Phokion G. Kolaitis

Conjunctive-query containment and constraint satisfaction

Conjunctive-query containment is recognized as a fundamental problem in database query evaluation and optimization. At the same time, constraint satisfaction is recognized as a fundamental problem in artificial intelligence. What do conjunctive-query containment and constraint satisfaction have in common? Our main conceptual contribution in this paper is to point out that, despite their very different formulation, conjunctive-query containment and constraint satisfaction are essentially the same problem. The reason is that they can be recast as the following fundamental algebraic problem: given two finite relational structures A and B, is there a homomorphism h:A?B? As formulated above, the homomorphism problem is uniform in the sense that both relational structures A and B are part of the input. By fixing the structure B, one obtains the following nonuniform problem: given a finite relational structure A, is there a homomorphism h:A?B? In general, nonuniform tractability results do not uniformize. Thus, it is natural to ask: which tractable cases of nonuniform tractability results for constraint satisfaction and conjunctive-query containment do uniformize? Our main technical contribution in this paper is to show that several cases of tractable nonuniform constraint-satisfaction problems do indeed uniformize. We exhibit three nonuniform tractability results that uniformize and, thus, give rise to polynomial-time solvable cases of constraint satisfaction and conjunctive-query containment. We begin by examining the tractable cases of Boolean constraint-satisfaction problems and show that they do uniformize. This can be applied to conjunctive-query containment via Booleanization; in particular, it yields one of the known tractable cases of conjunctive-query containment. After this, we show that tractability results for constraint-satisfaction problems that can be expressed using Datalog programs with bounded number of distinct variables also uniformize. Finally, we provide a new proof for the fact that tractability results for queries with bounded treewidth uniformize as well, via a connection with first-order logic with a bounded number of distinct variables.

Data exchange: getting to the core

Data exchange is the problem of taking data structured under a source schema and creating an instance of a target schema that reflects the source data as accurately as possible. Given a source instance, there may be many solutions to the data exchange problem, that is, many target instances that satisfy the constraints of the data exchange problem. In an earlier article, we identified a special class of solutions that we call universal. A universal solution has homomorphisms into every possible solution, and hence is a “most general possible” solution. Nonetheless, given a source instance, there may be many universal solutions. This naturally raises the question of whether there is a “best” universal solution, and hence a best solution for data exchange. We answer this question by considering the well-known notion of the core of a structure, a notion that was first studied in graph theory, and has also played a role in conjunctive-query processing. The core of a structure is the smallest substructure that is also a homomorphic image of the structure. All universal solutions have the same core (up to isomorphism); we show that this core is also a universal solution, and hence the smallest universal solution. The uniqueness of the core of a universal solution together with its minimality make the core an ideal solution for data exchange. We investigate the computational complexity of producing the core. Well-known results by Chandra and Merlin imply that, unless P = NP, there is no polynomial-time algorithm that, given a structure as input, returns the core of that structure as output. In contrast, in the context of data exchange, we identify natural and fairly broad conditions under which there are polynomial-time algorithms for computing the core of a universal solution. We also analyze the computational complexity of the following decision problem that underlies the computation of cores: given two graphs G and H, is H the core of G? Earlier results imply that this problem is both NP-hard and coNP-hard. Here, we pinpoint its exact complexity by establishing that it is a DP-complete problem. Finally, we show that the core is the best among all universal solutions for answering existential queries, and we propose an alternative semantics for answering queries in data exchange settings.

Schema mappings, data exchange, and metadata management

Schema mappings are high-level specifications that describe the relationship between database schemas. Schema mappings are prominent in several different areas of database management, including database design, information integration, data exchange, metadata management, and peer-to-peer data management systems. Our main aim in this paper is to present an overview of recent advances in data exchange and metadata management, where the schema mappings are between relational schemas. In addition, we highlight some research issues and directions for future work.

On the decision problem for two-variable first-order logic

We identify the computational complexity of the satisfiability problem for FO2, the fragment of first-order logic consisting of all relational first-order sentences with at most two distinct variables. Although this fragment was shown to be decidable a long time ago, the computational complexity of its decision problem has not been pinpointed so far. In 1975 Mortimer proved that FO2 has thefinite-modelproperty, which means that if an FO2-sentence is satisfiable, then it has a finite model. Moreover, Mortimer showed that every satisfiable FO2-sentence has a model whose size is at most doubly exponential in the size of the sentence. In this paper, we improve Mortimers bound by one exponential and show that every satisfiable FO2-sentence has a model whose size is at most exponential in the size of the sentence. As a consequence, we establish that the satisfiability problem for FO2 is NEXPTIME-complete. ?

