Ok, so maybe someone on this group will have a better idea. We have a database of financial information, and this has literally millions of entries. I have installed indicies, but for the rather computationally demanding processes we like to use, like a select query to find the commodity with the highest monthly or annual returns, the computer generally runs unacceptably slow. So, other than clustring, how could I achieve a speed increase in these complex queries? Is this better in mysql or postgresql?
If the bottleneck is really computational, not I/O, you might try PL/R in conjunction with the rpvm R package. rpvm allows R to make use of pvm to split its load among a cluster. See:
R: http://www.r-project.org/
PL/R: http://www.joeconway.com/plr/
rpvm: http://cran.r-project.org/src/contrib/Descriptions/rpvm.html http://cran.r-project.org/doc/packages/rpvm.pdf
I haven't had a chance to play with this myself yet, but I hope to relatively soon.
HTH,
Joe
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