Join operators are particularly important in SPARQL query engines that collect RDF data using Web access interfaces. State-of-the-art SPARQL query engines rely on binary join operators tailored for merging results from SPARQL queries over Web access interfaces.
However, in queries with a large number of triple patterns, binary joins constitute a significant burden on the query performance. Multi-way joins that handle more than two inputs are able to reduce the complexity of pre-processing stages and reduce the execution time.
Whereas in the relational field multi-way joins have already received some attention, the applicability of multi-way joins in SPARQL query processing remains unexplored. We devise SMJoin, a multi-way non-blocking join operator tailored for independently merging results from more than two RDF data sources. SMJoin implements intra-operator adaptivity, i.e., it is able to adjust join execution schedulers to the conditions of Web access interfaces; thus, query answers are produced as soon as they are computed and can be continuously generated even if one of the sources becomes blocked.
We empirically study the behavior of SMJoin in two benchmarks with queries of different selectivity; state-of-the-art SPARQL query engines are included in the study. Experimental results suggest that SMJoin outperforms existing approaches in very selective queries, and produces first answers as fast as state-of-the-art adaptive query engines in non-selective queries.
PhD
Fraunhofer Institute
http://www.fraunhofer.de
Dr. Diego Collarana (male) is a Lead Research Scientist and Senior Software Engineer at Fraunhofer IAIS. He is specialized in the conceptualization and development of enterprise information systems using state-of-the-art technologies such as Deep Learning and Knowledge Graphs.
Prof. Dr.
Universidad Simón Bolívar
http://www.usb.ve/
Prof. Dr. (Univ. Simon Bolivar) Maria-Esther Vidal is the head of the Scientific Data Management Research Group at TIB and a member of the L3S Research Centre at the University of Hannover; she is also a full professor (on-leave) at Universidad Simón Bolívar (USB) Venezuela. Her interests include Big data and knowledge management, knowledge representation, and semantic web.
Professor and director
Leibniz Information Center for Science & Technology
https://www.tib.eu/en/
Following stations at the universities of Dresden, Ekaterinburg, Leipzig, Pennsylvania, Bonn and the Fraunhofer Society, Prof. Auer was appointed Professor of Data Science and Digital Libraries at Leibniz Universität Hannover and Director of the TIB in 2017. Prof. Auer has made important contributions to semantic technologies, knowledge engineering and information systems.
