MV4PG: Materialized Views for Property Graphs

TL;DR

This paper introduces a novel approach to improve query performance in property graph databases by using materialized views, including an efficient maintenance method applicable across multiple systems, resulting in significant speedups.

Contribution

It proposes the first efficient templated view maintenance method for variable-length edges in property graphs and demonstrates its effectiveness on TuGraph and Neo4j.

Findings

Query optimization significantly outperforms maintenance costs.

Workload speedup reaches up to 28.71x.

Single query speedup nearly 100x.

Abstract

Graph databases are getting more and more attention in the highly interconnected data domain, and the demand for efficient querying of big data is increasing. We noticed that there are duplicate patterns in graph database queries, and the results of these patterns can be stored as materialized views first, which can speed up the query rate. So we propose materialized views on property graphs, including three parts: view creation, view maintenance, and query optimization using views, and we propose for the first time an efficient templated view maintenance method for containing variable-length edges, which can be applied to multiple graph databases. In order to verify the effect of materialized views, we prototype on TuGraph and experiment on both TuGraph and Neo4j. The experiment results show that our query optimization on read statements is much higher than the additional view maintenance cost brought by write statements. The speedup ratio of the whole workload reaches up to 28.71x, and the speedup ratio of a single query reaches up to nearly 100x.