Re: PATCH: logical_work_mem and logical streaming of large in-progress transactions

On Thu, Dec 26, 2019 at 12:36 PM Masahiko Sawada
<masahiko(dot)sawada(at)2ndquadrant(dot)com> wrote:
>
> On Tue, 24 Dec 2019 at 17:21, Amit Kapila <amit(dot)kapila16(at)gmail(dot)com> wrote:
> >
> > >
> > > Thank you for explanation. The plan makes sense. But I think in the
> > > current design it's a problem that logical replication worker doesn't
> > > receive changes (and doesn't check interrupts) during applying
> > > committed changes even if we don't have a worker dedicated for
> > > applying. I think the worker should continue to receive changes and
> > > save them to temporary files even during applying changes.
> > >
> >
> > Won't it beat the purpose of this feature which is to reduce the apply
> > lag? Basically, it can so happen that while applying commit, it
> > constantly gets changes of other transactions which will delay the
> > apply of the current transaction.
>
> You're right. But it seems to me that it optimizes the apply lags of
> only a transaction that made many changes. On the other hand if a
> transaction made many changes applying of subsequent changes are
> delayed.
>

Hmm, how would it be worse than the current situation where once
commit is encountered on the publisher, we won't start with other
transactions until the replay of the same is finished on subscriber?

>
> > I think the best way as
> > discussed is to launch new workers for streamed transactions, but we
> > can do that as an additional feature. Anyway, as proposed, users can
> > choose the streaming mode for subscriptions, so there is an option to
> > turn this selectively.
>
> Yes. But user who wants to use this feature would want to replicate
> many changes but I guess the side effect is quite big. I think that at
> least we need to make the logical replication tolerate such situation.
>

What exactly you mean by "at least we need to make the logical
replication tolerate such situation."? Do you have something specific
in mind?

--
With Regards,
Amit Kapila.
EnterpriseDB: http://www.enterprisedb.com