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Tina Popp

Publications and source records attributed to Tina Popp.

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A Trichotomy for Regular Trail Queries

Regular path queries (RPQs) are an essential component of graph query languages. Such queries consider a regular expression r and a directed edge-labeled graph G and search for paths in G for which the sequence of labels is in the language of r. In order to avoid having to consider infinitely many paths, some database engines restrict such paths to be trails, that is, they only consider paths without repeated edges. In this paper we consider the evaluation problem for RPQs under trail semantics, in the case where the expression is fixed. We show that, in this setting, there exists a trichotomy. More precisely, the complexity of RPQ evaluation divides the regular languages into the finite languages, the class Ttract (for which the problem is tractable), and the rest. Interestingly, the tractable class in the trichotomy is larger than for the trichotomy for simple paths, discovered by Bagan, Bonifati, and Groz [JCSS 2020]. In addition to this trichotomy result, we also study characterizations of the tractable class, its expressivity, the recognition problem, closure properties, and show how the decision problem can be extended to the enumeration problem, which is relevant to practice.

cs.FL

Representing Paths in Graph Database Pattern Matching

Modern graph database query languages such as GQL, SQL/PGQ, and their academic predecessor G-Core promote paths to first-class citizens in the sense that paths that match regular path queries can be returned to the user. This brings a number of challenges in terms of efficiency, caused by the fact that graphs can have a huge amount of paths between a given node pair. We introduce the concept of path multiset representations (PMRs), which can represent multisets of paths in an exponentially succinct manner. After exploring fundamental problems such as minimization and equivalence testing of PMRs, we explore how their use can lead to significant time and space savings when executing query plans. We show that, from a computational complexity point of view, PMRs seem especially well-suited for representing results of regular path queries and extensions thereof involving counting, random sampling, unions, and joins.

cs.DB