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The cost effectiveness and the ease of maintenance are the reasons behind the increasing popularity of Cloud Computing. The need to reduce the execution time of programs on Cloud platforms have led to development of Hadoop [12]. This paper analyzes the performance of K-Means Clustering Algorithm when running on Hadoop MapReduce on Eucalyptus [5] platform. Running Eucalyptus for Hadoop requires lot of customization for the software to run as discussed here. Several tools like Ganglia, TestDSFIO.java, Linux performance measuring tools have been used to measure the performance. The paper discusses how performance of KMeans Clustering Algorithm scales up with number of nodes on Eucalyptus cloud. Results of measurement of the disk, network, memory bandwidth, data throughput and average I/O are presented here.

Performance Analysis of Hadoop Map Reduce on Eucalyptus Private Cloud