Hadoop MapReduce vs MPI (vs Spark vs Mahout vs Mesos) - When to use one over the other?

Question

I am new to parallel computing and just starting to try out MPI and Hadoop+MapReduce on Amazon AWS. But I am confused about when to use one over the other.

For example,

Answer 1

The link you posted about FEM being done on MapReduce: http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6188175&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D6188175

uses MPI. It states it right there in the abstract. They combined MPI's programming model (non-embarrassingly parallel) with HDFS to "stage" the data to exploit data locality.

Hadoop is purely for embarrassingly parallel computations. Anything that requires processes to organize themselves and exchange data in complex ways will get crap performance with Hadoop. This can be demonstrated both from an algorithmic complexity point of view, and also from a measurement point of view.