Relational storage and efficient retrieval of rules in a deductive DBMS

A method is proposed to store and efficiently retrieve rules in a deductive database. The rules are compiled into an execution model called a PCN (production compilation network). The PCN is stored as a particular relational database which consists of three relations. For a given end-user query the first step of the inference process consists of searching for the relevant rules by traversing the PCN structure. This traversal is computed by a transitive closure of a part of the PCN. The transitive closure is performed by a loop of joins over the relations storing the PCN. In this context, a transitive closure algorithm that is based on a physical clustering of the relations is proposed. This clustering consists of a double hashing technique. It ensures a linear cost for the join operation with weak conditions on the size of the main memory. The approach reduces the number of I/O operations for semi-naive transitive closure operation. This algorithm will be applied to the search for relevant rules and to the transitive computation of linear recursive relations