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Re: Perform streaming logical transactions by background workers and parallel apply

Masahiko Sawada <sawada.mshk@gmail.com>

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From: Masahiko Sawada <sawada.mshk@gmail.com>
To: "shiy.fnst@fujitsu.com" <shiy.fnst@fujitsu.com>
Cc: Amit Kapila <amit.kapila16@gmail.com>, "houzj.fnst@fujitsu.com" <houzj.fnst@fujitsu.com>, "wangw.fnst@fujitsu.com" <wangw.fnst@fujitsu.com>, Dilip Kumar <dilipbalaut@gmail.com>, PostgreSQL Hackers <pgsql-hackers@lists.postgresql.org>, Peter Smith <smithpb2250@gmail.com>
Date: 2022-10-28T00:47:08Z
Lists: pgsql-hackers 
On Thu, Oct 27, 2022 at 11:34 AM shiy.fnst@fujitsu.com
<shiy.fnst@fujitsu.com> wrote:
>
> On Wed, Oct 26, 2022 7:19 PM Amit Kapila <amit.kapila16@gmail.com> wrote:
> >
> > On Tue, Oct 25, 2022 at 8:38 AM Masahiko Sawada
> > <sawada.mshk@gmail.com> wrote:
> > >
> > > On Fri, Oct 21, 2022 at 6:32 PM houzj.fnst@fujitsu.com
> > > <houzj.fnst@fujitsu.com> wrote:
> > >
> > > I've started to review this patch. I tested v40-0001 patch and have
> > > one question:
> > >
> > > IIUC even when most of the changes in the transaction are filtered out
> > > in pgoutput (eg., by relation filter or row filter), the walsender
> > > sends STREAM_START. This means that the subscriber could end up
> > > launching parallel apply workers also for almost empty (and streamed)
> > > transactions. For example, I created three subscriptions each of which
> > > subscribes to a different table. When I loaded a large amount of data
> > > into one table, all three (leader) apply workers received START_STREAM
> > > and launched their parallel apply workers.
> > >
> >
> > The apply workers will be launched just the first time then we
> > maintain a pool so that we don't need to restart them.
> >
> > > However, two of them
> > > finished without applying any data. I think this behaviour looks
> > > problematic since it wastes workers and rather decreases the apply
> > > performance if the changes are not large. Is it worth considering a
> > > way to delay launching a parallel apply worker until we find out the
> > > amount of changes is actually large?
> > >
> >
> > I think even if changes are less there may not be much difference
> > because we have observed that the performance improvement comes from
> > not writing to file.
> >
> > > For example, the leader worker
> > > writes the streamed changes to files as usual and launches a parallel
> > > worker if the amount of changes exceeds a threshold or the leader
> > > receives the second segment. After that, the leader worker switches to
> > > send the streamed changes to parallel workers via shm_mq instead of
> > > files.
> > >
> >
> > I think writing to file won't be a good idea as that can hamper the
> > performance benefit in some cases and not sure if it is worth.
> >
>
> I tried to test some cases that only a small part of the transaction or an empty
> transaction is sent to subscriber, to see if using streaming parallel will bring
> performance degradation.
>
> The test was performed ten times, and the average was taken.
> The results are as follows. The details and the script of the test is attached.
>
> 10% of rows are sent
> ----------------------------------
> HEAD            24.4595
> patched         18.4545
>
> 5% of rows are sent
> ----------------------------------
> HEAD            21.244
> patched         17.9655
>
> 0% of rows are sent
> ----------------------------------
> HEAD            18.0605
> patched         17.893
>
>
> It shows that when only 5% or 10% of rows are sent to subscriber, using parallel
> apply takes less time than HEAD, and even if all rows are filtered there's no
> performance degradation.

Thank you for the testing!

I think this performance improvement comes from both applying changes
in parallel to receiving changes and avoiding writing a file. I'm
happy to know there is also a benefit also for small streaming
transactions. I've also measured the overhead when processing
streaming empty transactions and confirmed the overhead is negligible.

Regards,

-- 
Masahiko Sawada
Amazon Web Services: https://aws.amazon.com

Commits

Same data as JSON: GET /api/v1/messages/:b64id/commits the thread's linked commits as JSON, with link sources. API reference →

  1. Fix invalid memory access during the shutdown of the parallel apply worker.

  2. Fix assertion failure in apply worker.

  3. Use elog to report unexpected action in handle_streamed_transaction().

  4. Use appropriate wait event when sending data in the apply worker.

  5. Allow the logical_replication_mode to be used on the subscriber.

  6. Rename GUC logical_decoding_mode to logical_replication_mode.

  7. Display the leader apply worker's PID for parallel apply workers.

  8. Improve the code to decide and process the apply action.

  9. Document the newly added wait events added by commit 216a784829.

  10. Perform apply of large transactions by parallel workers.

  11. Wake up a subscription's replication worker processes after DDL.

  12. Add copyright notices to meson files

  13. Better document logical replication parameters

  14. Add a common function to generate the origin name.

  15. Harmonize parameter names in storage and AM code.

  16. Avoid using list_length() to test for empty list.

  17. Improve two comments related to a boolean DefElem's value

  18. Fix partition table's REPLICA IDENTITY checking on the subscriber.

  19. Fix data inconsistency between publisher and subscriber.

  20. Fix cache look-up failures while applying changes in logical replication.