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XML-Based RDF Data Management for Efficient Query Processing Mo Zhou advised by Prof. Yuqing Wu

XML-Based RDF Data Management for Efficient Query Processing Mo Zhou advised by Prof. Yuqing Wu. Problem and Related Works RDF data and query RDF data model SPARQL Query Relational approaches for storing RDF data

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XML-Based RDF Data Management for Efficient Query Processing Mo Zhou advised by Prof. Yuqing Wu

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  1. XML-Based RDF Data Management for Efficient Query Processing Mo Zhou advised by Prof. Yuqing Wu • Problem and Related Works • RDF data and query RDF data model SPARQL Query • Relational approaches for storing RDF data • Triple Store (TS) Vertical Partition (VP) Property Table (PT) • The desired properties of RDF storage model • Preserve semantics High performance Scalable Small overhead • Our Proposal • Use XML technologies to achieve high storage and query efficiency of RDF data. avgRate Review text • RDF Schema Decomposition • gR2X: Decompose RDF schema into XML schemas with deep tree shape and small duplication • wR2X: Decompose RDF schema into XML schemas that can represent frequent queried paths in a workload. • RDF Data Decomposition • SPARQL-to-XQuery Rewrite • Class/Predicate determination: Associate possible classes to each node and possible matching to each predicate variables in the SPARQL query. • SPARQL query decomposition: Decompose the SPARQL query graph into trees. • XQuery query construction: Construct XQuery queries based on the trees. gR2X wR2X • Decompose RDF data conforming to the RDF schema to XML documents conforming to the XML schemas. • Experimental Results • The experiments were carried out on MonetDB using Berlin Benchmark. Performance comparison on 5 million triples Scalability Comparison XML-Based RDF Data Management for Efficient Query Processing, Mo Zhou, Yuqing Wu, technical report TR683, Computer Science, Indiana University, 2010

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