Reachability, distance, and shortest path queries are fundamental operations in the field of graph data management with various applications in research and industry. However, while various preprocessing-based methods have been proposed to optimize the computation of such queries, the integration of existing methods into graph database management systems and processing frameworks has been limited. In this paper, we present an implementation of a static graph index that employs landmark embedding for Neo4j, to enable the index-based computation of reachability, distance, and shortest path queries on the database. We explore different strategies for selecting landmarks and different schemes for storing the precomputed landmark distances. To evaluate the efficiency of each landmark selection strategy and each storage scheme, we conduct an experimental evaluation using four real-world network datasets. We measure the preprocessing cost, the query processing time, and the accuracy of the distance estimation of different configurations of our index structure.

Processing shortest path queries is a basic operation in many graph problems. Both preprocessing-based and batch processing techniques have been proposed to speed up the computation of a single shortest path by amortizing its costs. However, both of these approaches suffer from limitations. The former techniques are prohibitively expensive in situations where the precomputed information needs to be updated frequently due to changes in the graph, while the latter require coordinates and cannot be used on non-spatial graphs. In this paper, we address both limitations and propose novel techniques for batch processing shortest paths queries using landmarks. We show how preprocessing can be avoided entirely by integrating the computation of landmark distances into query processing. Our experimental results demonstrate that our techniques outperform the state of the art on both spatial and non-spatial graphs with a maximum speedup of 3.61× in online scenarios. CCS CONCEPTS• Information systems → Database query processing; • Theory of computation → Shortest paths.