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dc.contributor.authorVeiga, Jorge
dc.contributor.authorExpósito, Roberto R.
dc.contributor.authorTaboada, Guillermo L.
dc.contributor.authorTouriño, Juan
dc.date.accessioned2024-02-29T15:57:13Z
dc.date.available2024-02-29T15:57:13Z
dc.date.issued2015
dc.identifier.citationJorge 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.es_ES
dc.identifier.issn1877-0509
dc.identifier.urihttp://hdl.handle.net/2183/35751
dc.description.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.es_ES
dc.description.sponsorshipThis work was funded by the Ministry of Economy and Competitiviness of Spain (Ref. TIN2013- 42148-P), and by the Galician Government (Xunta de Galicia) under the Consolidation Program of Competitive Reference Groups (Ref. GRC2013/055), cofunded by FEDER funds of the EU.es_ES
dc.description.sponsorshipXunta de Galicia; GRC2013/055es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.relationinfo:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2013-42148-P/ES/NUEVOS DESAFIOS EN COMPUTACION DE ALTAS PRESTACIONES: DESDE ARQUITECTURAS HASTA APLICACIONESes_ES
dc.relation.urihttps://doi.org/10.1016/j.procs.2015.05.202es_ES
dc.rightsAtribución-NoComercial-SinDerivadas 4.0 Internacionales_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectHigh Performance Computing (HPC)es_ES
dc.subjectBig Dataes_ES
dc.subjectMapReducees_ES
dc.subjectPerformance Evaluationes_ES
dc.subjectResource Efficiencyes_ES
dc.subjectInfiniBandes_ES
dc.titleMREv: An Automatic MapReduce Evaluation Tool for Big Data Workloadses_ES
dc.typeinfo:eu-repo/semantics/conference paperes_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleProcedia Computer Sciencees_ES
UDC.volume51es_ES
UDC.startPage80es_ES
UDC.endPage89es_ES
dc.identifier.doi10.1016/j.procs.2015.05.202
UDC.conferenceTitleInternational Conference On Computational Science - ICCS 2015


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