In my experience, the OS's use of virtual memory is only relevant in the rough sense that the OS can store *other* running applications in virtual memory so that R can use as much of the physical memory as possible. Once R itself overflows into virtual memory it quickly becomes unusable.
I'm not sure I understand your second question. As R is available in source code form, it can be compiled for many 64-bit operating systems. -roger Marshall Feldman wrote: > Hi, > > I have two further comments/questions about large datasets in R. > > 1. Does R's ability to handle large datasets depend on the operating > system's use of virtual memory? In theory, at least, VM should make the > difference between installed RAM and virtual memory on a hard drive > primarily a determinant of how fast R will calculate rather than whether or > not it can do the calculations. However, if R has some low-level routines > that have to be memory resident and use more memory as the amount of data > increases, this may not hold. Can someone shed light on this? > > 2. Is What 64-bit versions of R are available at present? > > Marsh Feldman > The University of Rhode Island > > -----Original Message----- > From: Thomas Lumley [mailto:[EMAIL PROTECTED] > Sent: Monday, July 17, 2006 3:21 PM > To: Deepankar Basu > Cc: r-help@stat.math.ethz.ch > Subject: Re: [R] Large datasets in R > > On Mon, 17 Jul 2006, Deepankar Basu wrote: > >> Hi! >> >> I am a student of economics and currently do most of my statistical work >> using STATA. For various reasons (not least of which is an aversion for >> proprietary software), I am thinking of shifting to R. At the current >> juncture my concern is the following: would I be able to work on >> relatively large data-sets using R? For instance, I am currently working >> on a data-set which is about 350MB in size. Would be possible to work >> data-sets of such sizes using R? > > > The answer depends on a lot of things, but most importantly > 1) What you are going to do with the data > 2) Whether you have a 32-bit or 64-bit version of R > 3) How much memory your computer has. > > In a 32-bit version of R (where R will not be allowed to address more than > 2-3Gb of memory) an object of size 350Mb is large enough to cause problems > (see eg the R Installation and Adminstration Guide). > > If your 350Mb data set has lots of variables and you only use a few at a > time then you may not have any trouble even on a 32-bit system once you > have read in the data. > > If you have a 64-bit version of R and a few Gb of memory then there should > be no real difficulty in working with that size of data set for most > analyses. You might come across some analyses (eg some cluster analysis > functions) that use n^2 memory for n observations and so break down. > > > -thomas > > Thomas Lumley Assoc. Professor, Biostatistics > [EMAIL PROTECTED] University of Washington, Seattle > > ______________________________________________ > R-help@stat.math.ethz.ch 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. > -- Roger D. Peng | http://www.biostat.jhsph.edu/~rpeng/ ______________________________________________ R-help@stat.math.ethz.ch 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.