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

The best answer that I could come up with is that MPI is better than MapReduce in two cases:

1. For short tasks rather than batch processing. For example, MapReduce cannot be used to respond to individual queries - each job is expected to take minutes. I think that in MPI, you can build a query response system where machines send messages to each other to route the query and generate the answer.

2. For jobs nodes need to communicate more than what iterated MapReduce jobs support, but not too much so that the communication overheads make the computation impractical. I am not sure how often such cases occur in practice, though.