Timing things that are fairly simple is hard enough to do repeatedly, but when
it involves access to slower media and especially to network connections to
servers, the number of things that can change are enormous. There are all kinds
of caching at various levels depending on your hardware and resource contention
with other programs running here and there as well as on various network-like
structures and busses or just hard disks. Asking for anything to be repeated
multiple times in a row as a general rule can make your results seem slower or
faster depending on too many factors including what else is running on your
machine.
I am wondering if an approach to running something N times that may average
things out a bit is to simply put in a pause. Have your program wait a few
minutes between attempts and perhaps even do other things within your loop that
make it likely some of the resources you want not to be in a queue have a
chance to be flushed as other things take their place. Obviously, a machine or
system with lots of resources may take more effort to use enough new data that
replaces the old.
Good luck. Getting reliable numbers is no easy feat as someone else may have
trouble duplicating the results with a somewhat different setup.
-----Original Message-----
From: Python-list <python-list-bounces+avi.e.gross=gmail....@python.org> On
Behalf Of Albert-Jan Roskam via Python-list
Sent: Sunday, September 17, 2023 5:02 AM
To: Peter J. Holzer <hjp-pyt...@hjp.at>
Cc: python-list@python.org
Subject: Re: Postgresql equivalent of Python's timeit?
On Sep 15, 2023 19:45, "Peter J. Holzer via Python-list"
<python-list@python.org> wrote:
On 2023-09-15 17:42:06 +0200, Albert-Jan Roskam via Python-list wrote:
> This is more related to Postgresql than to Python, I hope this is
ok.
> I want to measure Postgres queries N times, much like Python timeit
> (https://docs.python.org/3/library/timeit.html). I know about
EXPLAIN
> ANALYZE and psql \timing, but there's quite a bit of variation in
the
> times. Is there a timeit-like function in Postgresql?
Why not simply call it n times from Python?
(But be aware that calling the same query n times in a row is likely to
be
unrealistically fast because most of the data will already be in
memory.)
=====
Thanks, I'll give this a shot. Hopefully the caching is not an issue if I
don't re-use the same database connection.
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