[R] memory problem for R

[Yun-Fang Juan]

Pleaase see the comments below.
> > Here is the exact error I got
> > ----------------------
> > Read 73 items
> > Error: cannot allocate vector of size 1953 Kb
> > Execution halted
> > -----------------------
> > I am running R on Freebsd 4.3
> > with double CPU and 2 GB memory
> > Is that sufficient?
>
> Clearly not.  What is the structure of your `attributes'?  As Andy Liaw
> said, the design matrix may be bigger than that if there are factors
> involved.  (And you need several copies of the design matrix.)
>
> I would try a 10% sample of the rows to get a measure of what will fit
> into your memory.  I have never seen a regression problem for which 600k
> cases were needed, and would be interested to know the context.  (It is
> hard to imagine that the cases are from a single homogeneous population
> and that a linear model fits so well that the random error is not
> dominated by systematic error.)
I tried 10% sample and it turned out the matrix became singular after I did
that.
Ther reason is some of the attributes only have zero values most of the
time.
The data i am using is web log data and after some transformation, they are
all numeric.
Can we specify some parameters in read.table so that the program will treat
all the vars as numeric
(with this context, hopefully that will reduce the memory consumption)  ?

thanks a lot,

Yun-Fang
>
> >
> > Yun-Fang
> > ----- Original Message -----
> > From: "Yun-Fang Juan" <yunfang at yahoo-inc.com>
> > To: <r-help at stat.math.ethz.ch>
> > Sent: Thursday, January 29, 2004 7:03 PM
> > Subject: [R] memory problem for R
> >
> >
> > > Hi,
> > > I try to use lm to fit a linear model with 600k rows and 70
attributes.
> > > But I can't even load the data into the R environment.
> > > The error message says the vector memory is used up.
> > >
> > > Is there anyone having experience with large datasets in R? (I bet)
> > >
> > > Please advise.
> > >
> > >
> > > thanks,
> > >
> > >
> > > Yun-Fang
> > >
> > > [[alternative HTML version deleted]]
> > >
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> --
> 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)
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>