XSPARQL is a language for transforming data between XML and RDF. XML is a widely used format for data exchange. RDF is a data format based on directed graphs, primarily used to represent Semantic Web data. XSPARQL is built by combining the strengths of the two corresponding query languages XQuery for XML, and SPARQL for RDF. In this talk we will present two new XSPARQL enhancements called Constructed Dataset and Dataset Scoping, the XDEP dependent join optimization, and a new XSPARQL implementation. Constructed Dataset allows to create intermediary RDF graphs while querying data sources. The Dataset Scoping enhancement provides an optional fix for unintended results which may occur when evaluating complex XSPARQL queries containing nested SPARQL queries. The XSPARQL implementation works by first rewriting an XSPARQL to XQuery expressions containing interleaved calls to a SPARQL engine. The resulting query is then evaluated by standard XQuery and SPARQL engines. The dependent join optimization XDEP is designed to reduce query evaluation time for queries demanding repeated evaluation of embedded SPARQL query parts. XDEP minimizes the number of interactions between the XQuery and SPARQL engines by bundling similar queries and let XQuery engines select relevant data on their own. We did an experimental evaluation of our approach using an adapted version of the XQuery benchmark suite XMark. We will show that the XDEP optimization reduces the evaluation time of all compatible benchmark queries. Using this optimization we could evaluate certain XSPARQL queries by two orders of magnitude faster than with unoptimized XSPARQL.
See also http://stefanbischof.at/masterthesis/ for the full text.