[R] FW: Large datasets in R

[Marshall Feldman]

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:tlumley at u.washington.edu] 
Sent: Monday, July 17, 2006 3:21 PM
To: Deepankar Basu
Cc: r-help at 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
tlumley at u.washington.edu	University of Washington, Seattle