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| Content Provider | ACM Digital Library |
|---|---|
| Author | Vlachou, Akrivi Polyzotis, Neoklis Doulkeridis, Christos |
| Abstract | This paper addresses the problem of efficiently computing the skyline set of a relational join. Existing techniques either require to access all tuples of the input relations or demand specialized multi-dimensional access methods to generate the skyline join result. To avoid these inefficiencies, we introduce the novel SFSJ algorithm that fuses the identification of skyline tuples with the computation of the join. SFSJ is able to compute the correct skyline set by accessing only a subset of the input tuples, i.e., it has the property of early termination. SFSJ employs standard access methods for reading the input tuples and is readily implementable in an existing database system. Moreover, it can be used in pipelined execution plans, as it generates the skyline tuples progressively. Additionally, we formally analyze the performance of SFSJ and propose a novel strategy for accessing the input tuples that is proven to be optimal for SFSJ. Finally, we present an extensive experimental study that validates the effectiveness of SFSJ and demonstrates its advantages over existing techniques. |
| Starting Page | 73 |
| Ending Page | 84 |
| Page Count | 12 |
| File Format | |
| ISBN | 9781450306614 |
| DOI | 10.1145/1989323.1989332 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2011-06-12 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Join operator Skyline query |
| Content Type | Text |
| Resource Type | Article |
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