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dc.contributor.authorGlushkova, Daria
dc.contributor.authorJovanovic, Petar
dc.contributor.authorAbelló Gamazo, Alberto
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Serveis i Sistemes d'Informació
dc.identifier.citationGlushkova, D., Jovanovic, P., Abelló, A. Mapreduce performance model for Hadoop 2.x. "Information systems", Gener 2019, vol. 79, p. 32-43.
dc.description.abstractMapReduce is a popular programming model for distributed processing of large data sets. Apache Hadoop is one of the most common open-source implementations of such paradigm. Performance analysis of concurrent job executions has been recognized as a challenging problem, at the same time, that may provide reasonably accurate job response time estimation at significantly lower cost than experimental evaluation of real setups. In this paper, we tackle the challenge of defining MapReduce performance model for Hadoop 2.x. While there are several efficient approaches for modeling the performance of MapReduce workloads in Hadoop 1.x, they could not be applied to Hadoop 2.x due to fundamental architectural changes and dynamic resource allocation in Hadoop 2.x. Thus, the proposed solution is based on an existing performance model for Hadoop 1.x, but taking into consideration architectural changes and capturing the execution flow of a MapReduce job by using queuing network model. This way, the cost model reflects the intra-job synchronization constraints that occur due the contention at shared resources. The accuracy of our solution is validated via comparison of our model estimates against measurements in a real Hadoop 2.x setup.
dc.format.extent12 p.
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.subjectÀrees temàtiques de la UPC::Informàtica::Arquitectura de computadors::Arquitectures distribuïdes
dc.subject.lcshElectronic data processing -- Distributed processing
dc.subject.lcshCost effectiveness
dc.subject.otherHadoop 2.x
dc.subject.otherMapReduce performance model
dc.titleMapreduce performance model for Hadoop 2.x
dc.subject.lemacProcessament distribuït de dades
dc.contributor.groupUniversitat Politècnica de Catalunya. inSSIDE - integrated Software, Service, Information and Data Engineering
dc.description.peerreviewedPeer Reviewed
dc.rights.accessOpen Access
dc.description.versionPostprint (author's final draft)
local.citation.authorGlushkova, D.; Jovanovic, P.; Abelló, A.
local.citation.publicationNameInformation systems

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