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dc.contributor.authorDerakhshan, R
dc.contributor.authorSattar, A
dc.contributor.authorStantic, B
dc.contributor.editorQi He
dc.date.accessioned2017-11-20T12:00:21Z
dc.date.available2017-11-20T12:00:21Z
dc.date.issued2013
dc.date.modified2014-04-22T05:15:06Z
dc.identifier.isbn9781450322638
dc.identifier.refurihttp://www.cikm2013.org/
dc.identifier.doi10.1145/2505515.2505728
dc.identifier.urihttp://hdl.handle.net/10072/58749
dc.description.abstractIn the last decade, Stream Processing Engines (SPEs) have emerged as a new processing paradigm that can process huge amounts of data while retaining low latency and high-throughputs. Yet, it is often necessary to join streaming data with traditional databases to provide more contextual information for the end-users and applications. The major problem that we confront is to join the fast arriving stream tuples with the static relation tuples that are on a slow database. This is what we call the Stream-Relation Join (SRJ) problem. Currently, SPEs use a naive tuple-by-tuple approach for SRJ processing where the SPE accesses the database for every incoming tuple. Some SPEs use cache to avoid accessing the database for every incoming tuple, while others do not because of the stochastic nature of streaming data. In this paper, we propose a new SRJ operator to facilitate SRJ processing regardless of the cache performance using two techniques: batching and out-of-order processing. The proposed operator provides an effective generic solution to the SRJ problem and the cost of incorporating our operator into different SPEs is minimal. Our experiments use a variety of synthetic and real data sets demonstrating that our operator outperforms the state-of-the-art tuple-by-tuple approach in terms of maximizing the throughput under ordering and memory constraints.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.languageEnglish
dc.publisherAMC
dc.publisher.placeUnited States
dc.publisher.urihttp://www.cikm2013.org/
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofconferencenameCIKM 2013 : ACM International Conference on Information and Knowledge Management
dc.relation.ispartofconferencetitleInternational Conference on Information and Knowledge Management, Proceedings
dc.relation.ispartofdatefrom2013-10-27
dc.relation.ispartofdateto2013-11-01
dc.relation.ispartoflocationBurlingame, CA, United States
dc.relation.ispartofpagefrom793
dc.relation.ispartofpageto798
dc.rights.retentionY
dc.subject.fieldofresearchArtificial Intelligence and Image Processing not elsewhere classified
dc.subject.fieldofresearchData Structures
dc.subject.fieldofresearchcode080199
dc.subject.fieldofresearchcode080403
dc.titleA New Operator for Efficient Stream-Relation Join Processing in Data Streaming Engines
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
gro.facultyGriffith Sciences, School of Information and Communication Technology
gro.date.issued2013
gro.hasfulltextNo Full Text
gro.griffith.authorStantic, Bela
gro.griffith.authorSattar, Abdul
gro.griffith.authorDerakhshan, Roozbeh


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    Contains papers delivered by Griffith authors at national and international conferences.

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