A Uniform Fixpoint Approach to the Implementation of Inference Methods for Deductive Databases

TL;DR

This paper introduces a unified fixpoint-based inference method for deductive databases, enabling efficient implementation of query evaluation, update propagation, and view updating within SQL systems.

Contribution

It proposes a new uniform soft consequence operator and improved transformation techniques for query optimization and updates in deductive databases.

Findings

Unified fixpoint approach simplifies implementation

Enhanced transformation methods improve performance

Operator supports multiple database tasks efficiently

Abstract

Within the research area of deductive databases three different database tasks have been deeply investigated: query evaluation, update propagation and view updating. Over the last thirty years various inference mechanisms have been proposed for realizing these main functionalities of a rule-based system. However, these inference mechanisms have been rarely used in commercial DB systems until now. One important reason for this is the lack of a uniform approach well-suited for implementation in an SQL-based system. In this paper, we present such a uniform approach in form of a new version of the soft consequence operator. Additionally, we present improved transformation-based approaches to query optimization and update propagation and view updating which are all using this operator as underlying evaluation mechanism.