From: Greg Smith <greg@2ndquadrant.com>
To: jgardner@jonathangardner.net <jgardner@jonathangardner.net>
Cc: pgsql-performance@postgresql.org
Subject: Re: PostgreSQL as a local in-memory cache
Date: Wed, 16 Jun 2010 04:27:00 -0400
Message-ID: <4C188AD4.20209@2ndquadrant.com> (raw)
In-Reply-To: <4634b12c-749f-4605-9d95-121b8e2bd9e4@k17g2000pro.googlegroups.com>
References: <cb0fb58c-9134-4314-a1d0-08fc39f911a6@40g2000pry.googlegroups.com>
<87bpbcpabg.fsf@cbbrowne-laptop.afilias-int.info>
<4C17A417.2040600@noao.edu>
<87ocfcnqmk.fsf@cbbrowne-laptop.afilias-int.info>
<4C180A3B.7090905@agliodbs.com>
<4634b12c-749f-4605-9d95-121b8e2bd9e4@k17g2000pro.googlegroups.com>
jgardner@jonathangardner.net wrote:
> NOTE: If I do one giant commit instead of lots of littler ones, I get
> much better speeds for the slower cases, but I never exceed 5,500
> which appears to be some kind of wall I can't break through.
>
That's usually about where I run into the upper limit on how many
statements Python can execute against the database per second. Between
that and the GIL preventing better multi-core use, once you pull the
disk out and get CPU bound it's hard to use Python for load testing of
small statements and bottleneck anywhere except in Python itself.
I normally just write little performance test cases in the pgbench
scripting language, then I get multiple clients and (in 9.0) multiple
driver threads all for free.
--
Greg Smith 2ndQuadrant US Baltimore, MD
PostgreSQL Training, Services and Support
greg@2ndQuadrant.com www.2ndQuadrant.us
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To: pgsql-performance@postgresql.org
Cc: greg@2ndquadrant.com, jgardner@jonathangardner.net
Subject: Re: PostgreSQL as a local in-memory cache
In-Reply-To: <4C188AD4.20209@2ndquadrant.com>
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