Native Execution of GraphQL Queries over RDF Graphs Using Multi-way Joins

TL;DR

This paper introduces a multi-way join algorithm that enables native execution of GraphQL queries over RDF graphs, outperforming existing solutions in speed and scalability.

Contribution

The paper presents a novel multi-way join algorithm inspired by worst-case optimal algorithms, allowing direct GraphQL querying of RDF graphs without translation layers.

Findings

Outperforms state-of-the-art solutions in query runtime

Demonstrates superior scalability in experiments

Implemented in an open-source triple store

Abstract

Purpose: The query language GraphQL has gained significant traction in recent years. In particular, it has recently gained the attention of the semantic web and graph database communities and is now often used as a means to query knowledge graphs. Most of the storage solutions that support GraphQL rely on a translation layer to map the said language to another query language that they support natively, for example SPARQL. Methodology: Our main innovation is a multi-way left-join algorithm inspired by worst-case optimal multi-way join algorithms. This novel algorithm enables the native execution of GraphQL queries over RDF knowledge graphs. We evaluate our approach in two settings using the LinGBM benchmark generator. Findings: The experimental results suggest that our solution outperforms the state-of-the-art graph storage solution for GraphQL with respect to both query runtimes and scalability. Value: Our solution is implemented in an open-sourced triple store, and is intended to advance the development of representation-agnostic storage solutions for knowledge graphs.