GeoReach: An Efficient Approach for Evaluating Graph Reachability Queries with Spatial Range Predicates

TL;DR

GeoReach introduces a novel spatially-aware graph reachability method that significantly improves query response times and reduces storage, enabling efficient spatial reachability queries in large graph databases.

Contribution

The paper presents GeoReach, a new approach integrating spatial data awareness into graph databases with a lightweight SPA-Graph structure for efficient RangeReach queries.

Findings

Up to 100x faster query response times compared to existing methods.

Four times less storage requirement than state-of-the-art approaches.

Effective in real system implementation within Neo4j.

Abstract

Graphs are widely used to model data in many application domains. Thanks to the wide spread use of GPS-enabled devices, many applications assign a spatial attribute to graph vertices (e.g., geo-tagged social media). Users may issue a Reachability Query with Spatial Range Predicate (abbr. RangeReach). RangeReach finds whether an input vertex can reach any spatial vertex that lies within an input spatial range. An example of a RangeReach query is: Given a social graph, find whether Alice can reach any of the venues located within the geographical area of Arizona State University. The paper proposes GeoReach an approach that adds spatial data awareness to a graph database management system (GDBMS). GeoReach allows efficient execution of RangeReach queries, yet without compromising a lot on the overall system scalability (measured in terms of storage size and initialization/maintenance time). To achieve that, GeoReach is equipped with a light-weight data structure, namely SPA-Graph, that augments the underlying graph data with spatial indexing directories. When a RangeReach query is issued, the system employs a pruned-graph traversal approach. Experiments based on real system implementation inside Neo4j proves that GEOREACH exhibits up to two orders of magnitude better query response time and up to four times less storage than the state-of-the-art spatial and reachability indexing approaches.