An implementation framework of mapreduce email social network analysis

Authors:
Rung-Hung Gau;Tzu-Chiang Hsieh;Sheng-Wen Tsai;Ching-Pei Cheng
Affiliations:
National Chiao Tung University, Hsinchu, Taiwan Roc;National Chiao Tung University, Hsinchu, Taiwan Roc;National Chiao Tung University, Hsinchu, Taiwan Roc;National Chiao Tung University, Hsinchu, Taiwan Roc
Venue:
Proceedings of the 6th ACM workshop on Wireless multimedia networking and computing
Year:
2011

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Abstract

In this paper, we introduce our own implementation of MapReduce graph-theoretic algorithms for Email social network analysis on the Hadoop platform. Graph theory is a powerful tool for social network analysis and MapReduce is a well-known paradigm for distributed parallel computing. However, based on our own experience, unlike writing conventional Java/C++ programs, writing Java programs to implement MapReduce graph-theoretic algorithms is not straight-forward, even for some fundamental graph-theoretic algorithms. In this paper, for the problem of Email social network analysis, we compare the performance of cloud computing programs with that of conventional computer programs. We show that as long as the size of the input data exceeds a threshold, the cloud computing programs outperform their conventional counterparts.