This paper describes the use of bitmap indices for optimizing Storage of RDF triples. Implementation techniques are described and results analyzed for different size data sets, up to a billion triples.
We show how we can load the 1 billion triple LUBM benchmark set with a sustained rate of 12692 triples/s and the 47M triple Wikipedia data set at a rate of 20800 triples/s.
The Lehigh University Benchmark is developed to facilitate the evaluation of Semantic Web repositories in a standard and systematic way. The benchmark is intended to evaluate the performance of those repositories with respect to extensional queries over a large data set that commits to a single realistic ontology. It consists of a university domain ontology, customizable and repeatable synthetic data, a set of test queries, and several performance metrics.