The mapReduce algorithm provides a framework for dividing a problem and working on it in parallel. There are two steps: a map step and a reducestep. Although, the two steps must proceed serially — map must preceded reduce — each step can be accomplished in parallel. In the map step, data is mapped to key-value pairs. In the reduce step, the values that share the same key are transformed (‘reduce’) by some algorithm.
This is available on CRAN.
Once day I should give this a go.