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Applicability of giraph and hadoop for the processing of big graph [Ejemplos de aplicabilidad de giraph y hadoop para el procesamiento de grandes grafos]

dc.contributor.authorValenzuela S.A.
dc.contributor.authorVidal C.L.
dc.contributor.authorMorales J.D.
dc.contributor.authorLópez L.P.
dc.date.accessioned2020-09-02T22:29:53Z
dc.date.available2020-09-02T22:29:53Z
dc.date.issued2016
dc.identifier10.4067/S0718-07642016000500019
dc.identifier.citation27, 5, 171-180
dc.identifier.issn07168756
dc.identifier.urihttps://hdl.handle.net/20.500.12728/6503
dc.descriptionThis article presents a comparison of the performance of the tools Hadoop y Giraph for the analysis and processing of large volumes of information or Big Data, with the aim of showing their usefulness for Big Graph processing. The analysis and processing of large volumes of information represents a real challenge nowadays. There already exist Big Data methodologies and free processing tools such as those mentioned above: Hadoop for processing large volumes of data, mainly non-related data, and recently Giraph for processing large graphs or Big Graph. In this comparison, this paper presents an analysis of the execution time cost for the practical implementation of the PageRank algorithm, which classifies Web pages according to their relevance, and of algorithms to find the minimum spanning tree in a graph. Experiments show that the use of Giraph for processing Big Graphs reduces the execution time by 25% with respect to the results obtained using Hadoop.
dc.language.isoes
dc.publisherCentro de Informacion Tecnologica
dc.subjectBig Data
dc.subjectBig Grap
dc.subjectGiraph
dc.subjectGrafos
dc.subjectHadoop
dc.subjectMapReduce
dc.subjectTrees (mathematics)
dc.subjectWebsites
dc.subjectBig Grap
dc.subjectGiraph
dc.subjectGrafos
dc.subjectHadoop
dc.subjectMap-reduce
dc.subjectBig data
dc.titleApplicability of giraph and hadoop for the processing of big graph [Ejemplos de aplicabilidad de giraph y hadoop para el procesamiento de grandes grafos]
dc.typeConference Paper


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