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dc.contributor.advisorMehta, Dinesh P.
dc.contributor.authorLangewisch, Ryan P.
dc.date.accessioned2016-01-11T15:26:07Z
dc.date.accessioned2022-02-03T12:52:12Z
dc.date.available2016-01-11T15:26:07Z
dc.date.available2022-02-03T12:52:12Z
dc.date.issued2015
dc.identifierT 7937
dc.identifier.urihttps://hdl.handle.net/11124/166690
dc.description2015 Fall.
dc.descriptionIncludes illustrations.
dc.descriptionIncludes bibliographical references.
dc.description.abstractGraphX is an API for graph computation built upon Apache Spark, a fast and generalized engine for large-scale data processing in the cloud. While the popularity of Spark and GraphX is growing, the relatively young technology has yet to explore the breadth of graph problems that exist in the field. In order to examine and gain insights into the capabilities of GraphX, this thesis approaches the framework with the intention of implementing a solution to the Maximum Flow Problem, a complex graph problem without a trivial distributed approach. Specifically, the implementation is to be based on the serial Push-Relabel algorithm. An original MapReduce-based approach to the problem is presented, as well as an implementation of the approach in GraphX. In addition to the implementation, experimentation and deployment to an Amazon EC2 cluster allowed observations on caching and checkpointing intervals to be made.
dc.format.mediumborn digital
dc.format.mediummasters theses
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado School of Mines. Arthur Lakes Library
dc.relation.ispartof2015 - Mines Theses & Dissertations
dc.rightsCopyright of the original work is retained by the author.
dc.subjectalgorithm
dc.subjectdistributed
dc.subjectGraphX
dc.subjectmaximum flow
dc.subjectpush-relabel
dc.subjectspark
dc.titlePerformance study of an implementation of the push-relabel maximum flow algorithm in Apache Spark's GraphX, A
dc.typeText
dc.contributor.committeememberWu, Bo
dc.contributor.committeememberRavindran, Arun
dc.contributor.committeememberJoshi, Bharat
thesis.degree.nameMaster of Science (M.S.)
thesis.degree.levelMasters
thesis.degree.disciplineElectrical Engineering and Computer Science
thesis.degree.grantorColorado School of Mines


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