Hadoop2010: Algorithms in MapReduce

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Existing best practices for MapReduce graph algorithms have significant shortcomings that limit performance, especially with respect to partitioning, serializing, and distributing the graph. Jimmy Lin (working with Michael Schatz), University of Maryland, presents three design patterns that address designing scalable graph algorithms, and can be used to accelerate a large class of graph algorithms based on message passing, exemplified by PageRank. Experiments show that the application of these design patterns reduces the running time of PageRank on a web graph with 1.4 billion edges by 69%.

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