04.rur-2021-04.r1) on AWS RDS which is hosted on an 4 CPU 32 GB RAM instance. The size of the database is not big (35 GB) and the PGA Aggregate Limit is 8GB & Target is 4GB. Whenever the scheduled internal Oracle Auto Optimizer Stats Collection Job (ORA$AT_OS_OPT_SY_nnn) runs then it consumes substantially high PGA memory (approx 7GB) and sometimes this makes database unstable and AWS loses communication with the RDS instance so it restarts the database.
We thought this may be linked to existing Oracle bug 30846782 (19C+: Fast/Excessive PGA growth when using DBMS_STATS.GATHER_TABLE_STATS) but Oracle & AWS had fixed it in the current 19C version we are using. There are no application level operations that consume this much PGA and the database restart have always happened when the Auto Optimizer Stats Collection Job was running. There are couple of more databases, which are on same version, where same pattern was observed and the database was restarted by AWS. We have disabled the job now on those databases to avoid further occurrence of this issue however we want to run this job as disabling it may cause old stats being available in the database.
Any pointers on how to tackle this issue?
I found the same issue in my AWS RDS Oracle 18c and 19c instances, even though I am not in the same patch level as you.
In my case, I applied this workaround and it worked.
SQL> alter system set "_fix_control"='20424684:OFF' scope=both;
However, before applying this change, I strongly suggest that you test it on your non production environments, and if you can, try to consult with Oracle Support. Dealing with hidden parameters might lead to unexpected side effects, so apply it at your own risk.
Instead of completely abandoning automatic statistics gathering, try find any specific objects that are causing the problem. If only a small number of tables are responsible for a large amount of statistics gathering, you can manually analyze those tables or change their preferences.
First, use the below SQL to see which objects are causing the most statistics gathering. According to the test case in bug 30846782, the problem seems to be only related to the number of times DBMS_STATS is called.
select *
from dba_optstat_operations
order by start_time desc;
In addition, you may be able to find specific SQL statements or sessions that generate a lot of PGA memory with the below query. (However, if the database restarts, it's possible that AWR won't save the recorded values.)
select username, event, sql_id, pga_allocated/1024/1024/1024 pga_allocated_gb, gv$active_session_history.*
from gv$active_session_history
join dba_users on gv$active_session_history.user_id = dba_users.user_id
where pga_allocated/1024/1024/1024 >= 1
order by sample_time desc;
If the problem is only related to a small number of tables with a large number of partitions, you can manually gather the stats on just that table in a separate session. Once the stats are gathered, the table won't be analyzed again until about 10% of the data is changed.
begin
dbms_stats.gather_table_stats(user, 'PGA_STATS_TEST');
end;
/
It's not uncommon for a database to spend a long time gathering statistics, but it is uncommon for a database to constantly analyze thousands of objects. Running into this bug implies there is something unusual about your database - are you constantly dropping and creating objects, or do you have a large number of objects that have 10% of their data modified every day? You may need to add a manual gather step to a few of your processes.
Turning off the automatic statistics job entirely will eventually cause many performance problems. Even if you can't add manual gathering steps, you may still want to keep the job enabled. For example, if tables are being analyzed too frequently, you may want to increase the table preference for the "STALE_PERCENT" threshold from 10% to 20%:
begin
dbms_stats.set_table_prefs
(
ownname => user,
tabname => 'PGA_STATS_TEST',
pname => 'STALE_PERCENT',
pvalue => '20'
);
end;
/
I am using OEM to view the tuning adviser report which runs as a part of daily maintenance job, for a specific query. Now my requirement is to get a single file (text/html) which will have the tuning adviser report for top-10/20 of AWR report. Can some one help me getting the report as requested.
