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A Constraint-Aware Query Optimizer for Web-Based Data Integration

Web has brought forth opportunities to connect information sources across all types of boundaries. Data integration is to combine data residing at different sources and providing the user with a unified view of these data. Currently users are expecting more efficient services from such data integration systems. This paper describes a query optimizer, which uses constraints to semantically optimize the queries. The optimizer first translates constraints from data sources into constraints expressed at the global level and stores them in the constraint repository. Then the optimizer can use semantic query optimization technologies including detection of empty results, join elimination, and predicate elimination to generate a more efficient but semantically equivalent query for the user. The optmizer is published as a web service and can be invoked by many data integration systems. We carry out experiments and first results show that performance can be greatly improved.