Performance Analysis of Hadoop Map Reduce on Eucalyptus Private Cloud
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. This paper analyzes the performance of K-means clustering algorithm when running on hadoop map reduce on eucalyptus platform. Running eucalyptus for hadoop requires lot of customization for the software to run as discussed here. Several tools like ganglia, testDSFIO.java and linux performance measuring tools have been used to measure the performance.