OBDA Constraints for Effective Query Answering (Extended Version)
This addresses performance bottlenecks in OBDA systems for users handling large enterprise databases, representing a novel method for a known bottleneck.
The paper tackled the problem of redundant joins and unions in SPARQL-to-SQL translation in Ontology Based Data Access (OBDA), which harms performance in complex industrial scenarios, and introduced OBDA constraints to improve query answering performance by up to orders of magnitude in experiments on large real-world datasets.
In Ontology Based Data Access (OBDA) users pose SPARQL queries over an ontology that lies on top of relational datasources. These queries are translated on-the-fly into SQL queries by OBDA systems. Standard SPARQL-to-SQL translation techniques in OBDA often produce SQL queries containing redundant joins and unions, even after a number of semantic and structural optimizations. These redundancies are detrimental to the performance of query answering, especially in complex industrial OBDA scenarios with large enterprise databases. To address this issue, we introduce two novel notions of OBDA constraints and show how to exploit them for efficient query answering. We conduct an extensive set of experiments on large datasets using real world data and queries, showing that these techniques strongly improve the performance of query answering up to orders of magnitude.