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CDB
2004
Springer

Constraint Processing Techniques for Improving Join Computation: A Proof of Concept

14 years 5 months ago
Constraint Processing Techniques for Improving Join Computation: A Proof of Concept
Constraint Processing and Database techniques overlap significantly. We discuss here the application of a constraint satisfaction technique, called dynamic bundling, to databases. We model the join query computation as a Constraint Satisfaction Problem (CSP) and solve it by search using dynamic bundling. First, we introduce a sort-based technique for computing dynamic bundling. Then, we describe the join algorithm that produces nested tuples. The resulting process yields a compact solution space and savings of memory, disk-space, and/or network bandwidth. We realize further savings by using bundling to reduce the number of join-condition checks. We place our bundling technique in the framework of the Progressive Merge Join (PMJ) [1] and use the XXL library [2] for implementing and testing our algorithm. PMJ assists in effective query-result-size prediction by producing early results. Our algorithm reinforces this feature of PMJ by producing the tuples as multiple solutions and is thus...
Anagh Lal, Berthe Y. Choueiry
Added 01 Jul 2010
Updated 01 Jul 2010
Type Conference
Year 2004
Where CDB
Authors Anagh Lal, Berthe Y. Choueiry
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