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Evaluating Adaptive Query Processing Techniques for Federations of SPARQL Endpoints

Veröffentlichung: 2011 November
Art der Veröffentlichung: 10th International Semantic Web Conference (ISWC) Demo Session

We present ANAPSID and illustrate the benefits of adap- tive semantic data management techniques for accessing a federation of SPARQL endpoints. ANAPSID adapts query execution schedulers to data availability and runtime conditions, implements physical SPARQL operators that detect when an endpoint becomes blocked or data traf- fic is bursty, and opportunistically produces results as quickly as data arrives from the sources. Additionally, ANAPSID operators implement main memory replacement policies to move previous computed matches to secondary memory avoiding duplicates. We show ANAPSID perfor- mance with respect to a variety of RDF engines for queries of diverse complexity, and show that ANAPSID may outperform existing engines.

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