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Database support for matching: limitations and opportunities
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Proceedings of the 2006 ACM SIGMOD international conference on Management of data table of contents
Chicago, IL, USA
SESSION: Database technology for novel applications table of contents
Pages: 85 - 96  
Year of Publication: 2006
ISBN:1-59593-434-0
Authors
Ameet Kini  University of Wisconsin - Madison, Madison, WI
Srinath Shankar  University of Wisconsin - Madison, Madison, WI
Jeffrey F. Naughton  University of Wisconsin - Madison, Madison, WI
David J. Dewitt  University of Wisconsin - Madison, Madison, WI
Sponsors
ACM: Association for Computing Machinery
SIGMOD: ACM Special Interest Group on Management of Data
Publisher
ACM  New York, NY, USA
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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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C. Berge, "Two Theorems in Graph Theory" Proceedings of the National Academy of Science USA, 1957, p. 842--844.
5
 
6
J. Feigenbaum et al., "On Graph Problems in a Semi-Streaming Model", Proceedings of ICALP 2004, p. 531--543
7
 
8
 
9
S. Guha et al. "Efficient Approximation of Optimization Queries Under Parametric Aggregation Constraints", Proceedings of VLDB 2003, p. 778--789
 
10
S. Guha et al. "Merging the Results of Approximate Match Operations", Proceedings of VLDB 2004, p. 636--647.
 
11
J. Hopcroft and R. Karp. "An n5/2 Algorithm for Maximum Matching in Bipartite Graphs", SIAM Journal of Computing, 1975, p. 225--231.
 
12
13
 
14
J. Magun. "Greedy Matching Algorithms: An experimental study", Proceedings of the 1st Workshop on Algorithm Engineering, p. 22--31, 1997.
 
15
 
16
Predator Project. http://www.distlab.dk/predator/
 
17
 
18
C. Schlup. "Automatic Game Matching", http://dcg.ethz.ch/theses/ws0203/OnlineMatching_abstract.pdf
 
19
 
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P. Tsaparas et al. "Ranked Join Indices", Proceedings of IEEE ICDE 2003, p. 277--288.
 
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Collaborative Colleagues:
Ameet Kini: colleagues
Srinath Shankar: colleagues
Jeffrey F. Naughton: colleagues
David J. Dewitt: colleagues