On Fri, May 2, 2008 at 2:26 PM, Alexy Khrabrov <[EMAIL PROTECTED]> wrote:
I naively thought that if I have a 100,000,000 row table, of the form (integer,integer,smallint,date), and add a real coumn to it, it will scroll through the memory reasonably fast.
In Postgres, an update is the same as a delete/insert. That means that changing the data in one column rewrites ALL of the columns for that row, and you end up with a table that's 50% dead space, which you then have to vacuum. Sometimes if you have a "volatile" column that goes with several "static" columns, you're far better off to create a second table for the volatile data, duplicating the primary key in both tables. In your case, it would mean the difference between 10^8 inserts of (int, float), very fast, compared to what you're doing now, which is 10^8 insert and 10^8 deletes of (int, int, smallint, date, float), followed by a big vacuum/analyze (also slow). The down side of this design is that later on, it requires a join to fetch all the data for each key. You do have a primary key on your data, right? Or some sort of index? Craig -- Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
