Phoenix Kiula wrote:
> [Ppsted similar note to PG General but I suppose it's more appropriate
> in this list. Apologies for cross-posting.]
>
> Hi. Further to my bafflement with the "count(*)" queries as described
> in this thread:
>
> http://archives.postgresql.org/pgsql-general/2009-01/msg00804.php
>
> It seems that whenever this question has come up, Postgresql comes up
> very short in terms of "count(*)" functions.
Sorry - I'm confused. That thread doesn't seem to contain a slow
count(*) query. You seem to be saying you're having problems with the
query taking 10-15 seconds, but the example takes less then half a
second. How have you identified the count() as being the problem here?
> The performance is always slow, because of the planner's need to guess
> and such. I don't fully understand how the statistics work (and the
> explanation on the PG website is way too geeky) but he columns I work
> with already have a stat level of 100. Not helping at all.
But your own email says it's slow sometimes:
"My queries are fast in general *except* the first time"
I'm not sure how the planner comes into this.
> We are now considering a web based logging functionality for users of
> our website. This means the table could be heavily INSERTed into. We
> get about 10 million hits a day, and I'm guessing that we will have to
> keep this data around for a while.
>
> My question: with that kind of volume and the underlying aggregation
> functions (by product id, dates, possibly IP addresses or at least
> countries of origin..) will PG ever be a good choice?
A good choice compared to what?
> Or should I be
> looking at some other kind of tools? I wonder if OLAP tools would be
> overkill for something that needs to look like a barebones version of
> google analytics limited to our site..
Typically you'd summarise the data by hour/day via triggers / a
scheduled script if you weren't going towards a pre-packaged OLAP
toolkit. Otherwise you're going to have to scan the hundreds of millions
of rows you've accumulated.
> Appreciate any thoughts. If possible I would prefer to tone down any
> requests for MySQL and such!
I'm not sure MySQL is going to help you here - if you were running lots
of small, simple queries it might make sense. If you want to aggregate
data by varying criteria I don't think there is any sensible
optimisation (other than pre-calculating summaries).
--
Richard Huxton
Archonet Ltd
