I've got a table with ~121 million records in it. Select count on it
currently takes ~45 minutes, and an update to the table to set a value
on one of the columns I finally killed after it ran 17 hours and had
still not completed. Queries into the table are butt slow, and
The update query that started this all I had to kill after 17hours.
It should have updated all 121+ million records. That brought my
select count down to 19 minutes, but still a far cry from acceptable.
If you have a column that needs to be updated often for all rows,
separate it into a different table, and create a view that joins it back
to the main table so that your application still sees the old schema.
This will greatly speed your update since (in Postgres) and update is
the same as a delete+insert. By updating that one column, you're
re-writing your entire 121 million rows. If you separate it, you're
only rewriting that one column. Don't forget to vacuum/analyze and
reindex when you're done.
Better yet, if you can stand a short down time, you can drop indexes on
that column, truncate, then do 121 million inserts, and finally
reindex. That will be MUCH faster.
Craig
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TIP 6: explain analyze is your friend
