k-means clustering in R on very large, sparse matrix?
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.
sparkcl performs sparse hierarchical clustering and sparse k-means clusteringThis should be good for R-suitable (so - fitting into memory) matrices.
http://cran.r-project.org/web/packages/sparcl/sparcl.pdf
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For really big matrices, I would try a solution with Apache Spark sparse matrices, and MLlib - still, do not know how experimental it is now:
https://spark.apache.org/docs/latest/api/scala/index.html#org.apache.spark.mllib.linalg.Matrices$