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dc.contributor.authorHagedorn, Stefan
dc.contributor.authorGötze, Philipp
dc.contributor.authorSattler, Kai-Uwe
dc.contributor.editorMitschang, Bernhard
dc.contributor.editorNicklas, Daniela
dc.contributor.editorLeymann, Frank
dc.contributor.editorSchöning, Harald
dc.contributor.editorHerschel, Melanie
dc.contributor.editorTeubner, Jens
dc.contributor.editorHärder, Theo
dc.contributor.editorKopp, Oliver
dc.contributor.editorWieland, Matthias
dc.date.accessioned2017-06-20T20:24:55Z
dc.date.available2017-06-20T20:24:55Z
dc.date.issued2017
dc.identifier.isbn978-3-88579-659-6
dc.identifier.issn1617-5468
dc.description.abstractBig Data sets can contain all types of information: from server log files to tracking information of mobile users with their location at a point in time. Apache Spark has been widely accepted for Big Data analytics because of its very fast processing model. However, Spark has no native support for spatial or spatio-temporal data. Spatial filters or joins using, e.g., a contains predicate are not supported and would have to be implemented ine ciently by the users. Also, Spark cannot make use of, e.g., spatial distribution for optimal partitioning. Here we present our STARK framework that adds spatio-temporal support to Spark. It includes spatial partitioners, different modes for indexing, as well as filter, join, and clustering operators. In contrast to existing solutions, STARK integrates seamlessly into any (Scala) Spark program and provides more flexible and comprehensive operators. Furthermore, our experimental evaluation shows that our implementation outperforms existing solutions.en
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartofDatenbanksysteme für Business, Technologie und Web (BTW 2017)
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-265
dc.titleThe STARK Framework for Spatio-Temporal Data Analytics on Sparken
dc.typeText/Conference Paper
mci.reference.pages123-142
mci.conference.sessiontitleBig Data and NoSQL
mci.conference.locationStuttgart
mci.conference.date6.-10. März 2017


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