Jeff Janes wrote:
On Sun, Aug 30, 2009 at 11:01 AM, Stefan Kaltenbrunner
<ste...@kaltenbrunner.cc> wrote:
Jeff Janes wrote:
---------- Forwarded message ----------
From: Stefan Kaltenbrunner <ste...@kaltenbrunner.cc>
To: Heikki Linnakangas <heikki.linnakan...@enterprisedb.com
<mailto:heikki.linnakan...@enterprisedb.com>
<mailto:heikki.linnakan...@enterprisedb.com
<mailto:heikki.linnakan...@enterprisedb.com>>>
Date: Sun, 30 Aug 2009 11:48:47 +0200
Subject: Re: LWLock Queue Jumping
Heikki Linnakangas wrote:
I don't have any pointers right now, but WALInsertLock does
often show
up as a bottleneck in write-intensive benchmarks.
yeah I recently ran accross that issue with testing
concurrent COPY
performance:
http://www.kaltenbrunner.cc/blog/index.php?/archives/27-Benchmarking-8.4-Chapter-2bulk-loading.html
discussed here:
http://archives.postgresql.org/pgsql-hackers/2009-06/msg01019.php
It looks like this is the bulk loading of data into unindexed
tables. How good is that as a target for optimization? I can
see several (quite difficult to code and maintain) ways to make
bulk loading into unindexed tables faster, but they would not
speed up the more general cases.
well bulk loading into unindexed tables is quite a common workload -
apart from dump/restore cycles (which we can now do in parallel) a
lot of analytic workloads are that way.
Import tons of data from various sources every night/weeek/month,
index, analyze & aggregate, drop again.
In those cases where you end by dropping the tables, we should be
willing to bypass WAL altogether, right? Is the problem we can bypass
WAL (by doing the COPY in the same transaction that created or truncated
the table), or we can COPY in parallel, but we can't do both simultaneously?
well yes that is part of the problem - if you bulk load into one or few
tables concurrently you can only sometimes make use of the WAL bypass
optimization. This is especially interesting if you consider that COPY
alone is more or less CPU bottlenecked these days so using multiple
cores makes sense to get higher load rates.
Stefan
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