On Fri, 20 Mar 2009, Will Rutherdale (rutherw) wrote:
> However, keeping the KISS principle in mind, you can create a benchmark
> that simply sets up a sample database and forks off a bunch of processes
> to do random updates for an hour, say. Dead simple.
There's a benchmark tool that does something like this that comes with
PostgreSQL named pgbench. A MySQL-oriented tool named sysbench also can
do that, and it supports running against PostgreSQL as well--badly though,
so it's hard to use that to do a fair comparison.
Simple benchmarks tend to measure only one thing though, and it's often
not what you think you're measuring. For example, pgbench produces a
transactions/per second number. It's useful for comparing the relative
performance between two PostgreSQL instances, and people think it gives
you an idea of transactional performance. What the actual magnitude of
the result measures in many cases is instead how well the generated data
set fits in cache.
If you're doing something update heavy, a lot of the time what you
actually will measure is how fast your disk can seek, process a disk
commit done using fsync, or some combination of the two. If you're not
careful to make sure you're using the same level of disk commit guarantee
on both installations, it's real easy to get bad benchmark results here.
The intro to that subject from the PostgreSQL perspective is at
http://www.postgresql.org/docs/8.3/static/wal-reliability.html
On MySQL, the parameters that controls this behavior are described
starting at
http://dev.mysql.com/doc/refman/5.1/en/innodb-parameters.html#sysvar_innodb_flush_log_at_trx_commit
For something with lots of disk commits, it's critical that you have both
systems configured identically here.
--
* Greg Smith gsmith@gregsmith.com http://www.gregsmith.com Baltimore, MD