Consistent Answers of Aggregation Queries using SAT Solvers

TL;DR

This paper introduces a novel system that computes consistent answers for complex aggregation queries in inconsistent databases by leveraging SAT solvers, demonstrating scalability and practical utility through extensive experiments.

Contribution

First system to compute consistent answers for general aggregation queries using reductions to SAT optimization problems.

Findings

Effective handling of COUNT, SUM, MIN, MAX aggregation queries.

Scalable performance demonstrated on synthetic and real-world data.

Leverages powerful SAT solvers for practical computation.

Abstract

The framework of database repairs and consistent answers to queries is a principled approach to managing inconsistent databases. We describe the first system able to compute the consistent answers of general aggregation queries with the COUNT(A), COUNT(*), SUM(A), MIN(A), and MAX(A) operators, and with or without grouping constructs. Our system uses reductions to optimization versions of Boolean satisfiability (SAT) and then leverages powerful SAT solvers. We carry out an extensive set of experiments on both synthetic and real-world data that demonstrate the usefulness and scalability of this approach.