Efficient Indices Using Graph Partitioning in RDF Triple Stores

With the advance of the Semantic Web, varying RDF data were increasingly generated, published, queried, and reused via the Web. For example, the DBpedia, a community effort to extract structured data from Wikipedia articles, broke 100 million RDF triples in its latest release. Initiated by Tim Berners-Lee, likewise, the Linking Open Data (LOD) project has published and interlinked many open licence datasets which consisted of over 2 billion RDF triples so far. In this context, fast query response over such large scaled data would be one of the challenges to existing RDF data stores. In this paper, we propose a novel triple indexing scheme to help RDF query engine fast locate the instances within a small scope. By considering the RDF data as a graph, we would partition the graph into multiple subgraph pieces and store them individually, over which a signature tree would be built up to index the URIs. When a query arrives, the signature tree index is used to fast locate the partitions th...

• Type: Conference
• Year: 2009
• Where: ICDE
• Authors: Ying Yan, Chen Wang, Aoying Zhou, Weining Qian, Li Ma, Yue Pan
• Keywords: Database, ICDE 2009, Query Processing Time, Query Response, RDF Data Stores, RDF Query Engine, RDF Triples