DB version: 12.1.0.2
You need a “task” from a SQL Tuning Advisor (STA) run to get a STA report. The code to do this for a single task follows:
SELECT DBMS_SQLTUNE.report_tuning_task(:task_name) AS recommendations FROM dual;
It should not be so difficult to get the STA report for multiple tasks, for example using SQL*Plus:
-- Once the tuning task has executed successfully the recommendations can be displayed using the REPORT_TUNING_TASK function.
set linesize 210
set pagesize 9999
set long 10000000
set time on
set timing on
SET SERVEROUTPUT ON
-- width of output should not need more than 200
column recommendations format a200
spool c:\temp\STA_reports.txt
SELECT DBMS_SQLTUNE.report_tuning_task('68vm8dtty867d_1340348426_AWR') AS recommendations FROM dual ;
prompt =================================================================
SELECT DBMS_SQLTUNE.report_tuning_task('69w2tux85a9x7_814599999_AWR') AS recommendations FROM dual ;
rem ...
spool off
So, basically, you’ll need to run the STA for the top-SQL then generate the reports as one file.
I don’t regularly use OEM as I’ve found this tool to not cover the use cases that I frequently encounter, rather, I’ll generate a Top-SQL listing from DBA_HIST_SQLSTAT directly*. One reason for this is I can subset out the SQL that does not apply to a reported performance problem; also, I can order the Top-SQL by a variety of metrics (e.g. elapsed time, cpu time, buffered gets, …). Once I have the SQL_ID’s for the SQL of interest I run them all through the SQL Tuning Advisor. Rather than examining the SQL Tuning Advisor Reports I aggregate the persisted results directly from the DBA_ADVISOR% tables. With these queries, I extract the code to implement the recommendations (e.g. SQL for gather stats, create indexes, accept SQL Profiles) directly from the DBA_ADVISOR% tables. I have presented on this at many Oracle conferences, but that solution goes far beyond the direct answer to the question.
*DBA_HIST_SQLSTAT script can be found in the answer to question "how much CPU a session consuming at a given time in oracle"
What is Plan hash value in Oracle ? Does this imply anything related to time of execution of a query ? How do I find execution time of a query in Oracle ?
There are 3 views that show SQL statements that ran in your SGA.
V$SQL shows stats and is updated every 5 seconds.
V$SQLAREA shows parsed statements in memory, ready to execute.
V$SQLSTATS has greater retention than V$SQL.
So if you look in V$SQL you will see every statement has a unique SQL ID. When the statement is parsed, oracle generates an explain plan for the SQL and then associates that plan with a hash value which is a unique value for that plan. Certain factors can cause the plan to change, making it execute better or worse. Then you will get a new plan and a new hash value for that plan.
To see the history of this, look at view DBA_HIST_SQL_PLAN.
There is a lot more theory around explain plans and how to optimize SQL statements, and how to give them profiles and baselines, but I hope this gives you an idea of the basics.
I am developing a DWH on Oracle 11g. We have some big tables (250+ million rows), partitioned by value. Each partition is a assigned to a different feeding source, and every partition is independent from others, so they can be loaded and processed concurrently.
Data distribution is very uneven, we have partition with millions rows, and partitions with not more than a hundred rows, but I didn't choose the partitioning scheme, and by the way I can't change it.
Considered the data volume, we must assure that every partition has always up-to-date statistics, because if the subsequent elaborations don't have an optimal access to the data, they will last forever.
So for each concurrent ETL thread, we
Truncate the partition
Load data from staging area with
SELECT /*+ APPEND */ INTO big_table PARTITION(part1) FROM temp_table WHERE partition_colum = PART1
(this way we have direct path and we don't lock the whole table)
We gather statistics for the modified partition.
In the first stage of the project, we used the APPROX_GLOBAL_AND_PARTITION strategy and worked like a charm
dbms_stats.gather_table_stats(ownname=>myschema,
tabname=>big_table,
partname=>part1,
estimate_percent=>1,
granularity=>'APPROX_GLOBAL_AND_PARTITION',
CASCADE=>dbms_stats.auto_cascade,
degree=>dbms_stats.auto_degree)
But, we had the drawback that, when we loaded a small partition, the APPROX_GLOBAL part was dominant (still a lot faster than GLOBAL) , and for a small partition we had, e.g., 10 seconds of loading, and 20 minutes of statistics.
