RCQ-GA: RDF Chain Query Optimization Using Genetic Algorithms

Authors:
Alexander Hogenboom;Viorel Milea;Flavius Frasincar;Uzay Kaymak
Affiliations:
Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, The Netherlands 3000;Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, The Netherlands 3000;Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, The Netherlands 3000;Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, The Netherlands 3000
Venue:
EC-Web 2009 Proceedings of the 10th International Conference on E-Commerce and Web Technologies
Year:
2009

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Abstract

The application of Semantic Web technologies in an Electronic Commerce environment implies a need for good support tools. Fast query engines are needed for efficient querying of large amounts of data, usually represented using RDF. We focus on optimizing a special class of SPARQL queries, the so-called RDF chain queries. For this purpose, we devise a genetic algorithm called RCQ-GA that determines the order in which joins need to be performed for an efficient evaluation of RDF chain queries. The approach is benchmarked against a two-phase optimization algorithm, previously proposed in literature. The more complex a query is, the more RCQ-GA outperforms the benchmark in solution quality, execution time needed, and consistency of solution quality. When the algorithms are constrained by a time limit, the overall performance of RCQ-GA compared to the benchmark further improves.