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SemStore
2014
Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management - CIKM '14
The flexibility of the RDF data model has attracted an increasing number of organizations to store their data in an RDF format. With the rapid growth of RDF datasets, we envision that it is inevitable to deploy a cluster of computing nodes to process large-scale RDF data in order to deliver desirable query performance. In this paper, we address the challenging problems of data partitioning and query optimization in a scale-out RDF engine. We identify that existing approaches only focus on using
doi:10.1145/2661829.2661876
dblp:conf/cikm/WuZYJL14
fatcat:4szayunflfdslogpsfaijyyvfu