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dc.contributor.authorXu, Qiang
dc.contributor.authorWang, Xin
dc.contributor.authorLi, Jianxin
dc.contributor.authorGan, Ying
dc.contributor.authorChai, Lele
dc.contributor.authorWang, Junhu
dc.contributor.editorCai, Y
dc.contributor.editorIshikawa, Y
dc.contributor.editorXu, J
dc.date.accessioned2019-06-27T12:30:47Z
dc.date.available2019-06-27T12:30:47Z
dc.date.issued2018
dc.identifier.isbn978-3-319-96889-6
dc.identifier.issn0302-9743
dc.identifier.doi10.1007/978-3-319-96890-2_34
dc.identifier.urihttp://hdl.handle.net/10072/383966
dc.description.abstractWith the proliferation of knowledge graphs, large amounts of RDF graphs have been released, which raises the need for addressing the challenge of distributed SPARQL queries. In this paper, we propose an efficient distributed method, called Open image in new window, to answer the SPARQL basic graph pattern (BGP) queries on big RDF graphs using MapReduce. In our method, query graphs are decomposed into a set of stars that utilize the semantic and structural information embedded RDF graphs as heuristics. Two optimization techniques are proposed to further improve the efficiency of our algorithms. One filters out invalid input data, the other postpones the Cartesian product operations. The extensive experiments on both synthetic and real-world datasets show that our Open image in new window method outperforms the state-of-the-art method S2X by an order of magnitude.
dc.description.peerreviewedYes
dc.languageEnglish
dc.publisherSpringer Nature
dc.publisher.placeSwitzerland
dc.relation.ispartofconferencenameAsia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint International Conference on Web and Big Data (APWeb-WAIM 2018)
dc.relation.ispartofconferencetitleLecture Notes in Computer Science
dc.relation.ispartofdatefrom2018-07-23
dc.relation.ispartofdateto2018-07-25
dc.relation.ispartoflocationMacau, China
dc.relation.ispartofpagefrom415
dc.relation.ispartofpageto430
dc.relation.ispartofvolume10987
dc.subject.fieldofresearchInformation and computing sciences
dc.subject.fieldofresearchcode46
dc.titleStarMR: An efficient star-decomposition based query processor for SPARQL basic graph patterns using MapReduce
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
gro.hasfulltextNo Full Text
gro.griffith.authorWang, John


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