Re: [HACKERS] Slow count(*) again...

From: Robert Haas <robertmhaas(at)gmail(dot)com>
To: david(at)lang(dot)hm
Cc: Vitalii Tymchyshyn <tivv00(at)gmail(dot)com>, Jon Nelson <jnelson+pgsql(at)jamponi(dot)net>, Mladen Gogala <mladen(dot)gogala(at)vmsinfo(dot)com>, Andrew Dunstan <andrew(at)dunslane(dot)net>, Bruce Momjian <bruce(at)momjian(dot)us>, Tom Lane <tgl(at)sss(dot)pgh(dot)pa(dot)us>, Craig Ringer <craig(at)postnewspapers(dot)com(dot)au>, "pgsql-performance(at)postgresql(dot)org" <pgsql-performance(at)postgresql(dot)org>
Subject: Re: [HACKERS] Slow count(*) again...
Date: 2011-02-04 02:05:52
Message-ID: AANLkTikN14hsVVVLJ=BQdqEcpmzkLLqSbEpqx-th4Ohx@mail.gmail.com
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On Thu, Feb 3, 2011 at 8:37 PM, <david(at)lang(dot)hm> wrote:
> On Thu, 3 Feb 2011, Robert Haas wrote:
>
>> On Thu, Feb 3, 2011 at 7:39 PM,  <david(at)lang(dot)hm> wrote:
>>>>
>>>> Yeah, but you'll be passing the entire table through this separate
>>>> process that may only need to see 1% of it or less on a large table.
>>>> If you want to write the code and prove it's better than what we have
>>>> now, or some other approach that someone else may implement in the
>>>> meantime, hey, this is an open source project, and I like improvements
>>>> as much as the next guy.  But my prediction for what it's worth is
>>>> that the results will suck.  :-)
>>>
>>> I will point out that 1% of a very large table can still be a lot of disk
>>> I/O that is avoided (especially if it's random I/O that's avoided)
>>
>> Sure, but I think that trying to avoid it will be costly in other ways
>> - you'll be streaming a huge volume of data through some auxiliary
>> process, which will have to apply some algorithm that's very different
>> from the one we use today.  The reality is that I think there's little
>> evidence that the way we do ANALYZE now is too expensive.  It's
>> typically very cheap and works very well.  It's a bit annoying when it
>> fires off in the middle of a giant data load, so we might need to
>> change the time of it a little, but if there's a problem with the
>> operation itself being too costly, this is the first I'm hearing of
>> it.  We've actually worked *really* hard to make it cheap.
>
> I could be misunderstanding things here, but my understanding is that it's
> 'cheap' in that it has little impact on the database while it is running.

I mean that it's cheap in that it usually takes very little time to complete.

> the issue here is that the workflow is
>
> load data
> analyze
> start work
>
> so the cost of analyze in this workflow is not "1% impact on query speed for
> the next X time", it's "the database can't be used for the next X time while
> we wait for analyze to finish running"

OK.

> I don't understand why the algorithm would have to be so different than
> what's done today, surely the analyze thread could easily be tweaked to
> ignore the rest of the data (assuming we don't have the thread sending the
> data to analyze do the filtering)

If you want to randomly pick 10,000 rows out of all the rows that are
going to be inserted in the table without knowing in advance how many
there will be, how do you do that? Maybe there's an algorithm, but
it's not obvious to me. But mostly, I question how expensive it is to
have a second process looking at the entire table contents vs. going
back and rereading a sample of rows at the end. I can't remember
anyone ever complaining "ANALYZE took too long to run". I only
remember complaints of the form "I had to remember to manually run it
and I wish it had just happened by itself".

--
Robert Haas
EnterpriseDB: http://www.enterprisedb.com
The Enterprise PostgreSQL Company

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