From: Tomas Vondra <tv@fuzzy.cz>
To: pgsql-performance@postgresql.org
Subject: Re: Slow query postgres 8.3
Date: Wed, 13 Apr 2011 22:16:35 +0200
Message-ID: <4DA604A3.502@fuzzy.cz> (raw)
In-Reply-To: <BANLkTin7x1t4dhjqpSa6+EJ2MEeWmSNNwg@mail.gmail.com>
References: <945629628BB0174D86709AFE6D1CDEF5017A66C1@SP-EXCHMBC.sp.corp.collab.net>
<50d8f2eb94b393c11221c9d5232d7326.squirrel@sq.gransy.com>
<945629628BB0174D86709AFE6D1CDEF5017A66E3@SP-EXCHMBC.sp.corp.collab.net>
<4DA2ED2F020000250003C657@gw.wicourts.gov>
<BANLkTin7x1t4dhjqpSa6+EJ2MEeWmSNNwg@mail.gmail.com>
Dne 12.4.2011 09:33, Claudio Freire napsal(a):
> I actually implemented a statistical system for measuring these kinds
> of correlations.
>
> It's complex, but it might be adaptable to pgsql. Furthermore, one of
> the latest projects of mine was to replace the purely statistical
> approach with SVCs.
You mean Support Vector Classifiers? Interesting idea, although I don't
see how to apply that to query planning, especially with non-numeric
inputs. Could you share more details on that statistical system and how
do you think it could be applied in the pgsql world?
> Too bad I won't be able to devote any time to that project before september.
I've been working on cross column stats for some time, and although I
had to put it aside for some time I'm going to devote more time to this
issue soon. So interesting ideas/comments are very welcome.
regards
Tomas
Reply instructions:
You may reply publicly to this message via plain-text email
using any one of the following methods:
* Reply to all the recipients using the --to and --cc options:
reply via email
To: pgsql-performance@postgresql.org
Cc: tv@fuzzy.cz
Subject: Re: Slow query postgres 8.3
In-Reply-To: <4DA604A3.502@fuzzy.cz>
* Save the following mbox file, import it into your mail client,
and reply-to-all from there: mbox
This inbox is served by DDX for PostgreSQL; see mirroring instructions
for how to clone and mirror all data and code used for this inbox