|From:||Hannu Krosing <hannu(at)tm(dot)ee>|
|To:||Nikk Anderson <Nikk(dot)Anderson(at)parallel(dot)ltd(dot)uk>|
|Cc:||"\"'Charles H(dot) \"Woloszynski'" <chw(at)clearmetrix(dot)com>,pgsql-performance(at)postgresql(dot)org|
|Subject:||Re: selects from large tables|
|Views:||Raw Message | Whole Thread | Download mbox|
Nikk Anderson kirjutas K, 20.11.2002 kell 20:08:
> I tried a test cluster on a copy of our real data - all 10 million
> rows or so. WOW! The normal select performance improved
> Selecting 3 months worth of data was taking 146 seconds to retrieve.
> After clustering it took 7.7 seconds! We are now looking into ways we
> can automate clustering to keep the table up to date. The cluster
> itself took around 2.5 hours.
> As our backend systems are writing hundreds of rows of data in per
> minute into the table that needs clustering - will cluster handle
> locking the tables when dropping the old, and renaming the clustered
> data? What happens to the data being added to the table while cluster
> is running? Our backend systems may have some problems if the table
> does not exist when it tries to insert, and we don't want to lose any
You could use a staging table that takes all the inserts and the
contents of which are moved (begin;insert into big select from
small;delete from small;commit;vacuum full small;) to the main table
once a day (or week or month) just before clustering the big one.
Then do all your selects from a UNION view on both - thus you have a big
fast clustered table and non-clustered "live" table which stays small.
That should make your selects fast(er).
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