Conjunctive Regular Path Queries Research Articles

Conjunctive Regular Path Queries with Capture Groups

In practice, regular expressions are usually extended by so-called capture groups or capture variables, which allow to capture a subexpression by a variable that can be referenced in the regular expression in order to describe repetitions of subwords. We investigate how this concept could be used for pattern-based graph querying; i.e., we investigate conjunctive regular path queries (CRPQs) that are extended by capture variables. If capture variables are added to CRPQs in a completely unrestricted way, then Boolean evaluation becomes PSPACE-hard in data complexity, even for single-edge graph patterns. On the other hand, if capture variables do not occur under a Kleene star, then the data complexity drops to NL-completeness. Combined complexity is in EXPSPACE but drops to PSPACE-completeness if the depth (i.e., the nesting depth of capture variables) is bounded, and it drops to NP-completeness if the size of the images of capture variables is bounded by a constant (regardless of the depth or of whether capture variables occur under a Kleene star). In the application of regular expressions as string searching tools, references to capture variables only describe exact repetitions of subwords (i.e., they implement the equality relation on strings). Following recent developments in graph database research, we also study CRPQs with capture variables that describe arbitrary regular relations. We show that if the expressions have depth 0, or if the size of the images of capture variables is bounded by a constant, then we can allow arbitrary regular relations while staying in the same complexity bounds. We also investigate the problems of checking whether a given tuple is in the solution set and computing the whole solution set. On the conceptual side, we add capture variables to CRPQs in such a way that they can be defined in an expression on one arc of the graph pattern but also referenced in expressions on other arcs. Hence, they add to CRPQs the possibility to define inter-dependencies between different paths, which is a relevant feature of pattern-based graph querying.

On the data complexity of consistent query answering over graph databases

Applications of graph databases are prone to inconsistency due to interoperability issues. This raises the need for studying query answering over inconsistent graph databases in a simple but general framework. We follow the approach of consistent query answering (CQA), and study its data complexity over graph databases for conjunctive regular-path queries (CRPQs) and conjunctive regular-path constraints (CRPCs). We deal with subset, superset and symmetric-difference repairs. Without restrictions, CQA is undecidable for the semantics of superset- and symmetric-difference repairs, and Π2P-complete for subset-repairs. However, we identify restrictions on CRPCs and databases that lead to decidability, and even tractability of CQA.

Semantic Acyclicity on Graph Databases

It is known that unions of acyclic conjunctive queries (CQs) can be evaluated in linear time, as opposed to arbitrary CQs, for which the evaluation problem is NP-complete. It follows from techniques in the area of constraint-satisfaction problems that semantically acyclic unions of CQs---i.e., unions of CQs that are equivalent to a union of acyclic ones---can be evaluated in polynomial time, though testing membership in the class of semantically acyclic CQs is NP-complete. We study here the fundamental notion of semantic acyclicity in the context of graph databases and unions of conjunctive regular path queries with inverse (UC2RPQs). It is known that unions of acyclic C2RPQs can be evaluated efficiently, but it is by no means obvious whether similarly good evaluation properties hold for the class of UC2RPQs that are semantically acyclic. We prove that checking whether a UC2RPQ is semantically acyclic is Expspace-complete and obtain as a corollary that evaluation of semantically acyclic UC2RPQs is fixed-p...

Expressive Path Queries on Graph with Data

Graph data models have recently become popular owing to their applications, e.g., in social networks and the semantic web. Typical navigational query languages over graph databases - such as Conjunctive Regular Path Queries (CRPQs) - cannot express relevant properties of the interaction between the underlying data and the topology. Two languages have been recently proposed to overcome this problem: walk logic (WL) and regular expressions with memory (REM). In this paper, we begin by investigating fundamental properties of WL and REM, i.e., complexity of evaluation problems and expressive power. We first show that the data complexity of WL is nonelementary, which rules out its practicality. On the other hand, while REM has low data complexity, we point out that many natural data/topology properties of graphs expressible in WL cannot be expressed in REM. To this end, we propose register logic, an extension of REM, which we show to be able to express many natural graph properties expressible in WL, while at the same time preserving the elementariness of data complexity of REMs. It is also incomparable to WL in terms of expressive power.

Regular Path Queries in Lightweight Description Logics: Complexity and Algorithms

Conjunctive regular path queries are an expressive extension of the well-known class of conjunctive queries. Such queries have been extensively studied in the (graph) database community, since they support a controlled form of recursion and enable sophisticated path navigation. Somewhat surprisingly, there has been little work aimed at using such queries in the context of description logic (DL) knowledge bases, particularly for the lightweight DLs that are considered best suited for data-intensive applications. This paper aims to bridge this gap by providing algorithms and tight complexity bounds for answering two-way conjunctive regular path queries over DL knowledge bases formulated in lightweight DLs of the DL-Lite and EL families. Our results demonstrate that in data complexity, the cost of moving to this richer query language is as low as one could wish for: the problem is NL-complete for DL-Lite and P-complete for EL. The combined complexity of query answering increases from NP- to PSpace-complete, but for two-way regular path queries (without conjunction), we show that query answering is tractable even with respect to combined complexity. Our results reveal two-way conjunctive regular path queries as a promising language for querying data enriched by ontologies formulated in DLs of the DL-Lite and EL families or the corresponding OWL 2 QL and EL profiles.

Expressiveness and static analysis of extended conjunctive regular path queries

We study the expressiveness and the complexity of static analysis of extended conjunctive regular path queries (ECRPQs), introduced by Barceló et al. (2010) [3]. ECRPQs are an extension of conjunctive regular path queries (CRPQs), a well-studied language for querying graph structured databases. Our first main result shows that query containment and equivalence of a CRPQ in an ECRPQ are undecidable. This settles one of the main open problems posed by Barceló et al. As a second main result, we prove a non-recursive succinctness gap between CRPQs and the CRPQ-expressible fragment of ECRPQs. Apart from this, we develop a tool for proving inexpressibility results for CRPQs and ECRPQs. In particular, this enables us to show that there exist queries definable by regular expressions with backreferencing, but not expressible by ECRPQs.

Expressive Languages for Path Queries over Graph-Structured Data

For many problems arising in the setting of graph querying (such as finding semantic associations in RDF graphs, exact and approximate pattern matching, sequence alignment, etc.), the power of standard languages such as the widely studied conjunctive regular path queries (CRPQs) is insufficient in at least two ways. First, they cannot output paths and second, more crucially, they cannot express relationships among paths. We thus propose a class of extended CRPQs, called ECRPQs, which add regular relations on tuples of paths, and allow path variables in the heads of queries. We provide several examples of their usefulness in querying graph structured data, and study their properties. We analyze query evaluation and representation of tuples of paths in the output by means of automata. We present a detailed analysis of data and combined complexity of queries, and consider restrictions that lower the complexity of ECRPQs to that of relational conjunctive queries. We study the containment problem, and look at further extensions with first-order features, and with nonregular relations that add arithmetic constraints on the lengths of paths and numbers of occurrences of labels.

Optimal schema hierarchies in searching semistructured databases by conjunctive regular path queries

An approach to estimating effectiveness of index usage when searching semistructured databases consisting of OEM documents is presented. In addition to the estimation of the hierarchy optimality from the standpoint of calculation of conjunctive regular path queries, this approach allows one to take into account arbitrary distributions of query probabilities. Algorithms for index construction are given, and estimates of their complexity are obtained. These estimates clearly demonstrate efficiency of the approach and practical applicability of the algorithms suggested.