SPARQL Query Optimization for Structural Indexed RDF Data

Resource description framework, RDF, is a standard language model for representing semantic data. As the concept of Semantic Web becomes more viable, the ability to retrieve and exchange semantic data will become increasingly more important. Efficient management of RDF data is one of the key research issues in Semantic Web; consequently, many RDF management systems have been proposed with data storage architectures and query processing algorithms for data retrieval. However, most of the proposed approaches require many join operations that result in the unnecessary processing of intermediate results for SPARQL queries. The additional processing becomes substantial as the RDF data volume is increased. In this paper, we propose an efficient structural index and a query optimizer to process queries without join operations. Empirical experimental results show that our proposed system outperforms conventional query processing approaches, such as Jena, up to 79% in terms of query processing time by reducing the volume of unnecessary intermediate results.