Re: Table partitioning for maximum speed?

From: Jean-Luc Lachance <jllachan(at)nsd(dot)ca>
To: Vivek Khera <khera(at)kcilink(dot)com>
Cc: pgsql-general(at)postgresql(dot)org
Subject: Re: Table partitioning for maximum speed?
Date: 2003-10-10 21:23:50
Message-ID: 3F872366.54234DE6@nsd.ca
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BULL.

How many times does PG have to scan the whole table because of MVCC?
At least with partitioning there is a fighting chance that that won't be
necessary.
Queries that involve the field on which the table is partitioned execute
faster by an order of magnitude.
It also helps with vaccuming as PG can vaccum only one partition at a
time.
I have 17M row table where all records get frequently updated over a
year.
I would do my own partitioning with inheritance if it was not broken.
Partitioning would be a BIG plus in my book. So would visibility of
records but that is another fight.

JLL

Vivek Khera wrote:
>
> >>>>> "JB" == Jeff Boes <jboes(at)nexcerpt(dot)com> writes:
>
> JB> Will a query against a table of 0.5 million rows beat a query against
> JB> a table of 7 million rows by a margin that makes it worth the hassle
> JB> of supporting 15 "extra" tables?
>
> I think you'll be better off with a single table, as you won't have
> contention for the index pages in the cache.
>
> One thing to do is to reindex reasonably often (for PG < 7.4) to avoid
> index bloat, which will make them not fit in cache. Just check the
> size of your index in the pg_class table, and when it gets big,
> reindex (assuming you do lots of updates/inserts to the table).
>
> Your table splitting solution sounds like something I'd do if I were
> forced to use mysql ;-)
>
> --
> =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
> Vivek Khera, Ph.D. Khera Communications, Inc.
> Internet: khera(at)kciLink(dot)com Rockville, MD +1-240-453-8497
> AIM: vivekkhera Y!: vivek_khera http://www.khera.org/~vivek/
>
> ---------------------------(end of broadcast)---------------------------
> TIP 9: the planner will ignore your desire to choose an index scan if your
> joining column's datatypes do not match

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