Alvaro Herrera wrote:
No amount of tinkering is going to change the fact that a seqscan is the fastest way to execute these queries. Even if you got it to be all in memory, it would still be much slower than the other systems which, I gather, are using columnar storage and thus are perfectly suited to this problem (unlike Postgres). The talk about "compression ratios" caught me by surprise until I realized it was columnar stuff. There's no way you can get such high ratios on a regular, row-oriented storage.
One of the "good tricks" with Postgres is to convert a very wide table into a set of narrow tables, then use a view to create something that looks like the original table. It requires you to modify the write portions of your app, but the read portions can stay the same. A seq scan on one column will *much* faster when you rearrange your database this way since it's only scanning relevant data. You pay the price of an extra join on primary keys, though. If you have just a few columns in a very wide table that are seq-scanned a lot, you can pull out just those columns and leave the rest in the wide table. The same trick is also useful if you have one or a few columns that are updated frequently: pull them out, and use a view to recreate the original appearance. It saves a lot on garbage collection. Craig -- Sent via pgsql-performance mailing list (pgsql-performance@xxxxxxxxxxxxxx) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
