Pay-as-you-go information integration: The semantic model approach
Rada Y. Chirkova, Dongfeng Chen, Fereidoon Sadri, Timo J. Salo · NCSU Libraries Repository (North Carolina State University Libraries) · 2007
This paper describes algorithms for query processing and optimization in our semantic-model approach to large-scale information integration and interoperability, and experimentally evaluates the algorithms on real-life and synthetic data. In addition to supporting gradual (pay-as-you-go) large-scale information integration and efficient inter-source (join) processing, the semantic-model approach, first described in [34], eliminates the need for mediation in deriving the global schema, thus addressing the main limitation [49] of dataintegration systems. The focus of our study in this paper is performance-related characteristics of several alternative approaches that we propose for efficient query processing in the semantic-model environment. Our theoretical results and practical algorithms are of independent interest and can be used in any information-integration system that avoids loading all the data into a single repository. In addition, we present an experimental study of our techniques on reallife and synthetic data. Our experimental results establish the efficiency of our algorithms, and, further allow us to make context-specific recommendations on selecting queryprocessing approaches from our proposed alternatives. As such, the approaches we propose form a basis for scalable query processing in information integration and interoperability.