----- "Martin Kersten" wrote:

Garrett Smith wrote:

...

Does anyone have some guidance on approaches for optimizing database performance?

I realize this is a pretty broad question :)

More specifically, I'm running a simple query

select max(date) from metric

on a table with 21 million rows (or whatever you call them in Monet). It's taking quite a bit longer than I'd expect, given a typically indexed column.

Given the fact that there is no (b-tree) index, the underlying engine has to perform a scan to find the maximum. This entails a linear scan over 21M elements in the current implementation.

Thanks! After going back and reading the docs on MonetDB, I realized my question was pretty naive. The SQL interface triggered a Pavlovian response to think in terms of a relational database with b-tree indexes. It's pretty amazing how fast that linear scan is. Still, my application calls for something else. I took a look at FastBit, which is insanely adept at selects into huge data sets, but requires a relatively expensive index update to get that performance. As I have routine updates to deal with, that doesn't seem a good fit. We'll probably stick with MySQL+MyISAM for this particular component. Garrett