PathEnum: Towards Real-Time Hop-Constrained s-t Path Enumeration

TL;DR

PathEnum introduces a novel index-based algorithm that significantly improves real-time enumeration of hop-constrained s-t paths, outperforming existing methods in speed and efficiency on real-world graphs.

Contribution

The paper presents PathEnum, a new index-based approach with optimized search strategies for efficient hop-constrained path enumeration in large graphs.

Findings

PathEnum achieves orders of magnitude faster query times.

It outperforms state-of-the-art algorithms in throughput and response time.

The approach is effective on real-world graph datasets.

Abstract

We study the hop-constrained s-t path enumeration (HcPE) problem, which takes a graph $G$, two distinct vertices $s,t$ and a hop constraint $k$ as input, and outputs all paths from $s$ to $t$ whose length is at most $k$. The state-of-the-art algorithms suffer from severe performance issues caused by the costly pruning operations during enumeration for the workloads with the large search space. Consequently, these algorithms hardly meet the real-time constraints of many online applications. In this paper, we propose PathEnum, an efficient index-based algorithm towards real-time HcPE. For an input query, PathEnum first builds a light-weight index aiming to reduce the number of edges involved in the enumeration, and develops efficient index-based approaches for enumeration, one based on depth-first search and the other based on joins. We further develop a query optimizer based on a join-based cost model to optimize the search order. We conduct experiments with 15 real-world graphs. Our experiment results show that PathEnum outperforms the state-of-the-art approaches by orders of magnitude in terms of the query time, throughput and response time.