Message-ID: <4C188AD4.20209@2ndquadrant.com>
Date: Wed, 16 Jun 2010 04:27:00 -0400
From: Greg Smith <greg@2ndquadrant.com>
User-Agent: Thunderbird 2.0.0.24 (X11/20100317)
MIME-Version: 1.0
To: "jgardner@jonathangardner.net" <jgardner@jonathangardner.net>
CC: pgsql-performance@postgresql.org
Subject: Re: PostgreSQL as a local in-memory cache
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>
In-Reply-To: 
 <4634b12c-749f-4605-9d95-121b8e2bd9e4@k17g2000pro.googlegroups.com>
Content-Type: text/plain; charset=ISO-8859-1; format=flowed
Content-Transfer-Encoding: 7bit

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