From: | Merlin Moncure <mmoncure(at)gmail(dot)com> |
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To: | Tom Lane <tgl(at)sss(dot)pgh(dot)pa(dot)us> |
Cc: | pgsql-bugs <pgsql-bugs(at)postgresql(dot)org> |
Subject: | Re: Introducing floating point cast into filter drastically changes row estimate |
Date: | 2012-11-06 21:30:11 |
Message-ID: | CAHyXU0xpEWSDYiJzoaUqcHEZDE7jxS3sN3mkYY1fJ-+5P4g+ig@mail.gmail.com |
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Lists: | pgsql-bugs |
On Wed, Oct 24, 2012 at 5:40 PM, Merlin Moncure <mmoncure(at)gmail(dot)com> wrote:
> On Wed, Oct 24, 2012 at 3:51 PM, Merlin Moncure <mmoncure(at)gmail(dot)com> wrote:
>> On Wed, Oct 24, 2012 at 3:33 PM, Tom Lane <tgl(at)sss(dot)pgh(dot)pa(dot)us> wrote:
>>> Merlin Moncure <mmoncure(at)gmail(dot)com> writes:
>>>> Yeah -- I have a case where a large number of joins are happening that
>>>> have a lot of filtering based on expressions and things like that.
>>>
>>> Might be worth your while to install some indexes on those expressions,
>>> if only to trigger collection of stats about them.
>>
>> Not practical -- these expressions are all about 'outlier culling'.
>> It's just wasteful to materialize indexes for stastical purposes only.
>> Anyways, in this case, I just refactored the query into a CTE.
Apologies for blabbing, but I was wondering if a solution to this
problem might be to have the planner identify low cost/high impact
scenarios that would qualify for simply running some of the stored
statistical values through qualifying stable expressions, particularly
when the input variables are constant or single sourced from a table.
Over the years, the planner has been getting very precise in terms of
algorithm choice and this is making the costs of statistics misses
increasingly dangerous, a trend which I think has been reflected by
regression reports on -performance.
merlin
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