From: Andrew Dunstan <andrew@dunslane.net>
To: Tom Lane <tgl@sss.pgh.pa.us>
Cc: Thomas Kellerer <spam_eater@gmx.net>
Cc: pgsql-performance@postgresql.org
Subject: Re: query optimization
Date: Thu, 26 Apr 2012 16:27:38 -0400
Message-ID: <4F99AFBA.4090605@dunslane.net> (raw)
In-Reply-To: <13222.1335470935@sss.pgh.pa.us>
References: <alpine.DEB.2.02.1204241008570.9591@krichy.tvnetwork.hu>
<12228.1335467838@sss.pgh.pa.us>
<jnc860$q30$1@dough.gmane.org>
<13222.1335470935@sss.pgh.pa.us>
On 04/26/2012 04:08 PM, Tom Lane wrote:
> Thomas Kellerer<spam_eater@gmx.net> writes:
>> Tom Lane wrote on 26.04.2012 21:17:
>>> Um ... did you analyze all the tables, or just some of them? I get
>>> sub-millisecond runtimes if all four tables have been analyzed, but it
>>> does seem to pick lousy plans if, say, only a and b have been analyzed.
>> Here it's similar to Richard's experience:
>> Before analyzing the four tables, the first statement yields this plan:
>> [ merge joins ]
>> This continues to stay the plan for about 10-15 repetitions, then it turns to this plan
>> [ hash joins ]
> Hmm. I see it liking the merge-join plan (with minor variations) with
> or without analyze data, but if just some of the tables have been
> analyzed, it goes for the hash plan which is a good deal slower. The
> cost estimates aren't that far apart though. In any case, the only
> reason the merge join is so fast is that the data is perfectly ordered
> in each table; on a less contrived example, it could well be a lot
> slower.
>
It's not so terribly contrived, is it? It's common enough to have tables
which are append-only and to join them by something that corresponds to
the append order (serial field, timestamp etc.)
cheers
andrew
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To: pgsql-performance@postgresql.org
Cc: andrew@dunslane.net, tgl@sss.pgh.pa.us, spam_eater@gmx.net
Subject: Re: query optimization
In-Reply-To: <4F99AFBA.4090605@dunslane.net>
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