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Applying stratosphere for big data analytics

dc.contributor.authorLeich, Marcus
dc.contributor.authorAdamek, Jochen
dc.contributor.authorSchubotz, Moritz
dc.contributor.authorHeise, Arvid
dc.contributor.authorRheinländer, Astrid
dc.contributor.authorMarkl, Volker
dc.contributor.editorMarkl, Volker
dc.contributor.editorSaake, Gunter
dc.contributor.editorSattler, Kai-Uwe
dc.contributor.editorHackenbroich, Gregor
dc.contributor.editorMitschang, Bernhard
dc.contributor.editorHärder, Theo
dc.contributor.editorKöppen, Veit
dc.date.accessioned2018-10-24T09:56:26Z
dc.date.available2018-10-24T09:56:26Z
dc.date.issued2013
dc.description.abstractAnalyzing big data sets as they occur in modern business and science applications requires query languages that allow for the specification of complex data processing tasks. Moreover, these ideally declarative query specifications have to be optimized, parallelized and scheduled for processing on massively parallel data processing platforms. This paper demonstrates the application of Stratosphere to different kinds of Big Data Analytics tasks. Using examples from different application domains, we show how to formulate analytical tasks as Meteor queries and execute them with Stratosphere. These examples include data cleansing and information extraction tasks, and a correlation analysis of microblogging and stock trade volume data that we describe in detail in this paper.en
dc.identifier.isbn978-3-88579-608-4
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/17344
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofDatenbanksysteme für Business, Technologie und Web (BTW) 2046
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-214
dc.titleApplying stratosphere for big data analyticsen
dc.typeText/Conference Paper
gi.citation.endPage510
gi.citation.publisherPlaceBonn
gi.citation.startPage507
gi.conference.date13.-15. März 2013
gi.conference.locationMagdeburg
gi.conference.sessiontitleRegular Research Papers

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