A Provenance-Based Caching System to Speed-up SPARQL Query Answering

We propose a new provenance-based approach for the dynamic extraction of subgraphs from an RDF database that can be used as a cache for a faster response to SPARQL queries. The proposed system can deal with dynamic workloads, allowing us to use the cache to answer queries similar but not identical to others seen before by the system. Moreover, our approach exploits existing technologies and can be seamlessly integrated on top of existing RDF DBMS without requiring any change to their internals. We conducted an in-depth evaluation on a widely used synthetic database (BSBM) and on Wikidata using real-world query logs. We show that the proposed approach improves the query execution times over the whole database.