Expressive Path Queries on Graph with Data

TL;DR

This paper investigates the expressive power and computational complexity of advanced graph query languages, proposing register logic as a practical extension that balances expressiveness and efficiency.

Contribution

It introduces register logic, an extension of REM, capable of expressing many properties of WL while maintaining low data complexity, addressing limitations of existing languages.

Findings

WL has nonelementary data complexity, making it impractical.

REM has low data complexity but limited expressive power.

Register logic combines expressiveness of WL with REM's efficiency.

Abstract

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.