An Empirical Study of Real-World SPARQL Queries

TL;DR

This study analyzes 3 million real-world SPARQL queries to identify common patterns, focusing on structural elements and join types, to inform query engine optimization and RDF store tuning.

Contribution

It provides the first large-scale empirical analysis of real-world SPARQL queries, highlighting prevalent query structures and join patterns.

Findings

Most queries are simple with few triple patterns and joins.

Star-shaped graph patterns are most common.

Short triple pattern chains are typical.

Abstract

Understanding how users tailor their SPARQL queries is crucial when designing query evaluation engines or fine-tuning RDF stores with performance in mind. In this paper we analyze 3 million real-world SPARQL queries extracted from logs of the DBPedia and SWDF public endpoints. We aim at finding which are the most used language elements both from syntactical and structural perspectives, paying special attention to triple patterns and joins, since they are indeed some of the most expensive SPARQL operations at evaluation phase. We have determined that most of the queries are simple and include few triple patterns and joins, being Subject-Subject, Subject-Object and Object-Object the most common join types. The graph patterns are usually star-shaped and despite triple pattern chains exist, they are generally short.