Abstract

This paper presents several complementary methods for the parallel, bottom-up evaluation of Datalog queries. We introduce the notion of a discriminating predicate, based on hash functions, that partitions the computation between the processors in order to achieve parallelism. A parallelization scheme with the property of nonredundant computation (no duplication of computation by processors) is then studied in detail. The mapping of Datalog programs onto a network of processors, such that the result is a nonredundant computation, is also studied.

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