Re: cross column correlation revisted

From: Hans-Jürgen Schönig <postgres(at)cybertec(dot)at>
To: Dimitri Fontaine <dim(at)tapoueh(dot)org>
Cc: eggyknap(at)gmail(dot)com, tgl(at)sss(dot)pgh(dot)pa(dot)us, heikki(dot)linnakangas(at)enterprisedb(dot)com, pgsql-hackers(at)postgresql(dot)org, zb(at)cybertec(dot)at
Subject: Re: cross column correlation revisted
Date: 2010-07-15 10:04:21
Message-ID: 7EA01A14-3D58-4E9F-89CF-AB83044A2F40@cybertec.at
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hello ...

a view is already nice but i think it is still too narrow.
the problem is: you don't want a view for every potential join.
in addition to that - ideally there is not much left of a view when it comes to checking for costs.
so, i think, this is not the kind of approach leading to total success here.

one side question: does anybody happen to know how this is one in oracle or db2?

many thanks,

hans

On Jul 15, 2010, at 1:33 AM, Dimitri Fontaine wrote:

> Joshua Tolley <eggyknap(at)gmail(dot)com> writes:
>>>>> ALTER TABLE x SET CORRELATION STATISTICS FOR (x.id =3D y.id AND x.id=
> 2 =3D y.id2)
>>>> =20
>>> it says X and Y ... the selectivity of joins are what i am most
>>> interested in. cross correlation of columns within the same table are
>>> just a byproduct. the core thing is: how can i estimate the number
>>> of rows returned from a join?
>>
>> All the discussion of this topic that I've seen has been limited to the s=
> ingle
>> table case. The hard problem in that case is coming up with something you=
> can
>> precalculate that will actually be useful during query planning, without
>> taking too much disk, memory, CPU, or something else. Expanding the discu=
> ssion
>> to include join relations certainly still has valid use cases, but is even
>> harder, because you've also got to keep track of precisely how the underl=
> ying
>> relations are joined, so you know in what context the statistics remain v=
> alid.
>
> Well I've been proposing to handle the correlation problem in another
> way in some past mails here, and I've been trying to write it down too:
>
> http://archives.postgresql.org/pgsql-performance/2009-06/msg00118.php
> http://tapoueh.org/char10.html#sec13
>
> What I propose is to extend ANALYZE to be able to work on a VIEW too,
> rather than just a table. The hard parts seems to be:
>
> a. what stats to record, exploiting the view definition the best we can
> b. how to match a user query against the view definitions we have in
> order to actually use the stats
>
> If you have answers or good ideas=C2=A0:)
>
> Regards,
> --=20
> dim
>
>
> --
> dim
>

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