Exploring Apache Hama

Apache Hama is one of the under-hyped projects in the Hadoop ecosystem but gaining a lot of traction steadily with the efforts of its committers. "Apache Hama is a pure BSP (Bulk Synchronous Parallel) computing framework on top of HDFS (Hadoop Distributed File System) for massive scientific computations such as matrix, graph and network algorithms."

First a short introduction to BSP in Apache Hadoop context :

Apache HAMA: An Introduction toBulk Synchronization Parallel on Hadoop from Edward J. Yoon

A look at Apache Hama components and its high level architecture :

Apache hama 0.2-userguide from Edward J. Yoon

Among its various use cases, a presentation which explores usage in Machine learning with Apache Hama - a slide deck from the recently concluded ApacheCon Europe 2012

Machine learning with Apache Hama from Tommaso Teofili

Algorithms available within Apache Hama:

Addition of multiple matrices
Multiplication
Matrix Norm
Compute the transpose of matrix
Compute the determinant of square matrix
Cholesky Decomposition
Singular Value Decompostion

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