Re: again on index usage - Mailing list pgsql-hackers

From Bruce Momjian
Subject Re: again on index usage
Date
Msg-id 200201101940.g0AJePW08772@candle.pha.pa.us
Whole thread Raw
In response to Re: again on index usage  ("Zeugswetter Andreas SB SD" <ZeugswetterA@spardat.at>)
List pgsql-hackers
This topic seems to come up a lot.  Is there something we are missing in
the FAQ?

---------------------------------------------------------------------------

Zeugswetter Andreas SB SD wrote:
> 
> >  > > > What is actually estimated wrong here seems to be the estimated
> >  > > > effective cache size, and thus the cache ratio of page fetches.
> >  > > 
> >  > > Good point, but I think the estimates are only marginally sensitive
> >  > > to estimated cache size (if they're not, we have a problem, considering
> >  > > how poorly we can estimate the kernel's disk buffer size).  It would
> >  > > be interesting for Daniel to try a few different settings of
> >  > > effective_cache_size and see how much the EXPLAIN costs change.
> >  > 
> >  > Well, the number I told him (29370) should clearly prefer the index.
> >  > The estimate is very sensitive to this value :-(
> >  > With 29370 (=229 Mb) the index cost is 1,364 instead of 3,887 with the 
> >  > default of 1000 pages ==> index scan.
> > 
> > But... if I understand it right (effective_cache_size to be related to kernel 
> > buffer space). it turns out that the estimates are different with reality - my 
> > buffer cache is ca. 50 MB and I still get at least twice the performance with 
> > index scan instead of sequential scan - where as Tom explained things should 
> > be much worse.
> 
> Since pg only reads one 8k page at a time, the IO performance of a seq scan is
> probably not nearly a good as it could be when a lot of other IO is done on the
> same drive.
> 
> First thing you should verify is if there is actually a measurable difference
> in IO throughput on the pg drive during the seq scan and the index scan. (iostat)
> If there is not, then random_page_cost is too high in your scenario.
> (All assuming your data is not still clustered like Tom suggested)
> 
> Andreas
> 
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