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dc.contributor.authorSundaravarathan, Kiran
dc.contributor.otherQueen's University (Kingston, Ont.). Theses (Queen's University (Kingston, Ont.))en
dc.date2015-09-14 18:00:28.306en
dc.date.accessioned2015-09-15T19:47:06Z
dc.date.available2015-09-15T19:47:06Z
dc.date.issued2015-09-15
dc.identifier.urihttp://hdl.handle.net/1974/13607
dc.descriptionThesis (Master, Computing) -- Queen's University, 2015-09-14 18:00:28.306en
dc.description.abstractIn this era of BigData, designing a workflow to gain insights from the vast amount of data has become more complex. There are several different frameworks which individually process the batch and streaming data but coordinating the jobs between the engines in the workflow creates a performance penalty and other performance issues. Current workflow systems typically run only on one engine and do not offer the versatility required for today’s workflows. The process of submitting the jobs on different engines manually is not only time consuming, but also requires the expertise of working on these engines. In this thesis, we have overcome the above mentioned issues by proposing a MEWSE - Multi Engine Workflow Submission and Execution on Apache YARN. It should also have design with plug and play functionalities to allow the inclusion of new engines. MEWSE has been tested on Amazon EC2 with a sample workflow which requires the following engines, Hadoop, Mahout, java and some scripts to process the data.en_US
dc.languageenen
dc.language.isoenen_US
dc.relation.ispartofseriesCanadian thesesen
dc.rightsQueen's University's Thesis/Dissertation Non-Exclusive License for Deposit to QSpace and Library and Archives Canadaen
dc.rightsProQuest PhD and Master's Theses International Dissemination Agreementen
dc.rightsIntellectual Property Guidelines at Queen's Universityen
dc.rightsCopying and Preserving Your Thesisen
dc.rightsThis publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.en
dc.subjectBig Dataen_US
dc.subjectAnalytic systemsen_US
dc.subjectWorkflow Submitteren_US
dc.subjectApache YARNen_US
dc.titleMEWSE - Multi Engine Workflow Submission and Execution on Apache YARNen_US
dc.typethesisen_US
dc.description.degreeMasteren
dc.contributor.supervisorMartin, Patricken
dc.contributor.departmentComputingen


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