Q:

k-means clustering in R on very large, sparse matrix?

I am trying to do some k-means clustering on a very large matrix.
The matrix is approximately 500000 rows x 4000 cols yet very sparse (only a couple of "1" values per row). 
The whole thing does not fit into memory, so I converted it into a sparse ARFF file. But R obviously can't read the sparse ARFF file format. I also have the data as a plain CSV file.
Is there any package available in R for loading such sparse matrices efficiently? I'd then use the regular k-means algorithm from the cluster package to proceed.
Many thanks

A:

The bigmemory package (or now family of packages -- see their website) used k-means as running example of extended analytics on large data. See in particular the sub-package biganalytics which contains the k-means function.

