Re: Including unique users in huge data warehouse in Postgresql...

Mark Jensen wrote:
> So i've been given the task of designing a data warehouse in
> either Postgresql or Mysql for our clickstream data for our sites.  I
> started with Mysql but the joins in Mysql are just way too slow
> compared to Postgresql when playing with star schemas.

Mark - it's not my usual area, but no-one else has picked up your
posting, so I'll poke my nose in. The other thing you might want to do
is post this on the performance list - that's probably the best place.
Might be worth talking to those at www.bizgres.org too (although I think
they all hang out on the performance list).

 > I can't say
> which sites i'm working on, but we get close to 3-5 million uniques
> users per day, so over time, that's a lot of unique users to keep
> around and de-dup your fact tables by.  Need to be able to query normal
> analytics like:
<snip>

> i've
> made a lot of optimizations in postgresql.conf by playing with work_mem
> and shared_buffers and such and i think the database is using as much
> as it can disk/memory/cpu wise.

Big work_mem, I'm guessing. Limiting factor is presumably disk I/O.

<snip>
> here's a sample query that takes a while to run... just a simple report that shows gender by area of the site.
>
> select A.gender as gender, B.area as area, sum(C.imps) as imps, sum(C.clicks) as clicks, count(distinct(C.uu_id)) as
users
> from uus as A, areas as B, daily_area_fact as C
> where A.uu_id = C.uu_id
> and B.area_id = C.area_id
> group by gender,area;
>
> so
> by just having one day of data, with 3,168,049 rows in the user
> dimension table (uus), 17,213,420 in the daily_area_fact table that
> joins all the dimension tables, takes about 15 minutes.  if i had 30-90
> days in this fact table, who knows how long this would take... i know
> doing a distinct on uu_id is very expensive, so that's the main problem
> here i guess and would want to know if anyone else is doing it this way
> or better.

In the end, I'd suspect the seq-scan over the fact table will be your
biggest problem. Can you pre-aggregate your fact-table into daily summaries?

See you over on the performance list, where there are more experienced
people than myself to help you.
--
   Richard Huxton
   Archonet Ltd