Published in

De Gruyter Open, International Journal of Applied Mathematics and Computer Science, 2(21), p. 275-284, 2011

DOI: 10.2478/v10006-011-0020-3

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Performance evaluation of MapReduce using full virtualisation on a departmental cloud

Journal article published in 2011 by Horacio González-Vélez ORCID, Maryam Kontagora
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Performance evaluation of MapReduce using full virtualisation on a departmental cloudThis work analyses the performance of Hadoop, an implementation of the MapReduce programming model for distributed parallel computing, executing on a virtualisation environment comprised of 1+16 nodes running the VMWare workstation software. A set of experiments using the standard Hadoop benchmarks has been designed in order to determine whether or not significant reductions in the execution time of computations are experienced when using Hadoop on this virtualisation platform on a departmental cloud. Our findings indicate that a significant decrease in computing times is observed under these conditions. They also highlight how overheads and virtualisation in a distributed environment hinder the possibility of achieving the maximum (peak) performance.