So we have been suggested to switch to the INCREMENTAL STATS feature of 11g, which means that you don't specify the partition you have modified, you leave all parameters in auto, and Oracle does it's magic, automatically understanding which partition(s) have been touched. And it actually works, we have really speeded up the small partition. After turning on the feature, the call became
dbms_stats.gather_table_stats(ownname=>myschema,
tabname=>big_table,
estimate_percent=>dbms_stats.auto_sample_size,
granularity=>'AUTO',
CASCADE=>dbms_stats.auto_cascade,
degree=>dbms_stats.auto_degree)
notice, that you don't pass the partition anymore, and you don't specify a sample percent.
But, we're having a drawback, maybe even worse that the previous one, and this is correlated with the high level of parallelism we have.
Let's say we have 2 big partition that starts at the same time, they will finish the load phase almost at the same time too.
The first thread ends the insert statement, commits, and launches the stats gathering. The stats procedure notices there are 2 partition modified (this is correct, one is full and the second is truncated, with a transaction in progress), updates correctly the stats for both the partitions.
Eventually the second partition ends, gather the stats, it see all partition already updated, and does nothing (this is NOT correct, because the second thread committed the data in the meanwhile).
The result is:
PARTITION NAME | LAST ANALYZED | NUM ROWS | BLOCKS | SAMPLE SIZE
-----------------------------------------------------------------------
PART1 | 04-MAR-2015 15:40:42 | 805731 | 20314 | 805731
PART2 | 04-MAR-2015 15:41:48 | 0 | 16234 | (null)
and the consequence is that I occasionally incur in not optimal plans (which mean killing the session, refresh manually the stats, manually launch the precess again).
I tried even putting an exclusive lock on the gathering, so no more than one thread can gather stats on the same table at once, but nothing changed.
IMHO this is an odd behaviour, because the stats procedure, the second time it is invoked, should check for the last commit on the second partition, and should see it's newer than the last stats gathering time. But seems it's not happening.
Am I doing something wrong? Is it an Oracle bug? How can I guarantee that all stats are always up-to-date with incremental stats feature turned on, and an high level of concurrency?
I managed to reach a decent compromise with this function.
PROCEDURE gather_tb_partiz(
p_tblname IN VARCHAR2,
p_partname IN VARCHAR2)
IS
v_stale all_tab_statistics.stale_stats%TYPE;
BEGIN
BEGIN
SELECT stale_stats
INTO v_stale
FROM user_tab_statistics
WHERE table_name = p_tblname
AND object_type = 'TABLE';
EXCEPTION
WHEN NO_DATA_FOUND THEN
v_stale := 'YES';
END;
IF v_stale = 'YES' THEN
dbms_stats.gather_table_stats(ownname=>myschema,
tabname=> p_tblname,
partname=>p_partname,
degree=>dbms_stats.auto_degree,
granularity=>'APPROX_GLOBAL AND PARTITION') ;
ELSE
dbms_stats.gather_table_stats(ownname=>myschema,
tabname=>p_tblname,
partname=>p_partname,
degree=>dbms_stats.auto_degree,
granularity=>'PARTITION') ;
END IF;
END gather_tb_partiz;
At the end of each ETL, if the number of added/deleted/modified rows is low enough not to mark the table as stale (10% by default, can be tuned with STALE_PERCENT parameter), I collect only partition statistics; otherwise i collect global and partition statistics.
This keeps ETL of small partition fast, because no global partition must be regathered, and big partition safe, because any subsequent query will have fresh statistics and will likely use an optimal plan.
Incremental stats is anyway enabled, so whenever the global has to be recalculated, it is pretty fast because aggregates partition level statistics and does not perform a full scan.
I am not sure if, with incremental enabled, "APPROX_GLOBAL AND PARTITION" and "GLOBAL AND PARTITION" do differ in something, because both incremental and approx do basically the same thing: aggregate stats and histograms without doing a full scan.
