Selectivity Estimation for SPARQL Triple Patterns with Shape Expressions

Abstract

ShEx (Shape Expressions) is a language for expressing constraints on RDF graphs. In this work we optimize the evaluation of conjunctive SPARQL queries, on RDF graphs, by taking advantage of ShEx constraints. Our optimization is based on computing and assigning ranks to query triple patterns, dictating their order of execution. We first define a set of well formed ShEx schemas, that possess interesting characteristics for SPARQL query optimization. We then define our optimization method by exploiting information extracted from a ShEx schema. We finally report on evaluation results performed showing the advantages of applying our optimization on the top of an existing state-of-the-art query evaluation system.

Shape Fragments

“…Yet we believe many more insights from database query optimization can be beneficial and specialized to shape processing. (A related direction is to use shapes to inform SPARQL query optimization [2,50]. )…”

“…By specifying the intended structural constraints on the data, they help maintaining data quality [24]. The shape schema can also be used by the query optimizer in processing SPARQL queries [2,50]. Knowledge of a schema helps data consumers to effectively formulate their SPARQL queries in the first place.…”

“…However, the task of checking whether an input RDF graph conforms to a shape schema can, at least in principle, also be done by evaluating a, typically complex, SPARQL query. 2 That SHACL was still invented and proposed within the Web community strongly indicates that this language allows for easier expression of typical constraints on the structure of the data. This suggests that there may be an opportunity to leverage SHACL beyond conformance checking, and use it also to retrieve data.…”