clara - memory limit

From the help page:

'clara' is fully described in chapter 3 of Kaufman and Rousseeuw
      (1990). Compared to other partitioning methods such as 'pam', it
      can deal with much larger datasets.  Internally, this is achieved
      by considering sub-datasets of fixed size ('sampsize') such that
      the time and storage requirements become linear in n rather than
      quadratic.

and the default for 'sampsize' is apparently at least nrow(x).

So you need to set 'sampsize' (and perhaps 'samples') appropriately,

Dear all,

I'm trying to estimate clusters from a very large dataset using clara but the
program stops with a memory error. The (very simple) code and the error:

mydata<-read.dbf(file="fnorsel_4px.dbf")
my.clara.7k<-clara(mydata,k=7)

Error: cannot allocate vector of size 465108 Kb

The dataset contains >3,000,000 rows and 15 columns. I'm using a windows
computer with 1.5G RAM; I also tried changing the memory limit to the maximum
possible (4000M)

Actually, the limit is probably 2048M: see the rw-FAQ Q on memory limits.

Is there a way to calculate clara clusters from such large datasets?

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