Abstract
The optimization effect on large-scale RDF data is not statisfactory using the existing algorithms based on cost models. This paper presents the Run-time Optimization of SPARQL queries (ROS), and describes the join graphs and the index structures for SPARQL queries that are foundations of the ROS approach. The ROS algorithm, without cost models, intertwines cost estimation and query optimization into the execution procedure, and determines query plans in run time. Our experiments using the SP2Bench benchmark show that ROS can select the best query plan and improve query efficiency dramatically compared with the existing approaches. © 2011 Springer-Verlag.
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CITATION STYLE
Li, L., Wang, X., Meng, X., & Feng, Z. (2011). ROS: Run-time optimization of SPARQL queries. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6988 LNCS, pp. 79–86). https://doi.org/10.1007/978-3-642-23982-3_11
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