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| Content Provider | ACM Digital Library |
|---|---|
| Author | Dewitt, David J. Kini, Ameet Shankar, Srinath Naughton, Jeffrey F. |
| 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. |
| Starting Page | 85 |
| Ending Page | 96 |
| Page Count | 12 |
| File Format | |
| ISBN | 1595934340 |
| DOI | 10.1145/1142473.1142484 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2006-06-27 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Matching Join Advanced query types |
| Content Type | Text |
| Resource Type | Article |
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