MREv: An Automatic MapReduce Evaluation Tool for Big Data Workloads
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MREv: An Automatic MapReduce Evaluation Tool for Big Data WorkloadsDate
2015Citation
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.
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.
Keywords
High Performance Computing (HPC)
Big Data
MapReduce
Performance Evaluation
Resource Efficiency
InfiniBand
Big Data
MapReduce
Performance Evaluation
Resource Efficiency
InfiniBand
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Atribución-NoComercial-SinDerivadas 4.0 Internacional
ISSN
1877-0509