Re: UPDATEDs slowing SELECTs in a fully cached database - Mailing list pgsql-performance

From ktm@rice.edu
Subject Re: UPDATEDs slowing SELECTs in a fully cached database
Date
Msg-id 20110711161458.GD14305@staff-mud-56-27.rice.edu
Whole thread Raw
In response to Re: UPDATEDs slowing SELECTs in a fully cached database  (Robert Klemme <shortcutter@googlemail.com>)
List pgsql-performance
On Mon, Jul 11, 2011 at 05:26:49PM +0200, Robert Klemme wrote:
> On Mon, Jul 11, 2011 at 3:13 PM, ktm@rice.edu <ktm@rice.edu> wrote:
> > I do not know if this makes sense in PostgreSQL and that readers
> > do not block writers and writes do not block readers. Are your
> > UPDATEs to individual rows, each in a separate transaction, or
> > do you UPDATE multiple rows in the same transaction? If you
> > perform multiple updates in a single transaction, you are
> > synchronizing the changes to that set of rows and that constraint
> > is causing other readers that need to get the correct values post-
> > transaction to wait until the COMMIT completes. This means that
> > the WAL write must be completed.
>
> What readers should that be?  Docs explicitly state that readers are
> never blocked by writers:
> http://www.postgresql.org/docs/9.0/interactive/mvcc-intro.html
> http://www.postgresql.org/docs/9.0/interactive/mvcc.html
>
> From what I understand about this issue the observed effect must be
> caused by the implementation and not by a conceptual issue with
> transactions.
>
> > Have you tried disabling synchronous_commit? If this scenario
> > holds, you should be able to reduce the slowdown by un-batching
> > your UPDATEs, as counter-intuitive as that is. This seems to
> > be similar to a problem that I have been looking at with using
> > PostgreSQL as the backend to a Bayesian engine. I am following
> > this thread with interest.
>
> I don't think this will help (see above).  Also, I would be very
> cautious to do this because although the client might get a faster
> acknowledge the DB still has to do the same work as without
> synchronous_commit (i.e. WAL, checkpointing etc.) but it still has to
> do significantly more transactions than in the batched version.
>
> Typically there is an optimum batch size: if batch size is too small
> (say, one row) the ratio of TX overhead to "work" is too bad.  If
> batch size is too large (say, millions of rows) you hit resource
> limitations (memory) which inevitable force the RDBMS to do additional
> disk IO.
>
> Kind regards
>
> robert
>
Okay,

If we assume that the current implementation of MVCC is preventing
readers from blocking writers and writers from blocking readers, then
the application may have some statements that are implicitly locking
the database and that is conflicting with the UPDATEs. Maybe the
slowdown is caused by index updates caused by the write activity.
Just throwing out some ideas.

Regards,
Ken
regarding index updates with the read-only queries.
> --
> remember.guy do |as, often| as.you_can - without end
> http://blog.rubybestpractices.com/
>

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