From: Rob Sargent <robjsargent@gmail.com>
To: pgsql-sql@postgresql.org
Subject: Extrapolating performance expectation
Date: Sun, 17 May 2009 22:04:46 -0600
Message-ID: <5c4ddc540905172104t1a91b829tc2848798a31df886@mail.gmail.com> (raw)
Can one extrapolate future performance expectations for ever-growing tables
from a given (non-trivial) data set, and if so with what curve? Corollary:
what would one expect a performance curve to approximate in terms of query
execution time v. number of data rows (hardware, load staying constant).
I have user and group information on system usage. I would like to be able
to do year-to-date counts per user given a single group id but in the data
for one business quarter the query is taking in between 10 and 60+ seconds
depending on both on the size of the group and the group's total usage.
Groups typically have 10-100 users and consume 20K - 80K records in a 9M
record data set. Group id column is indexed, but it is not the primary
index. (Sad note: two pseudo groups account for 50 percent of the total
records IIRC (and will never be used for the usage-by-group query below)
This is a single table query:
select user_id, element_type, count(*)
from dataset
where group_id = N
group by user_id, element_type
order by user_id, element_type
Is this the sort of situation which might benefit from increasing the number
of histogram bins (alter table alter column statistics (N>10))?
Any and all pointers appreciated,
Reply instructions:
You may reply publicly to this message via plain-text email
using any one of the following methods:
* Reply to all the recipients using the --to and --cc options:
reply via email
To: pgsql-sql@postgresql.org
Cc: robjsargent@gmail.com
Subject: Re: Extrapolating performance expectation
In-Reply-To: <5c4ddc540905172104t1a91b829tc2848798a31df886@mail.gmail.com>
* Save the following mbox file, import it into your mail client,
and reply-to-all from there: mbox
This inbox is served by DDX for PostgreSQL; see mirroring instructions
for how to clone and mirror all data and code used for this inbox