Year: 2024
Type: preprint
Abstract: Two-way regular path queries (2-RPQs) allow one to use regular languages over edges and inverted edges in edge-labelled graph to constrain paths of interest. 2-RPQs are (partially) adopted in different real-world graph analysis systems and have become a part of the GQL ISO standard. However the performance of 2-RPQs on real-world graphs remains a bottleneck for wider adoption. Utilisation of high-performance sparse linear algebra libraries for the algorithm implementation allows one to achieve significant speedup over competitors on real-world data and queries. We propose a new breadth-first-search-based algorithm that leverages linear algebra for evaluating single-source regular path queries. We integrate it into the LAGraph graph processing algorithm infrastructure and provide in-depth performance comparison on the large real-world knowledge bases. Additionally, we present extensive analysis of its performance across different query types using synthetic data, comparing it with various databases and other linear algebra-based approaches.
Source: arXiv (Cornell University)
Authors: Belyanin, Georgiy, Grigoriev, Semyon, Suvorov, Rodion
Institution: St Petersburg University
Language: English
Topic: Graph Theory and Algorithms
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Award: G4102169419
OpenAlex ID: W4405434166