Semantic Optimization Techniques for Preference Queries

TL;DR

This paper introduces semantic optimization techniques for preference queries in relational databases, leveraging integrity constraints like constraint-generating dependencies to improve query evaluation and optimization.

Contribution

It identifies fundamental properties for optimizing preference queries using integrity constraints and formulates conditions as constraint validity problems, extending the theoretical framework.

Findings

Containment and satisfaction of order axioms can be reduced to dependency entailment.

Necessary and sufficient conditions for optimization techniques are characterized.

The computational complexity of these problems is analyzed.

Abstract

Preference queries are relational algebra or SQL queries that contain occurrences of the winnow operator ("find the most preferred tuples in a given relation"). Such queries are parameterized by specific preference relations. Semantic optimization techniques make use of integrity constraints holding in the database. In the context of semantic optimization of preference queries, we identify two fundamental properties: containment of preference relations relative to integrity constraints and satisfaction of order axioms relative to integrity constraints. We show numerous applications of those notions to preference query evaluation and optimization. As integrity constraints, we consider constraint-generating dependencies, a class generalizing functional dependencies. We demonstrate that the problems of containment and satisfaction of order axioms can be captured as specific instances of constraint-generating dependency entailment. This makes it possible to formulate necessary and sufficient conditions for the applicability of our techniques as constraint validity problems. We characterize the computational complexity of such problems.