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Network-aware multiway join for MapReduce
Conference paper   Peer reviewed

Network-aware multiway join for MapReduce

Kenn Slagter, Ching-Hsien Hsu, YEH-CHING CHUNG and Jong Hyuk Park
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol.7861 LNCS, pp.73-80
2013

Abstract

Hadoop MapReduce Multiway Join Workload Redistribution
MapReduce is an effective tool for processing large amounts of data in parallel using a cluster of processors or computers. One common data processing task is the join operation, which combines two or more datasets based on values common to each. In this paper, we present a network aware multi-way join for MapReduce(NAMM) that improves performance by redistributing the workload amongst reducers. NAMM achieves this by redistributing tuples directly between reducers with an intelligent network aware algorithm. We show that our presented technique has significant potential to minimize the time required to join multiple datasets. © 2013 Springer-Verlag.

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