A Parallel Algorithm for the Generalized Partially Instantiated Same Generation Query in Deductive Databases

Abstract

The expressive power and intelligence of traditional database systems can be improved by recursion. Using recursion, relational database systems are extended into knowledge-base systems (deductive database systems). Linear recursion is the most frequently found type of recursion in deductive databases. Deductive databases queries are computationally intensive and lend themselves naturally to parallelization to speed up the solution of such queries. In this paper, a parallel algorithm to solve the generalized partially instantiated form of the same generation query in deductive databases is presented. The algorithm uses special data structures, namely, a special matrix that stores paths from source nodes of the graph representing a two-attribute normalized database relation to all nodes reachable from these source nodes, and a reverse matrix that stores paths from any node to all source nodes related to that node.