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Andreas Pieris

Publications and source records attributed to Andreas Pieris.

21 records · Page 2Linked to original sources

Semantic Acyclicity Under Constraints

A conjunctive query (CQ) is semantically acyclic if it is equivalent to an acyclic one. Semantic acyclicity has been studied in the constraint-free case, and deciding whether a query enjoys this property is NP-complete. However, in case the database is subject to constraints such as tuple-generating dependencies (tgds) that can express, e.g., inclusion dependencies, or equality-generating dependencies (egds) that capture, e.g., functional dependencies, a CQ may turn out to be semantically acyclic under the constraints while not semantically acyclic in general. This opens avenues to new query optimization techniques. In this paper we initiate and develop the theory of semantic acyclicity under constraints. More precisely, we study the following natural problem: Given a CQ and a set of constraints, is the query semantically acyclic under the constraints, or, in other words, is the query equivalent to an acyclic one over all those databases that satisfy the set of constraints? We show that, contrary to what one might expect, decidability of CQ containment is a necessary but not sufficient condition for the decidability of semantic acyclicity. In particular, we show that semantic acyclicity is undecidable in the presence of full tgds (i.e., Datalog rules). In view of this fact, we focus on the main classes of tgds for which CQ containment is decidable, and do not capture the class of full tgds, namely guarded, non-recursive and sticky tgds. For these classes we show that semantic acyclicity is decidable, and its complexity coincides with the complexity of CQ containment. In the case of egds, we show that for keys over unary and binary predicates semantic acyclicity is decidable (NP-complete). We finally consider the problem of evaluating a semantically acyclic query over a database that satisfies a set of constraints; for guarded tgds and functional dependencies this problem is tractable.

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Query Rewriting and Optimization for Ontological Databases

Ontological queries are evaluated against a knowledge base consisting of an extensional database and an ontology (i.e., a set of logical assertions and constraints which derive new intensional knowledge from the extensional database), rather than directly on the extensional database. The evaluation and optimization of such queries is an intriguing new problem for database research. In this paper, we discuss two important aspects of this problem: query rewriting and query optimization. Query rewriting consists of the compilation of an ontological query into an equivalent first-order query against the underlying extensional database. We present a novel query rewriting algorithm for rather general types of ontological constraints which is well-suited for practical implementations. In particular, we show how a conjunctive query against a knowledge base, expressed using linear and sticky existential rules, that is, members of the recently introduced Datalog+/- family of ontology languages, can be compiled into a union of conjunctive queries (UCQ) against the underlying database. Ontological query optimization, in this context, attempts to improve this rewriting process so to produce possibly small and cost-effective UCQ rewritings for an input query.

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Ontological Queries: Rewriting and Optimization (Extended Version)

Ontological queries are evaluated against an ontology rather than directly on a database. The evaluation and optimization of such queries is an intriguing new problem for database research. In this paper we discuss two important aspects of this problem: query rewriting and query optimization. Query rewriting consists of the compilation of an ontological query into an equivalent query against the underlying relational database. The focus here is on soundness and completeness. We review previous results and present a new rewriting algorithm for rather general types of ontological constraints. In particular, we show how a conjunctive query against an ontology can be compiled into a union of conjunctive queries against the underlying database. Ontological query optimization, in this context, attempts to improve this process so to produce possibly small and cost-effective UCQ rewritings for an input query. We review existing optimization methods, and propose an effective new method that works for linear Datalog+/-, a class of Datalog-based rules that encompasses well-known description logics of the DL-Lite family.

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