On the expressive power of datalog: tools and a case study

We study here the language Datalog(≠), which is the query language obtained from Datalog by allowing equalities and inequalities in the bodies of the rules. We view Datalog(≠) as a fragment of an infinitary logic <italic>L</italic><supscrpt>ω</supscrpt> and show that <italic>L</italic><supscrpt>ω</supscrpt> can be characterized in terms of certain two-person pebble games. This characterization provides us with tools for investigating the expressive power of Datalog(≠). As a case study, we classify the expressibility of <italic>fixed subgraph homeomorphism</italic> queries on directed graphs. Fortune et al. [FHW80] classified the computational complexity of these queries by establishing two dichotomies, which are proper only if P ≠ NP. Without using any complexity-theoretic assumptions, we show here that the two dichotomies are indeed proper in terms of expressibility in Datalog(≠).

Peer data exchange

In this article, we introduce and study a framework, called peer data exchange, for sharing and exchanging data between peers. This framework is a special case of a full-fledged peer data management system and a generalization of data exchange between a source schema and a target schema. The motivation behind peer data exchange is to model authority relationships between peers, where a source peer may contribute data to a target peer, specified using source-to-target constraints, and a target peer may use target-to-source constraints to restrict the data it is willing to receive, but cannot modify the data of the source peer.A fundamental algorithmic problem in this framework is that of deciding the existence of a solution: given a source instance and a target instance for a fixed peer data exchange setting, can the target instance be augmented in such a way that the source instance and the augmented target instance satisfy all constraints of the settingq We investigate the computational complexity of the problem for peer data exchange settings in which the constraints are given by tuple generating dependencies. We show that this problem is always in NP, and that it can be NP-complete even for “acyclic” peer data exchange settings. We also show that the data complexity of the certain answers of target conjunctive queries is in coNP, and that it can be coNP-complete even for “acyclic” peer data exchange settings.After this, we explore the boundary between tractability and intractability for deciding the existence of a solution and for computing the certain answers of target conjunctive queries. To this effect, we identify broad syntactic conditions on the constraints between the peers under which the existence-of-solutions problem is solvable in polynomial time. We also identify syntactic conditions between peer data exchange settings and target conjunctive queries that yield polynomial-time algorithms for computing the certain answers. For both problems, these syntactic conditions turn out to be tight, in the sense that minimal relaxations of them lead to intractability. Finally, we introduce the concept of a universal basis of solutions in peer data exchange and explore its properties.

The expressive power of stratified logic programs

The study of negation in logic programming has been the topic of substantial research activity during the past several years, starting with the negation as failure semantics in Clark (1978), and Apt and van Emden (1982). More recently, a major direction of research has focused on the class of stratified logic programs, in which no predicate is defined recursively in terms of its own negation and which can be given natural semantics in terms of iterated fixpoints. Stratified logic programs were introduced and studied first by Chandra and Hare1 (1985), but soon attracted the interest of researchers from both database theory and artificial intelligence. Recent research work on stratified logic programs and their generalizations includes the papers by Apt, Blair, and Walker (1988), Van Gelder (1986) Lifschitz (1988), Przymusinski (1988), Apt and Pugin (1987) and others. At the same time, stratified logic programs became the choice for the treatment of negation in the NAIL ! system developed at Stanford University by Ullman and his co-workers (cf. Morris

The Connectivity of Boolean Satisfiability: Computational and Structural Dichotomies

Boolean satisfiability problems are an important benchmark for questions about complexity, algorithms, heuristics, and threshold phenomena. Recent work on heuristics and the satisfiability threshold has centered around the structure and connectivity of the solution space. Motivated by this work, we study structural and connectivity-related properties of the space of solutions of Boolean satisfiability problems and establish various dichotomies in Schaefers framework. On the structural side, we obtain dichotomies for the kinds of subgraphs of the hypercube that can be induced by the solutions of Boolean formulas, as well as for the diameter of the connected components of the solution space. On the computational side, we establish dichotomy theorems for the complexity of the connectivity and

Infinitary logics and 0–1 laws

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Why not negation by fixpoint

-connectivity questions for the graph of solutions of Boolean formulas. Our results assert that the intractable side of the computational dichotomies is PSPACE-complete, while the tractable side—which includes but is not limited to all problems with polynomial-time algorithms for satisfiability—is in P for the