A dichotomy in the complexity of consistent query answering for queries with two atoms

Kolaitis, Phokion G.; Pema, Enela

doi:10.1016/j.ipl.2011.10.018

Cited by 43 publications

(33 citation statements)

References 12 publications

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“…Its cases depend on the set of MDs, for a fixed class of queries. In CQA with FDs, dichotomy results have been obtained for limited classes of conjunctive queries [15,16,18]. However, in CQA the cases depend mainly on the queries, as opposed to FDs.…”

Section: Discussionmentioning

confidence: 99%

Tractable vs. Intractable Cases of Query Answering under Matching Dependencies

Bertossi

Gardezi

2014

Lecture Notes in Computer Science

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Abstract. Matching Dependencies (MDs) are a recent proposal for declarative entity resolution. They are rules that specify, on the basis of similarities satisfied by values in a database, what values should be considered duplicates, and have to be matched. On the basis of a chase-like procedure for MD enforcement, we can obtain clean (duplicate-free), and possibly several, resolved instances. The resolved answers to a query are invariant under the class of resolved instances. Previous work identified classes of queries and sets of MDs for which resolved query answering is tractable, with special emphasis on cyclic sets of MDs. In this work we further investigate the complexity of this problem, identifying intractable cases, and exploring the frontier between tractability and intractability. We concentrate mostly on acyclic sets of MDs. For a special case we obtain a dichotomy result relative to NP-hardness.

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Section: Discussionmentioning

confidence: 99%

Tractable vs. Intractable Cases of Query Answering under Matching Dependencies

Bertossi

Gardezi

2014

Lecture Notes in Computer Science

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“…• For each self-join-free conjunctive query q with exactly two atoms, CERTAINTY(q) is either in P or coNPcomplete, and it is decidable which of the two cases applies [17]. The sufficient condition for coNP-completeness has later on been generalized to more than two atoms [33].…”

Section: Related Workmentioning

confidence: 99%

“…q4(x) = ∃u∃v∃w∃y∃z R(u, v, w, x, y, z) ∧ S(y, z, ' * * * ') It is coNP-complete to decide, given an uncertain database db and a salary c on input, whether c is a certain answer to q4 on db [17]. Therefore, any known algorithm (be it EQUIP or another) which computes all certain answers will be exponential-time in the size of the input database.…”

Section: Experimental Evidencementioning

confidence: 99%

“…Earlier work [17] implies that CERTAINTY(q1) is coNPcomplete. Nevertheless, the results in the current article will imply that CERTAINTY(q1, {σ1}) is first-order expressible and hence in the low complexity class AC 0 .…”

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confidence: 98%

“…Given a Boolean query q, the problem CERTAINTY(q) takes as input an uncertain database db and asks whether q evaluates to true on every repair of db. In the last few years, the complexity of this problem has been studied in particular for q ranging over the class of Boolean conjunctive queries without self-join [16,17,30,31,32,33]. In this case, the complexity varies from AC 0 to coNP-complete, depending on q.…”

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confidence: 99%

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Certain query answering in partially consistent databases

2014

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A database is called uncertain if two or more tuples of the same relation are allowed to agree on their primary key. Intuitively, such tuples act as alternatives for each other. A repair (or possible world) of such uncertain database is obtained by selecting a maximal number of tuples without ever selecting two tuples of the same relation that agree on their primary key. For a Boolean query q, the problem CERTAINTY(q) takes as input an uncertain database db and asks whether q evaluates to true on every repair of db. In recent years, the complexity of CERTAINTY(q) has been studied under different restrictions on q. These complexity studies have assumed no restrictions on the uncertain databases that are input to CERTAINTY(q). In practice, however, it may be known that these input databases are partially consistent, in the sense that they satisfy some dependencies (e.g., functional dependencies). In this article, we introduce the problem CERTAINTY(q) in the presence of a set Σ of dependencies. The problem CERTAINTY(q, Σ) takes as input an uncertain database db that satisfies Σ, and asks whether every repair of db satisfies q.We focus on the complexity of CERTAINTY(q, Σ) when q is an acyclic conjunctive query without self-join, and Σ is a set of functional dependencies and join dependencies, the latter of a particular form. We provide an algorithm that, given q and Σ, decides whether CERTAINTY(q, Σ) is first-order expressible. Moreover, we show how to effectively construct a first-order definition of CERTAINTY(q, Σ) if it exists.

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A SAT-Based System for Consistent Query Answering

Dixit

Kolaitis

2019

Lecture Notes in Computer Science

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An inconsistent database is a database that violates one or more integrity constraints, such as functional dependencies. Consistent Query Answering is a rigorous and principled approach to the semantics of queries posed against inconsistent databases. The consistent answers to a query on an inconsistent database is the intersection of the answers to the query on every repair, i.e., on every consistent database that differs from the given inconsistent one in a minimal way. Computing the consistent answers of a fixed conjunctive query on a given inconsistent database can be a coNP-hard problem, even though every fixed conjunctive query is efficiently computable on a given consistent database. We designed, implemented, and evaluated CAvSAT, a SAT-based system for consistent query answering. CAvSAT leverages a set of natural reductions from the complement of consistent query answering to SAT and to Weighted MaxSAT. The system is capable of handling unions of conjunctive queries and arbitrary denial constraints, which include functional dependencies as a special case. We report results from experiments evaluating CAvSAT on both synthetic and realworld databases. These results provide evidence that a SAT-based approach can give rise to a comprehensive and scalable system for consistent query answering.

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A dichotomy in the complexity of consistent query answering for queries with two atoms

Cited by 43 publications

References 12 publications

Tractable vs. Intractable Cases of Query Answering under Matching Dependencies

Tractable vs. Intractable Cases of Query Answering under Matching Dependencies

Certain query answering in partially consistent databases

A SAT-Based System for Consistent Query Answering

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