Taming Primary Key Violations to Query Large Inconsistent Data

TL;DR

This paper introduces a novel ASP-based decomposition strategy that efficiently computes consistent query answers over large, inconsistent databases with primary key violations, overcoming previous size limitations.

Contribution

It presents a polynomial-time decomposition and pruning method for consistent query answering, enabling logic programming solutions to scale to large datasets.

Findings

Effective on large datasets in benchmarks

Reduces problem complexity via decomposition

Demonstrates efficiency of ASP approach

Abstract

Consistent query answering over a database that violates primary key constraints is a classical hard problem in database research that has been traditionally dealt with logic programming. However, the applicability of existing logic-based solutions is restricted to data sets of moderate size. This paper presents a novel decomposition and pruning strategy that reduces, in polynomial time, the problem of computing the consistent answer to a conjunctive query over a database subject to primary key constraints to a collection of smaller problems of the same sort that can be solved independently. The new strategy is naturally modeled and implemented using Answer Set Programming (ASP). An experiment run on benchmarks from the database world prove the effectiveness and efficiency of our ASP-based approach also on large data sets. To appear in Theory and Practice of Logic Programming (TPLP), Proceedings of ICLP 2015.