In this case either your nologging hint is ignored if you have force
logging at db level or you are breaking the synchronization between DBs.
You might want to check this aspect.
On Mon, Mar 29, 2021, 21:59 Lok P <loknath.73@xxxxxxxxx> wrote:
No Its active-active configuration in which replication happens through
the golden gate. So yes to answer your question it's not a data guard
configured environment.
On Tue, Mar 30, 2021 at 12:12 AM Laurentiu Oprea <
laurentiu.oprea06@xxxxxxxxx> wrote:
Out of curiosity the database is in a dataguard configuration?
On Mon, Mar 29, 2021, 21:30 Lothar Flatz <l.flatz@xxxxxxxxxx> wrote:
Lok,
I am afraid exchange partition will generally hardly help in your case.
Of course from the point of manageability a table of this size should be
range partitioned by date.
In addition I rather wonder about the usefulness of the list
partitioning if one partition holds 18billion rows out of total ~20billion.
700 million rows however are not that much. When I was RWPG member I had
once the opportunity to load 2 billion rows and a standard hardware. Took
15 minutes.
As Tim mentioned, it was likely not a direct path load in your case.
Can you shared an execution plan of the insert?
Thanks
Lothar
Am 29.03.2021 um 20:11 schrieb Lok P:
Thank you Tim. Actually we have the target table holding ~20billion rows
which is list-hash composite partitioned. It has two list partitions and
each list partition has a ~2048 hash subpartition. And we want to insert
into that target table around ~700+ million rows which is failing with
ora-01624.
Now I am unable to fully understand how we can utilize partition
exchange method here to load those ~700million rows. As because , I see
even all of those rows are meant for one of the list partitions(which
itself holds ~18billion rows out of total ~20billion) but were spread
across ~2048 hash subpartitions. So do you mean to say, we should load
~18billion rows into a similar structure stage table(without index with
same list-hash composite partition) and also load those additional
~700million those are missing (and it should succeed as it wont have
indexes now so zero UNDO with APPEND INSERT) and then do the truncate of
the list partition and then do the partition exchange with stage table?
On Mon, Mar 29, 2021 at 2:45 AM Tim Gorman <tim.evdbt@xxxxxxxxx> wrote:
Lok,
Ora-01628 max extent 32765 reached for rollback segment
If you are running out of space on your rollback segments, then you are
not actually using direct path insert, APPEND or APPEND_VALUES hint
notwithstanding. The only undo you should be generating is for the DDL,
not the DML, and that should not max out anything.
Long story short: you really can not effectively perform direct-path
APPEND insert directly to that "live" table or partition with indexes. In
your case, you need to perform the direct-path insert to a hash-partitioned
table of the same logical "shape" as the list partition you are targeting,
then build indexes to match the main table when you are done loading, and
then finally use ALTER TABLE ... EXCHANGE PARTITION to swap it all with the
"live" partition(s) in the main table. If it helps, HERE
<http://evdbt.com/download/presentation-scaling-to-infinity-partitioning-data-warehouses-on-oracle-database/>is
a presentation on this technique and HERE
<http://evdbt.com/download/paper-scaling-to-infinity-partitioning-data-warehouses-on-oracle-database-2/>is
a corresponding white paper on the technique. Also, HERE
<http://evdbt.com/download/exchpart-sql/>is a PL/SQL package called
EXCHPART which contains procedures to automate the moves mentioned in the
white paper and presentation. Please don't consider EXCHPART as anything
more than a template, it is not intended as working code, particularly when
it must be adapted for your local coding culture and standards. Hopefully
it is a good start?
Oh also, there is no such thing as a NOLOGGING hint; nologging is an
attribute on the table or partition which is effective only with
direct-path insert operations, never with conventional-path INSERT, UPDATE,
or DELETE operations.
Hope this helps...
Thanks!
-Tim
On 3/27/2021 10:37 PM, Lok P wrote:
Hi Listers, we have one process in which we load ~50million daily
(using direct path insert.. INSERT APPEND ) to a target table which holds
~20billion rows(~1TB in size)) and is list -hash composite partitioned. ~2
list partition and ~2048 hash subpartitions. It has 4 indexes out of those
one is a composite primary key comprising of 5 columns.We have that data
load job failing since ~15-20 days without notice and it thus accumulated
~billion rows and the load process is now failing with (Ora-01628 max
extent 32765 reached for rollback segment).
So we thought of running it in a bulk collect method(append_values
hint) and commit in chunks of ~1million. But during that process we endup
seeing the data load is significantly slower , it was inserting ~1million
rows in ~40minutes. And we were not able to understand the reason but the
wait events were all showing "cell single block physical read" and the
object was the target load object. Means it was the INSERt which was
struggling. So we now endup having partial data loaded to the target i.e.
around ~40-50million loaded to the target. And as it has a primary key , we
have to delete the ~40-50million rows from the target table and then reload
it.
I was thinking if we should do the delete in bulk method with a chunk
of 1million , but again that will happen in a single thread and will be
significantly slow. So what is the best way to have those ~40-50million
data deleted from the target table(which holds a total ~20billion rows)?
And then I was also thinking , if we could make the index unusable and
perform the delete and then data load(which would happen with almost zero
UNDo in absence of INDEXes) , but then in that case it seems that DELETE
will need the PK index to fetch the rowids so we cant get rid of the PK
index then. So what is the best approach to go for the delete and data
load here without breaking data consistency in the target table?
So wanted to understand what is the best/faster approach to go for
delete and data load in this situation?
Regards
Lok
