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Sparqling pig - processing linked data with pig Latin

dc.contributor.authorHagedorn, Stefan
dc.contributor.authorHose, Katja
dc.contributor.authorSattler, Kai-Uwe
dc.contributor.editorSeidl, Thomas
dc.contributor.editorRitter, Norbert
dc.contributor.editorSchöning, Harald
dc.contributor.editorSattler, Kai-Uwe
dc.contributor.editorHärder, Theo
dc.contributor.editorFriedrich, Steffen
dc.contributor.editorWingerath, Wolfram
dc.date.accessioned2017-06-30T11:40:45Z
dc.date.available2017-06-30T11:40:45Z
dc.date.issued2015
dc.description.abstractIn recent years, dataflow languages such as Pig Latin have emerged as flexible and powerful tools for handling complex analysis tasks on big data. These languages support schema flexibility as well as common programming patterns such as iteration. They offer extensibility through user-defined functions while running on top of scalable distributed platforms. In doing so, these languages enable analytical tasks while avoiding the limitations of classical query languages such as SQL and SPARQL. However, the tuple-oriented view of general-purpose languages like Pig does not match very well the specifics of modern datasets available on the Web, which often use the RDF data model. Graph patterns, for instance, are one of the core concepts of SPARQL but have to be formulated as explicit joins, which burdens the user with the details of efficient query processing strategies. In this paper, we address this problem by proposing extensions to Pig that deal with linked data in RDF to bridge the gap between Pig and SPARQL for analytics. These extensions are realized by a set of user-defined functions and rewriting rules, still allowing to compile the enhanced Pig scripts to plain MapReduce programs. For all proposed extensions, we discuss possible rewriting strategies and present results from an experimental evaluation.en
dc.identifier.isbn978-3-88579-635-0
dc.identifier.pissn1617-5468
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofDatenbanksysteme für Business, Technologie und Web (BTW 2015)
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-241
dc.titleSparqling pig - processing linked data with pig Latinen
dc.typeText/Conference Paper
gi.citation.endPage298
gi.citation.publisherPlaceBonn
gi.citation.startPage279
gi.conference.date2.-3. März 2015
gi.conference.locationHamburg

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