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dc.contributor.authorXiang, Helen
dc.date.accessioned2014-03-03T14:58:56Z
dc.date.available2014-03-03T14:58:56Z
dc.date.issued2013
dc.identifier.citationXiang , H 2013 , Query optimization over a heterogeneously distributed scientific database . in Procs 2013 IEEE International Conference on Big Data . IEEE , pp. 58-64 , 2013 IEEE Int Conf on Big Data , Santa Clara , United States , 6/10/13 . https://doi.org/10.1109/BigData.2013.6691689
dc.identifier.citationconference
dc.identifier.isbn978-1-4799-1293-3
dc.identifier.otherPURE: 2804216
dc.identifier.otherPURE UUID: 277e367b-1d4a-4888-a4d5-d27dcd3cd348
dc.identifier.otherScopus: 84893309975
dc.identifier.urihttp://hdl.handle.net/2299/12980
dc.description© 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.description.abstractThis paper briefly discusses the concepts about distributed databases management system and distributed query processing. It then talks about the need of distributing large Scientific datasets such as the Sloan Digital Sky Survey. The main focus of this paper is to investigate fully distributed queries involving cross-joins across a heterogeneously distributed scientific database.en
dc.language.isoeng
dc.publisherIEEE
dc.relation.ispartofProcs 2013 IEEE International Conference on Big Data
dc.rightsOpen
dc.titleQuery optimization over a heterogeneously distributed scientific databaseen
dc.contributor.institutionSchool of Computer Science
dc.contributor.institutionScience & Technology Research Institute
dc.contributor.institutionCentre for Computer Science and Informatics Research
dc.relation.schoolSchool of Computer Science
dc.description.versiontypeFinal Accepted Version
dcterms.dateAccepted2013
rioxxterms.versionAM
rioxxterms.versionofrecordhttps://doi.org/10.1109/BigData.2013.6691689
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue
herts.rights.accesstypeOpen


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