A parallel pipelined strategy for evaluating linear recursive predicates in a multiprocessor environment

Abstract

A parallel pipelined strategy for evaluating single linear recurssive predicates in a multiprocessor system is described. A top-down compiling technique generates the resolvents corresponding to the recursive predicate. While evaluating the resolvents against the database relations, the proposed strategy exploits three database query optimization techniques. We develop an analytical model for the proposed evaluation strategy; it models the execution of the pipelined butterfly hash-join operation. In an analytical performance evaluation, we compare the proposed strategy with a sequential and parallel bottom-up semi-naive algorithm, for computing the transitive closure of a database relation. We measure the response time and execution time for each resolvent. The speedup demonstrates the benefits of the parallel pipelined strategy; the performance evaluation indicates that it can increasingly benefit from each additional processor used, as larger relations are passed along the pipeline. A steady pipeline can be maintained even when hash table overflow occurs due to memory limitations.