Re: benchmarking the query planner

From: Gregory Stark <stark(at)enterprisedb(dot)com>
To: Simon Riggs <simon(at)2ndQuadrant(dot)com>
Cc: Robert Haas <robertmhaas(at)gmail(dot)com>, Tom Lane <tgl(at)sss(dot)pgh(dot)pa(dot)us>, Kevin Grittner <Kevin(dot)Grittner(at)wicourts(dot)gov>, "jd\(at)commandprompt(dot)com" <jd(at)commandprompt(dot)com>, Josh Berkus <josh(at)agliodbs(dot)com>, Greg Smith <gsmith(at)gregsmith(dot)com>, pgsql-hackers(at)postgresql(dot)org
Subject: Re: benchmarking the query planner
Date: 2008-12-12 17:05:58
Message-ID: 87hc59s4qx.fsf@oxford.xeocode.com
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Simon Riggs <simon(at)2ndQuadrant(dot)com> writes:

> The amount of I/O could stay the same, just sample all rows on block.
> Lifting the sample size will help large tables. Will it be perfect? No.
> But I'll take "better" over "not working at all".

That will just raise the table size at which the problems start. It'll still
be a constant-sized sample.

It will also introduce strange biases. For instance in a clustered table it'll
think there are a lot more duplicates than there really are because it'll see
lots of similar values.

Incidentally we *do* do block sampling. We pick random blocks and then pick
random records within those blocks. This was new in, uh, 7.4? 8.0? Sometime
around then. It dramatically reduced the i/o requirements but there were long
discussions of how to do it without introducing biases.

> If we are going to quote literature we should believe all the
> literature. We can't just listen to some people that did a few tests
> with sample size, but then ignore the guy that designed the MS optimizer
> and many others.

I'm not sure what you're talking about regarding "some people that did a few
tests". I looked around for the paper I keep referencing and can't find it on
my laptop. I'll look for it online. But it included a section which was a
survey of past results from other papers and the best results required
stupidly large sample sizes to get anything worthwhile.

--
Gregory Stark
EnterpriseDB http://www.enterprisedb.com
Ask me about EnterpriseDB's On-Demand Production Tuning

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