From: | Tomas Vondra <tomas(dot)vondra(at)2ndquadrant(dot)com> |
---|---|
To: | Robert Haas <robertmhaas(at)gmail(dot)com> |
Cc: | Andres Freund <andres(at)anarazel(dot)de>, "pgsql-hackers(at)postgresql(dot)org" <pgsql-hackers(at)postgresql(dot)org> |
Subject: | Re: alternative compression algorithms? |
Date: | 2015-04-29 22:55:06 |
Message-ID: | 5541614A.5030208@2ndquadrant.com |
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Lists: | pgsql-hackers |
Hi,
On 04/29/15 23:54, Robert Haas wrote:
> On Mon, Apr 20, 2015 at 9:03 AM, Tomas Vondra
> <tomas(dot)vondra(at)2ndquadrant(dot)com> wrote:
>> Sure, it's not an ultimate solution, but it might help a bit. I do have
>> other ideas how to optimize this, but in the planner every milisecond
>> counts. Looking at 'perf top' and seeing pglz_decompress() in top 3.
>
> I suggested years ago that we should not compress data in
> pg_statistic. Tom shot that down, but I don't understand why. It
> seems to me that when we know data is extremely frequently accessed,
> storing it uncompressed makes sense.
I'm not convinced not compressing the data is a good idea - it suspect
it would only move the time to TOAST, increase memory pressure (in
general and in shared buffers). But I think that using a more efficient
compression algorithm would help a lot.
For example, when profiling the multivariate stats patch (with multiple
quite large histograms), the pglz_decompress is #1 in the profile,
occupying more than 30% of the time. After replacing it with the lz4,
the data are bit larger, but it drops to ~0.25% in the profile and
planning the drops proportionally.
It's not a silver bullet, but it would help a lot in those cases.
--
Tomas Vondra http://www.2ndQuadrant.com
PostgreSQL Development, 24x7 Support, Remote DBA, Training & Services
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