The complexity of acyclic conjunctive queries revisited

TL;DR

This paper revisits the complexity of acyclic conjunctive queries over unary functions, establishing they are fixed-parameter linear, which improves existing bounds and provides new insights into related algorithmic problems.

Contribution

It introduces a natural notion of acyclicity for this language and proves fixed-parameter linear evaluation complexity for various query variants, extending to classical relational settings.

Findings

All studied query variants are fixed-parameter linear in evaluation time.

Improves known bounds for acyclic conjunctive queries with inequalities.

Provides a descriptive approach to the complexity of problems like acyclic subgraph and multidimensional matching.

Abstract

In this paper, we consider first-order logic over unary functions and study the complexity of the evaluation problem for conjunctive queries described by such kind of formulas. A natural notion of query acyclicity for this language is introduced and we study the complexity of a large number of variants or generalizations of acyclic query problems in that context (Boolean or not Boolean, with or without inequalities, comparisons, etc...). Our main results show that all those problems are \textit{fixed-parameter linear} i.e. they can be evaluated in time $f(|Q|).|\textbf{db}|.|Q(\textbf{db})|$ where $|Q|$ is the size of the query $Q$, $|\textbf{db}|$ the database size, $|Q(\textbf{db})|$ is the size of the output and $f$ is some function whose value depends on the specific variant of the query problem (in some cases, $f$ is the identity function). Our results have two kinds of consequences. First, they can be easily translated in the relational (i.e., classical) setting. Previously known bounds for some query problems are improved and new tractable cases are then exhibited. Among others, as an immediate corollary, we improve a result of \~\cite{PapadimitriouY-99} by showing that any (relational) acyclic conjunctive query with inequalities can be evaluated in time $f(|Q|).|\textbf{db}|.|Q(\textbf{db})|$. A second consequence of our method is that it provides a very natural descriptive approach to the complexity of well-known algorithmic problems. A number of examples (such as acyclic subgraph problems, multidimensional matching, etc...) are considered for which new insights of their complexity are given.