Efficient Rank Join with Aggregation Constraints

The authors show aggregation constraints that naturally arise in several applications can enrich the semantics of rank join queries, by allowing users to impose their application-specific preferences in a declarative way. By analyzing the properties of aggregation constraints, they develop efficient deterministic and probabilistic algorithms which can push the aggregation constraints inside the rank join framework. Through extensive experiments on various datasets, they show that in many cases their proposed algorithms can significantly outperform the naive approach of applying the state-of-the-art rank join algorithm followed by post-filtering to discard results violating the constraints.

Provided by: VLD Digital Topic: Data Management Date Added: Sep 2011 Format: PDF

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