I think you are looking for the 'data.table' package.
On 09/10/2011 17:31, ivo welch wrote:
Dear R experts---I am struggling with memory and speed issues. Advice would be appreciated. I have a long data set (of financial stock returns, with stock name and trading day). All three variables, stock return, id and day, are irregular. About 1.3GB in object.size (200MB on disk). now, I need to merge the main data set with some aggregate data (e.g., the S&P500 market rate of return, with a day index) from the same day. this "market data set" is not a big data set (object.size=300K, 5 columns, 12000 rows). let's say my (dumb statistical) plan is to run one grand regression, where the individual rate of return is y and the market rate of return is x. the following should work without a problem: combined<- merge( main, aggregate.data, by="day", all.x=TRUE, all.y=FALSE ) lm( stockreturn ~ marketreturn, data=combined ) alas, the merge is neither space-efficient nor fast. in fact, I run out of memory on my 16GB linux machine. my guess is that by whittling it down, I could work it (perhaps doing it in chunks, and then rbinding it), but this is painful. in perl, I would define a hash with the day as key and the market return as value, and then loop over the main data set to supplement it. is there a recommended way of doing such tasks in R, either super-fast (so that I merge many many times) or space efficient (so that I merge once and store the results)? sincerely, /iaw ---- Ivo Welch (ivo.we...@gmail.com) ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
-- Patrick Burns pbu...@pburns.seanet.com twitter: @portfolioprobe http://www.portfolioprobe.com/blog http://www.burns-stat.com (home of 'Some hints for the R beginner' and 'The R Inferno') ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
