Please RTFM, specifically the rw-FAQ and ?"Memory-limits". The short
answer is that your OS is your problem, and using a decent 64-bit OS
will solve this (so why should the very limited resources of the R
developers be spent working on this?)
People who must use Windows may like to be aware that at least one
64-bit Windows port of R is likely this year, and so think about using
64-bit Windows where appropriate. That will even help with the
problem below by doubling the address space (as explained in the
rw-FAQ).
On Sat, 17 Jan 2009, Vishwa Goudar wrote:
> Hi,
>
> Im using R-2.8.1 on windows vista and have 4GB RAM. Im trying to run LDA
> from the MASS package on a fairly large dataset and keep running out of
> memory ("Cannot allocate vector of size ...)
>
> Ive tried freeing up as much memory as possible with gc(). I tried using
the
> ff package but that would need modifications to the way LDA accesses the
> memory mapped data. The error I get is "invalid 'type' (list)
for variable
> ..."
>
> Basically, I need someone's help on how I can force R to use the large
> swaths of empty space on my hard drive as virtual memory. As I understand
> it, virtual memory increases the address space. So, why isnt R capable of
Your understanding is completely incorrect.
> using my hard drive. I dont mind the hit in performance. How do I get this
> to work? And if I cant why cant I?
All you need to do is to rewrite your OS and the compiler. Easy for
someone who know better than Microsoft about virtual memory ....
>
> Any help would be sincerely appreciated.
>
> Thanks in advance!
> VG
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> 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.
PLEASE do: sending HTML mail shows that you lacked the courtesy to do
so.
--
Brian D. Ripley, ripley at stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595