Re: Performance Improvement by reducing WAL for Update Operation

From: Robert Haas <robertmhaas(at)gmail(dot)com>
To: Amit Kapila <amit(dot)kapila16(at)gmail(dot)com>
Cc: Greg Smith <greg(at)2ndquadrant(dot)com>, Hari Babu <haribabu(dot)kommi(at)huawei(dot)com>, Mike Blackwell <mike(dot)blackwell(at)rrd(dot)com>, "pgsql-hackers(at)postgresql(dot)org" <pgsql-hackers(at)postgresql(dot)org>
Subject: Re: Performance Improvement by reducing WAL for Update Operation
Date: 2013-11-28 21:35:00
Message-ID: CA+TgmoZcLqZwToELm0t7JLNZH6jEKeqMGE3cctmpCh6tpKqP3Q@mail.gmail.com
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On Wed, Nov 27, 2013 at 9:31 AM, Amit Kapila <amit(dot)kapila16(at)gmail(dot)com> wrote:
> Sure, but to explore (a), the scope is bit bigger. We have below
> options to explore (a):
> 1. try to optimize existing algorithm as used in patch, which we have
> tried but ofcourse we can spend some more time to see if anything more
> can be tried out.
> 2. try fingerprint technique as suggested by you above.
> 3. try some other standard methods like vcdiff, lz4 etc.

Well, obviously, I'm hot on idea #2 and think that would be worth
spending some time on. If we can optimize the algorithm used in the
patch some more (option #1), that would be fine, too, but the code
looks pretty tight to me, so I'm not sure how successful that's likely
to be. But if you have an idea, sure.

As to #3, I took a look at lz4 and snappy but neither seems to have an
API for delta compression. vcdiff is a commonly-used output for delta
compression but doesn't directly address the question of what
algorithm to use to find matches between the old and new input; and I
suspect that when you go searching for algorithms to do that
efficiently, it's going to bring you right back to #2.

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

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