Optimizing SPARQL queries on multi-core processors
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The Semantic Web is an extension of the current World Wide Web where information is represented in a machine processable way. Resource Description Framework (RDF) is the format created for publishing data in the Semantic Web and SPARQL is the standard language for querying RDF data. The size of the RDF data sets being published has been ever increasing. Consequently, the execution times of SPARQL queries have been growing, as well. In this thesis, we present a novel SPARQL query execution algorithm which takes advantage of multi-processor and multi-core architectures and executes individual queries in parallel. We have implemented our algorithm in Java using Java threads and conducted a number of experiments on a multi-processor, multi-core computer system to assess the efficiency of the algorithm. The results of the experiments indicate a significant speed up of our parallel approach in comparison to the sequential SPARQL query processors in use today.