MREv: An Automatic MapReduce Evaluation Tool for Big Data Workloads

Bibliographic citation

Jorge Veiga, Roberto R. Expósito, Guillermo L. Taboada, Juan Touriño, “MREv: An Automatic MapReduce Evaluation Tool for Big Data Workloads”, in Procedia Computer Science, V. 51, 2015, p. 80-89, ISSN 1877-0509, https://doi.org/10.1016/j.procs.2015.05.202.

Type of academic work

Academic degree

Abstract

[Abstract]: The popularity of Big Data computing models like MapReduce has caused the emergence of many frameworks oriented to High Performance Computing (HPC) systems. The suitability of each one to a particular use case depends on its design and implementation, the underlying system resources and the type of application to be run. Therefore, the appropriate selection of one of these frameworks generally involves the execution of multiple experiments in order to assess their performance, scalability and resource efficiency. This work studies the main issues of this evaluation, proposing a new MapReduce Evaluator (MREv) tool which unifies the configuration of the frameworks, eases the task of collecting results and generates resource utilization statistics. Moreover, a practical use case is described, including examples of the experimental results provided by this tool. MREv is available to download at http://mrev.des.udc.es.

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Atribución-NoComercial-SinDerivadas 4.0 Internacional
Atribución-NoComercial-SinDerivadas 4.0 Internacional

Except where otherwise noted, this item's license is described as Atribución-NoComercial-SinDerivadas 4.0 Internacional