instead of spliting the entire dataframe, split the indices and then use these to access your data: try
system.time(s <- split(seq(nrow(d)), d$key)) this should be faster and less memory intensive. you can then use the indices to access the subset: result <- lapply(s, function(.indx){ doSomething <- sum(d$someCol[.indx]) }) Sent from my iPad On Oct 10, 2011, at 21:01, ivo welch <ivo.we...@gmail.com> wrote: > dear R experts: apologies for all my speed and memory questions. I > have a bet with my coauthors that I can make R reasonably efficient > through R-appropriate programming techniques. this is not just for > kicks, but for work. for benchmarking, my [3 year old] Mac Pro has > 2.8GHz Xeons, 16GB of RAM, and R 2.13.1. > > right now, it seems that 'split()' is why I am losing my bet. (split > is an integral component of *apply() and by(), so I need split() to be > fast. its resulting list can then be fed, e.g., to mclapply().) I > made up an example to illustrate my ills: > > library(data.table) > N <- 1000 > T <- N*10 > d <- data.table(data.frame( key= rep(1:T, rep(N,T)), val=rnorm(N*T) )) > setkey(d, "key"); gc() ## force a garbage collection > cat("N=", N, ". Size of d=", object.size(d)/1024/1024, "MB\n") > print(system.time( s<-split(d, d$key) )) > > My ordered input data table (or data frame; doesn't make a difference) > is 114MB in size. it takes about a second to create. split() only > needs to reshape it. this simple operation takes almost 5 minutes on > my computer. > > with a data set that is larger, this explodes further. > > am I doing something wrong? is there an alternative to split()? > > 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. ______________________________________________ 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.