Have you tried to have incremental statistics on, but still explicitly name a partition to analyze?
dbms_stats.gather_table_stats(ownname=>myschema,
tabname=>big_table,
partname=>part,
degree=>dbms_stats.auto_degree);
For your table, stale (yesterday's) global stats are not as harmful as completely invalid partition stats (0 rows). I can propose 2 a bit alternative approaches that we use:
Have a separate GLOBAL stats gathering executed by your ETL tool right after all partitions are loaded. If it's taking too long, play with estimate_percent as dbms_stats.auto_degree will likely to be more than 1%
Gather the global (as well as all other stale) stats in a separate database job run later during the day, after all data is loaded into DW.
The key point is that stale statistics which differ only slightly from fresh are almost just as good. If statistics show you 0 rows, they'll kill any query.
Considering what you are trying to achieve, you need to run stats on specific intervals of time for all Partitions and not at the end of the process that loads each partition. It could be challenging if this is a live table and has constant data loads happening round the clock, but since these are LARGE DW tables I really doubt that's the case. So the best bet would be to collect stats at the end of loading all partitions, this will ensure that the statistics is collected for partitions where data has change or statistics are missing and update the global statistics based on the partition level statistics and synopsis.
However to do so, you need to turn on incremental feature for the table (11gR1).
EXEC DBMS_STATS.SET_TABLE_PREFS('<Owner>','BIG_TABLE','INCREMENTAL','TRUE');
At the end of every load, gather table statistics using GATHER_TABLE_STATS command. You don't need to specify the partition name. Also, do not specify the granularity parameter.
EXEC DBMS_STATS.GATHER_TABLE_STATS('<Owner>','BIG_TABLE');
Kindly check if you have used DBMS_STATS to set table preference to gather incremental statistics.This oracle blog explains that statistics will be gathered after each row affected.
Incremental statistics maintenance needs to gather statistics on any partition that will change the global or table level statistics. For instance, the min or max value for a column could change after just one row is inserted or updated in the table
BEGIN
DBMS_STATS.SET_TABLE_PREFS(myschema,'BIG_TABLE','INCREMENTAL','TRUE');
END;
I'm a bit rusty about it, so first of all a question:
did you try serializing partition loading? If so, how long and how well does statistics run? Notice that since loading time is so much smaller than statistics gathering, i guess this could also act as a temporary workaround.
Append hint does affects redo size, meaning the transaction just traces something, thus statistics may not reckon new data:
http://oracle-base.com/articles/misc/append-hint.php
Thinking out loud: since the direct path insert does append rows at the end of the partition and eventually updates metadata at the end, the already running thread gathering statistics could have read non-updated (stale) data. Thus it may not be a bug, and locking threads would accomplish nothing.
You may test this behaviour temporarily switching your table/partition to LOGGING, for instance, and see how it works (slower, of course, but it's a test). Can you do it?
EDIT: incremental stats should work anyway, even disabling a parallel statistics gathering, since it reiles on the incremental values no matter how they were collected:
https://blogs.oracle.com/optimizer/entry/incremental_statistics_maintenance_what_statistics
In Db trace, there is a query taking long time.Can some one explain what it means.Seems this is very generic oracle query and not involved with my custom tables.
select condition from cdef$ where rowid=:1;
Found the same query in multiple places in trc files(DB trace) and one among all have huge amount of elapsed time. So, what will be the solution to avoid taking such a long time. Am using 11g version oracle.
You're right, that is an example of Oracle's recursive SQL, the statements it runs against the data dictionary to support our application SQL. That particular statement is the query Oracle runs to get the Search Condition of a CHECK constraint. If you are inserting or updating rows in tables with check constraints you will see it a lot.
The actual statement shouldn't take too long to run, so it is unlikely to be the source of a performance problem. Unless you are running lots of insert statements with hard-coded values. Oracle will run that query every time it parses a fresh insert or update statement. That will get expensive if you're not using bind variables.