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dc.contributor.authorKini, Ameeten_US
dc.contributor.authorShankar, Srinathen_US
dc.contributor.authorDeWitt, Daviden_US
dc.contributor.authorNaughton, Jeffreyen_US
dc.date.accessioned2012-03-15T17:19:47Z
dc.date.available2012-03-15T17:19:47Z
dc.date.created2005en_US
dc.date.issued2005en_US
dc.identifier.citationTR1545en_US
dc.identifier.urihttp://digital.library.wisc.edu/1793/60472
dc.description.abstractA match join of R and S with predicate theta is a subset of the theta join of R and S such that each tuple of R and S contributes to at most one result tuple. Match joins and their generalizations arise in many scenarios, including one that was our original motivation, assigning jobs to processors in the Condor distributed job scheduling system. We explore the use of RDBMS technology to compute match joins. We show that the simplest approach of computing the full theta join and then applying standard graph-matching algorithms to the result is ineffective for all but the smallest of problem instances. By contrast, a closer study shows that the DBMS primitives of grouping, sorting, and joining can be exploited to yield efficient match join operations. This suggests that RDBMSs can play a role in matching beyond merely serving as passive storage for external programs.en_US
dc.format.mimetypeapplication/pdfen_US
dc.publisherUniversity of Wisconsin-Madison Department of Computer Sciencesen_US
dc.titleDatabase Support for Matching: Limitations and Opportunitiesen_US
dc.typeTechnical Reporten_US


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    Technical Reports Archive for the Department of Computer Sciences at the University of Wisconsin-Madison

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