From: | Tom Lane <tgl(at)sss(dot)pgh(dot)pa(dot)us> |
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To: | Samuel Gendler <sgendler(at)ideasculptor(dot)com> |
Cc: | pgsql-performance(at)postgresql(dot)org |
Subject: | Re: near identical queries have vastly different plans |
Date: | 2011-07-01 22:46:49 |
Message-ID: | 6960.1309560409@sss.pgh.pa.us |
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Lists: | pgsql-performance |
Samuel Gendler <sgendler(at)ideasculptor(dot)com> writes:
> I've got 2 nearly identical queries that perform incredibly differently.
The reason the slow query sucks is that the planner is estimating at
most one "s" row will match that complicated AND/OR condition, so it
goes for a nestloop. In the "fast" query there is another complicated
AND/OR filter condition, but it's not so far off on the number of
matching rows, so you get a better plan choice. Can't tell from the
given information whether the better guess is pure luck, or there's some
difference in the column statistics that makes it able to get a better
estimate for that.
In general, though, you're skating on thin ice anytime you ask the
planner to derive statistical estimates about combinations of correlated
columns --- and these evidently are correlated. Think about refactoring
the table definitions so that you're only testing a single column, which
ANALYZE will be able to provide stats about. Or maybe you can express
it as a test on a computed expression, which you could then keep an
index on, prompting ANALYZE to gather stats about that.
regards, tom lane
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