Horton

Re: row filtering for logical replication

Ajin Cherian <itsajin@gmail.com>

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From: Ajin Cherian <itsajin@gmail.com>
To: Dilip Kumar <dilipbalaut@gmail.com>
Cc: Amit Kapila <amit.kapila16@gmail.com>, Euler Taveira <euler@eulerto.com>, Peter Smith <smithpb2250@gmail.com>, Rahila Syed <rahilasyed90@gmail.com>, Peter Eisentraut <peter.eisentraut@enterprisedb.com>, Önder Kalacı <onderkalaci@gmail.com>, japin <japinli@hotmail.com>, Michael Paquier <michael@paquier.xyz>, David Steele <david@pgmasters.net>, Craig Ringer <craig@2ndquadrant.com>, Tomas Vondra <tomas.vondra@2ndquadrant.com>, Amit Langote <amitlangote09@gmail.com>, PostgreSQL Hackers <pgsql-hackers@lists.postgresql.org>
Date: 2021-09-21T03:27:49Z
Lists: pgsql-hackers

Commits

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  1. Release cache tuple when no longer needed

  2. Add some additional tests for row filters in logical replication.

  3. Fix one of the tests introduced in commit 52e4f0cd47.

  4. Allow specifying row filters for logical replication of tables.

  5. Move scanint8() to numutils.c

  6. Replace Test::More plans with done_testing

  7. Reduce relcache access in WAL sender streaming logical changes

  8. Small cleanups related to PUBLICATION framework code

  9. Add a view to show the stats of subscription workers.

  10. Allow publishing the tables of schema.

  11. Doc: improve documentation of CREATE/ALTER SUBSCRIPTION.

  12. Add PublicationTable and PublicationRelInfo structs

  13. Remove unused argument "txn" in maybe_send_schema().

  14. Add prepare API support for streaming transactions in logical replication.

  15. Unify PostgresNode's new() and get_new_node() methods

  16. Use l*_node() family of functions where appropriate

  17. Add support for prepared transactions to built-in logical replication.

  18. Restore the portal-level snapshot after procedure COMMIT/ROLLBACK.

  19. Rename a parse node to be more general

  20. Remove unused column atttypmod from initial tablesync query

  21. SEARCH and CYCLE clauses

On Tue, Sep 21, 2021 at 12:03 AM Dilip Kumar <dilipbalaut@gmail.com> wrote:
>
> On Mon, Sep 20, 2021 at 5:37 PM Amit Kapila <amit.kapila16@gmail.com> wrote:
> > > >
> > >
> > > Adding a patch that strives to do the logic that I described above.
> > > For updates, the row filter is applied on both old_tuple
> > > and new_tuple. This patch assumes that the row filter only uses
> > > columns that are part of the REPLICA IDENTITY. (the current patch-set
> > > only
> > > restricts this for row-filters that are delete only)
> > > The old_tuple only has columns that are part of the old_tuple and have
> > > been changed, which is a problem while applying the row-filter. Since
> > > unchanged REPLICA IDENTITY columns
> > > are not present in the old_tuple, this patch creates a temporary
> > > old_tuple by getting such column values from the new_tuple and then
> > > applies the filter on this hand-created temp old_tuple. The way the
> > > old_tuple is created can be better optimised in future versions.
>
> I understand why this is done, but I have 2 concerns here 1) We are
> having extra deform and copying the field from new to old in case it
> is unchanged replica identity.  2) The same unchanged attribute values
> get qualified in the old tuple as well as in the new tuple.  What
> exactly needs to be done is that the only updated field should be
> validated as part of the old as well as the new tuple, the unchanged
> field does not make sense to have redundant validation.   For that we
> will have to change the filter for the old tuple to just validate the
> attributes which are actually modified and remaining unchanged and new
> values will anyway get validated in the new tuple.
>
But what if the filter expression depends on multiple columns, say (a+b) > 100
where a is unchanged while b is changed. Then we will still need both
columns for applying
the filter even though one is unchanged. Also, I am not aware of any
mechanism by which
we can apply a filter expression on individual attributes. The current
mechanism does it
on a tuple. Do let me know if you have any ideas there?

Even if it were done, there would still be the overhead of deforming the tuple.
I will run some performance tests like Amit suggested and see what the
overhead is and
try to minimise it.

regards,
Ajin Cherian
Fujitsu Australia