| Database support for matching: limitations and opportunities |
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International Conference on Management of Data
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Proceedings of the 2006 ACM SIGMOD international conference on Management of data
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Chicago, IL, USA
SESSION: Database technology for novel applications
table of contents
Pages: 85 - 96
Year of Publication: 2006
ISBN:1-59593-434-0
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Downloads (6 Weeks): 7, Downloads (12 Months): 72, Citation Count: 1
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ABSTRACT
We define a match join of R and S with predicate θ to be a subset of the θ-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 belong to a broad class of matching problems that have attracted a great deal of attention in disciplines including operations research and theoretical computer science. Instances of these problems arise in practice in resource allocation scenarios. To the best of our knowledge no one uses an RDBMS as a tool to help solve these problems; our goal in this paper is to explore whether or not this needs to be the case. We show that the simple approach of computing the full θ-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 related problems beyond merely serving as expensive file systems exporting data sets to external user programs.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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CITED BY
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David J. DeWitt , Erik Paulson , Eric Robinson , Jeffrey Naughton , Joshua Royalty , Srinath Shankar , Andrew Krioukov, Clustera: an integrated computation and data management system, Proceedings of the VLDB Endowment, v.1 n.1, August 2008
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