The refactoring of Hadoop MapReduce framework, by separating resource management (YARN) from job execution (MapReduce) has allowed multiple programming paradigms to take advantage of the massive scale Hadoop Distributed File System (HDFS) clusters. Hamster (Hadoop And Mpi on the same cluSTER) is a port of OpenMPI to use YARN as a resource manager. Hamster allows applications written using MPI (Message Passing Interface) to run alongside other YARN applications and frameworks, such as MapReduce, on the same Hadoop cluster. In this talk, I will describe the architecture of Hamster, and present a few MPI applications that have been demonstrated to run in Hadoop. GraphLab uses MPI as one of the supported communication libraries, and can read/write data from/to HDFS. I will describe how GraphLab runs on top of Hadoop using Hamster, and present a few benchmarks in graph analytics, comparing GraphLab with other machine frameworks.