A framework for the parallel processing of Datalog queries

Authors:
Sumit Ganguly;Avi Silberschatz;Shalom Tsur
Affiliations:
Department of Computer Sciences, The University of Texas, Austin, Texas;Department of Computer Sciences, The University of Texas, Austin, Texas;Mcroelectronics and Computer Technology Corporation, Austin, Texas
Venue:
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
Year:
1990

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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 non-redundant 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 results is a non-redundant computation, is also studied. The methods reported in this paper clearly demonstrate the trade-offs between redundancy and interprocessor-communication for this class of problems.