
> 
> On Tue, 18 May 1999, Jim Lindsey wrote:
> 
> > I am wondering what you mean by "R's poor handling of large datasets".
> > How large is large? I have often been working simultaneously with a
> > fair number of vectors of say 40,000 using my libraries (data objects
> > and functions) with no problems. They use the R scoping rules. On the
> > other hand, if you use dataframes and/or standard functions like glm,
> > then you are restricted to extremely small (toy) data sets. But then
> > maybe you are thinking of gigabytes of data.

The answer was that at least 1/2 giga was involved.

> 
> While I agree that R isn't much use for really big datasets, I am a bit
> surprised by Jim's comments about glm(). I have used R (including glm)
> perfectly satisfactorily on real data sets of ten thousand or so
> observations. This isn't large by today's standards but it isn't in
> any sense toy data.

Oh yes with my 128 RAM machine and vsize set to 20M or more I can do the
same (very slowly) but glm has made several copies of the data in the
process whereas functions using the R scoping rules to avoid copies
should run the same thing with maybe a vsize of 5-8M.
  Jim

> 
> 
> Thomas Lumley
> Assistant Professor, Biostatistics
> University of Washington, Seattle
> 
> 
> 
> 
> 
> 
> 
> 
> 

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