Efficiently Querying RDF Data in Triple Stores
Efficiently querying RDF 1 data is being an important factor in applying Semantic Web technologies to real-world applications. In this context, many e.orts have been made to store and query RDF data in relational database using particular schemas. In this paper, we propose a new scheme to store, index, and query RDF data in triple stores. Graph feature of RDF data is taken into considerations which might help reduce the join costs on the vertical database structure. We would partition RDF triples into overlapped groups, store them in a triple table with one more column of group identity, and build up a signature tree to index them. Based on this infrastructure, a complex RDF query is decomposed into multiple pieces of sub-queries which could be easily.ltered into some RDF groups using signature tree index, and.nally is evaluated with a composed and optimized SQL with speci.c constraints. We compare the performance of our method with prior art on typical queries over a large scaled LUBM and UOBM benchmark data (more than 10 million triples)in 3. For some extreme cases, they can promote 3 to 4 orders of magnitude.
RDF Signature Graph Partitioning Indexing
Ying Yan Chen Wang Aoying Zhou Weining Qian Li Ma Yue Pan
Department of Computer Science and Engineering, Fudan University IBM China Research Laboratory Department of Computer Science and Engineering, Fudan University;Institute of Massive Computing, Eas Institute of Massive Computing, East China Normal University
国际会议
第十七届国际万维网大会(the 17th International World Wide Web Conference)(WWW08)
北京
英文
2008-04-21（万方平台首次上网日期，不代表论文的发表时间）