An Empirical Study of Real-World SPARQL Queries

Understanding how users tailor their SPARQL queries is crucial when designing query evaluation engines or ne-tuning RDF stores with performance in mind. In this paper the authors analyze 3 million real-world SPARQL queries extracted from logs of the DBPedia and SWDF public endpoints. They 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.