Enrico Sirola wrote:
> typically, arrays contain 1000 elements, and an operation is either
> multiply it by a scalar or multiply it element-by-element with another
> array. The time to rescale 1000 arrays, multiply it for another array
> and at the end sum all the 1000 resulting arrays should be enough to be
> carried on in an interactive application (let's say 0.5s). This, in the
> case when no disk-access is required. Disk access will obviously
> downgrade performances a bit ad the beginning, but the workload is
> mostly read-only so after a while the whole table will be cached anyway.
> The table containing the arrays would be truncated/repopulated every day
> and the number of arrays is expected to be more or less 150000 (at least
> this is what we have now). Nowadays, we have a c++ middleware between
> the calculations and an aggressive caching of the table contents (and we
> don't use arrays, just a row per element) but the application could be
> refactored (and simplified a lot) if we have a smart way to save data
> into the DB.
I don't know if the speed will meet your needs, but you might test to
see if PL/R will work for you:
http://www.joeconway.com/plr/
You could use pg.spi.exec() from within the R procedure to grab the
arrays, do all of your processing inside R (which uses whatever BLAS
you've set it up to use), and then return the result out to Postgres.
Joe
