D2R2: Disk-Oriented Deductive Reasoning in a RISC-Style RDF Engine
Deductive reasoning lies in the expressive intersection of Datalog and Description Logics. In this paper, we present the D2R2 engine, which implements deductive reasoning capabilities based on the Query-Sub-Query (QSQR) algorithm on top of the disk-oriented RDF-3X engine. D2R2 aims to bridge the gap between rule-oriented (intensional) reasoning with deduction rules and data-oriented (extensional) processing of large joins, over a set of highly tuned, disk-based index structures for large RDF collections. We present a generalization of QSQR, which allows for dynamic sub-query scheduling and chaining of extensional predicates into atomic join patterns—two key extensions for coupling QSQR with a disk-oriented storage backend. Experiments over a set of recursive queries and a very large knowledge base, consisting of 20 million RDF facts, as well as comparisons to disk-oriented reasoning engines, confirm the practical viability and significant runtime improvements of D2R2 compared to these engines.
KeywordsDeductive reasoning QSQR disk-oriented RDF processing
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