Here is a function I use to look at the size of objects:
######################start
my.ls <- function (pos = 1, sorted = FALSE, envir = as.environment(pos))
{
.result <- sapply(ls(envir = envir, all.names = TRUE),
function(..x) object.size(eval(as.symbol(..x),
envir = envir)))
if (sorted) {
.result <- rev(sort(.result))
}
.ls <- as.data.frame(rbind(as.matrix(.result), `**Total` = sum(.result)))
names(.ls) <- "Size"
.ls$Size <- formatC(.ls$Size, big.mark = ",", digits = 0,
format = "f")
.ls$Mode <- c(unlist(lapply(rownames(.ls)[-nrow(.ls)], function(x)
mode(eval(as.symbol(x),
envir = envir)))), "-------")
.ls
}
#########################end
> # create some large objects
> x <- matrix(0, 3000, 3000)
> my.ls()
Size Mode
x 72,000,112 numeric
**Total 72,000,112 -------> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 684078 18.3 1368491 36.6 1368491 36.6
Vcells 10198339 77.9 11581078 88.4 10200979 77.9> # make another one
> y <- matrix(0, 5000, 5000)
> my.ls()
Size Mode
x 72,000,112 numeric
y 200,000,112 numeric
**Total 272,000,224 -------> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 684087 18.3 1368491 36.6 1368491 36.6
Vcells 35198359 268.6 39143593 298.7 35201440 268.6>
On Fri, May 4, 2012 at 12:49 PM, Alexander Shenkin <ashenkin at ufl.edu>
wrote:> Hi Folks,
>
> I'm running 32-bit R 2.14 in RStudio on my Win 7 x64 system with 8GB
> RAM. ?I'm getting memory problems as R wants to swallow more than the
> 4GB limit.
>
> I think I'm stuck at 4GB as I have to use 32-bit R for a number of
> packages (ODBC, etc). ?However, I doubt I really need to be using that
> much memory - I'm probably being very sloppy in my memory management,
> leaving lots of temporary dataframes around, etc.
>
> I'm looking for suggestions about how to audit R's memory usage.
?Yes, I
> could go around my code and tie up every loose end. ?But in the interest
> of efficiency, I'm wondering about ways I might more intelligently
audit
> R's memory usage. ?Are there any tools that can tell me what objects
are
> swallowing what amounts of memory? ?Armed with that information, I can
> go track down the worst culprits.
>
> Thanks,
> Allie
>
> ______________________________________________
> R-help at 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.
--
Jim Holtman
Data Munger Guru
What is the problem that you are trying to solve?
Tell me what you want to do, not how you want to do it.