<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>This 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.</p></abstract>

This 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.

Performance evaluation of MapReduce using full virtualisation on a departmental cloud

School of Computing, Robert Gordon University, St Andrew Street, Aberdeen AB25 1HG, UK

IDEAS Research Institute, Robert Gordon University, St Andrew Street, Aberdeen AB25 1HG, UK

International Journal of Applied Mathematics and Computer Science

This work analyses the performance of Hadoop, an implementation of the MapReduce programming model for distributed parallel computing, executing on a...

Performance evaluation of MapReduce using full virtualisation on a departmental cloud

Publié en ligne: 22 juin 2011

Pages: 275 - 284

DOI: https://doi.org/10.2478/v10006-011-0020-3

Mots clés
MapReduce, server virtualization, cloud computing, algorithmic skeletons, structured parallelism, parallel computing

This content is open access.

Performance evaluation of MapReduce using full virtualisation on a departmental cloud

Publié en ligne: 22 juin 2011

Pages: 275 - 284

DOI: https://doi.org/10.2478/v10006-011-0020-3

Mots clésMapReduce, server virtualization, cloud computing, algorithmic skeletons, structured parallelism, parallel computing

This content is open access.

Mots clés
MapReduce, server virtualization, cloud computing, algorithmic skeletons, structured parallelism, parallel computing