[Paper Review] Consistent Query Answering via ASP from Different Perspectives: Theory and Practice

Marco Manna, Francesco Ricca+1 more|arXiv (Cornell University)|Jul 22, 2011

Logic, Reasoning, and Knowledge33 references4 citations

TL;DR

This paper presents a unified, ASP-based framework for consistent query answering (CQA) across multiple semantics—sound, complete, and exact—by encoding CQA as cautious reasoning over disjunctive ASP programs with aggregates. It introduces query-driven optimizations that localize computation and reduce complexity, enabling efficient handling of large-scale data integration workloads with proven scalability and support for key constraints (KDs and INDs).

ABSTRACT

A data integration system provides transparent access to different data sources by suitably combining their data, and providing the user with a unified view of them, called global schema. However, source data are generally not under the control of the data integration process, thus integrated data may violate global integrity constraints even in presence of locally-consistent data sources. In this scenario, it may be anyway interesting to retrieve as much consistent information as possible. The process of answering user queries under global constraint violations is called consistent query answering (CQA). Several notions of CQA have been proposed, e.g., depending on whether integrated information is assumed to be sound, complete, exact or a variant of them. This paper provides a contribution in this setting: it uniforms solutions coming from different perspectives under a common ASP-based core, and provides query-driven optimizations designed for isolating and eliminating inefficiencies of the general approach for computing consistent answers. Moreover, the paper introduces some new theoretical results enriching existing knowledge on decidability and complexity of the considered problems. The effectiveness of the approach is evidenced by experimental results. To appear in Theory and Practice of Logic Programming (TPLP).

Motivation & Objective

• Address the challenge of consistent query answering (CQA) in data integration systems where global integrity constraints may be violated despite locally consistent data sources.
• Unify diverse CQA semantics—loosely-sound, loosely-complete, and loosely-exact—under a single declarative ASP-based core to enable consistent reasoning across different assumptions about data quality.
• Overcome the inherent computational hardness of CQA by introducing query-driven optimizations that localize and simplify repair computation, reducing complexity and improving scalability.
• Develop and implement a full-featured prototype system capable of handling real-world data integration workloads with large-scale data and complex constraints.
• Extend decidability boundaries for CQA under the loosely-exact and loosely-sound semantics when dealing with key dependencies (KDs) and foreign key-like inclusion dependencies (SFSK INDs).

Proposed method

• Formalize CQA as cautious reasoning over disjunctive ASP programs with aggregates, automatically generated from user queries and global integrity constraints.
• Introduce a query-aware rewriting mechanism that constructs ASP programs tailored to the specific query and constraint structure, enabling precise and efficient computation of consistent answers.
• Design a novel optimization technique—'vertical' simplification—that reduces the arity of active relations by localizing and simplifying relevant constraints, thereby minimizing the number of candidate repairs.
• Integrate the DLV DB system as the underlying query evaluator to support mass-memory database operations and distributed data management, enabling scalability on large datasets.
• Apply query-driven filtering to isolate only the minimal set of constraints relevant to the query, avoiding unnecessary computation on irrelevant or redundant constraints.
• Combine the ASP-based framework with existing optimization strategies (e.g., magic sets) and extend them to support CQA, ensuring compatibility with broader logic programming techniques.

Experimental results

Research questions

• RQ1 How can different CQA semantics—loosely-sound, loosely-complete, and loosely-exact—be formally unified under a single declarative framework?
• RQ2 What is the computational complexity of CQA under the loosely-exact and loosely-sound semantics when both key dependencies (KDs) and inclusion dependencies (SFSK INDs) are present?
• RQ3 Can query-driven optimizations reduce the computational overhead of CQA by localizing and simplifying constraint processing without sacrificing correctness?
• RQ4 To what extent can ASP-based rewriting and optimization techniques scale on real-world and synthetic data integration workloads with complex constraints?
• RQ5 How does the proposed framework compare in performance and expressiveness to existing systems that support only a subset of CQA semantics or constraint types?

Key findings

• The proposed ASP-based framework successfully unifies three major CQA semantics—loosely-sound, loosely-complete, and loosely-exact—into a single, coherent, and declarative computational model.
• The framework extends decidability boundaries for CQA under the loosely-exact and loosely-sound semantics, even in the presence of both key dependencies (KDs) and inclusion dependencies (SFSK INDs).
• The query-driven optimization strategy significantly reduces the number of candidate repairs by simplifying constraint structures, leading to improved performance and reduced computational complexity.
• Experimental evaluation on real-world and synthetic data demonstrates the scalability and efficiency of the prototype system, particularly under conjunctive queries and common database constraints.
• The integration of the DLV DB system enables effective handling of large-scale data, confirming the feasibility of the approach in real-world data integration scenarios.
• The system supports a complete stack including a user-friendly GUI, full constraint support (KDs and INDs), and multiple semantics, outperforming prior systems that were limited to single semantics or constraint types.