From: | Andrew Dunstan <andrew(at)dunslane(dot)net> |
---|---|
To: | Mischa Sandberg <mischa(dot)sandberg(at)telus(dot)net> |
Cc: | josh(at)agliodbs(dot)com, pgsql-perform <pgsql-performance(at)postgresql(dot)org>, pgsql-hackers(at)postgresql(dot)org |
Subject: | Re: [HACKERS] Bad n_distinct estimation; hacks suggested? |
Date: | 2005-04-27 13:43:31 |
Message-ID: | 426F9703.4010108@dunslane.net |
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Lists: | pgsql-hackers pgsql-performance |
Mischa Sandberg wrote:
>
>Perhaps I can save you some time (yes, I have a degree in Math). If I
>understand correctly, you're trying extrapolate from the correlation
>between a tiny sample and a larger sample. Introducing the tiny sample
>into any decision can only produce a less accurate result than just
>taking the larger sample on its own; GIGO. Whether they are consistent
>with one another has no relationship to whether the larger sample
>correlates with the whole population. You can think of the tiny sample
>like "anecdotal" evidence for wonderdrugs.
>
>
>
Ok, good point.
I'm with Tom though in being very wary of solutions that require even
one-off whole table scans. Maybe we need an additional per-table
statistics setting which could specify the sample size, either as an
absolute number or as a percentage of the table. It certainly seems that
where D/N ~ 0.3, the estimates on very large tables at least are way way
out.
Or maybe we need to support more than one estimation method.
Or both ;-)
cheers
andrew
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