What are some scenarios for which MPI is a better fit than MapReduce?

Question

As far as I understand, MPI gives me much more control over how exactly different nodes in the cluster will communicate.

In MapReduce/Hadoop, each node does some com

Answer 1

I expect that MPI beats MapReduce easily when the task is iterating over a data set whose size is comparable with the processor cache, and when communication with other tasks is frequently required. Lots of scientific domain-decomposition parallelization approaches fit this pattern. If MapReduce requires sequential processing and communication, or ending of processes, then the computational performance benefit from dealing with a cache-sized problem is lost.