From: Cédric Villemain <cedric@2ndquadrant.com>
To: pgsql-performance@postgresql.org
Cc: Josh Berkus <josh@agliodbs.com>
Cc: Peter van Hardenberg <pvh@pvh.ca>
Cc: Jeff Janes <jeff.janes@gmail.com>
Cc: Scott Marlowe <scott.marlowe@gmail.com>
Subject: Re: random_page_cost = 2.0 on Heroku Postgres
Date: Fri, 10 Feb 2012 20:48:07 +0100
Message-ID: <201202102048.07495.cedric@2ndquadrant.com> (raw)
In-Reply-To: <4F3570E2.2070301@agliodbs.com>
References: <CAAcg=kWsjAXRNt0sSjsF-Ft+NfZi30Owa=-PGvghSJ6A0jeVYQ@mail.gmail.com>
<CAAcg=kXOiAi66tzP6hdFTSECjvKjLx65jUcMYQ1g3j4XdzOWDw@mail.gmail.com>
<4F3570E2.2070301@agliodbs.com>
Le vendredi 10 février 2012 20:32:50, Josh Berkus a écrit :
> On 2/9/12 2:41 PM, Peter van Hardenberg wrote:
> > Hmm, perhaps we could usefully aggregate auto_explain output.
>
> The other option is to take a statistical approach. After all, what you
> want to do is optimize average response times across all your user's
> databases, not optimize for a few specific queries.
>
> So one thought would be to add in pg_stat_statements to your platform
> ... something I'd like to see Heroku do anyway. Then you can sample
> this across dozens (or hundreds) of user databases, each with RPC set to
> a slightly different level, and aggregate it into a heat map.
>
> That's the way I'd do it, anyway.
in such set up, I sometime build a ratio between transactions processed and
CPU usage, many indicators exists, inside and outside DB, that are useful to
combine and use just as a 'this is normal behavior'. It turns to be easy in
the long term to see if things go better or worse.
--
Cédric Villemain +33 (0)6 20 30 22 52
http://2ndQuadrant.fr/
PostgreSQL: Support 24x7 - Développement, Expertise et Formation
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To: pgsql-performance@postgresql.org
Cc: cedric@2ndquadrant.com, josh@agliodbs.com, pvh@pvh.ca, jeff.janes@gmail.com, scott.marlowe@gmail.com
Subject: Re: random_page_cost = 2.0 on Heroku Postgres
In-Reply-To: <201202102048.07495.cedric@2ndquadrant.com>
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