Is there any way to detect which calls are consuming memory? I run a program whose global variables take up about 50 Megabytes of memory, but when I monitor the progress of the program it seems to allocating 150 Megabytes of memory, with peaks of up to 2 Gigabytes.
I know that the global variables aren't "copied" many times by the routines, but I suspect something weird must be happening. Alberto Monteiro PS: the lines, below, count the memory allocated to all global variables, probably it could be adapted to track the local variables: y <- ls(pat="") # get all names of the variables z <- rep(0, length(y)) # create array of sizes for (i in 1:length(y)) z[i] <- object.size(get(y[i])) # loop: get all sizes (in bytes) of the variables # BTW, is there any way to vectorialize the above loop? xix <- sort.int(z, index.return = TRUE) # sort the sizes y <- y[xix$ix] # apply the sort to the variables z <- z[xix$ix] # apply the sort to the sizes y <- c(y, "total") # add a totalizator z <- c(z, sum(z)) # sum them all cbind(y, z) # ugly way to list them ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.