Type-based Semantic Optimization for Scalable RDF Graph Pattern Matching
HyeongSik Kim, Padmashree Ravindra, Kemafor Anyanwu · 2017
Scalable query processing relies on early and aggressive determination and pruning of query-irrelevant data. Besides the traditional space-pruning techniques such as indexing, type-based optimizations that exploit integrity constraints defined on the types can be used to rewrite queries into more efficient ones. However, such optimizations are only applicable in strongly-typed data and query models which make it a challenge for semi-structured models such as RDF. Consequently, developing techniques for enabling typebased query optimizations will contribute new insight to improving the scalability of RDF processing systems.