multicore by(), like mclapply?
I could be waay off base here, but my concern about presplitting the data is that you will have your data, and a second copy of our data that is something like a list where each element contains the portion of the data for that split. Good speed wise, bad memory wise. My hope with the technique I showed (again I may not have accomplished it) was to only have at anyone time, the original data and a copy of the particular elements being worked with. Of course this is not an issue if you have plenty of memory.
On Oct 10, 2011, at 12:19, Thomas Lumley <tlumley at uw.edu> wrote:
On Tue, Oct 11, 2011 at 7:54 AM, ivo welch <ivo.welch at gmail.com> wrote:
hi josh---thx. I had a different version of this, and discarded it because I think it was very slow. the reason is that on each application, your version has to scan my (very long) data vector. (I have many thousand different cases, too.) I presume that by() has one scan through the vector that makes all splits.
by.data.frame() is basically a wrapper for tapply(), and the key line in tapply() is ans <- lapply(split(X, group), FUN, ...) which should be easy to adapt for mclapply. -- Thomas Lumley Professor of Biostatistics University of Auckland