%0 Conference Paper %1 Stadler2019-cs %A Stadler, Claus %A Sejdiu, Gezim %A Graux, Damian %A Lehmann, Jens %D 2019 %I Zenodo %K %T Querying large-scale RDF datasets using the SANSA framework %X In this paper we present Sparklify: a scalable software component for efficient evaluation of SPARQL queries over distributed RDF datasets. In particular, we demonstrate a W3C SPARQL endpoint powered by our SANSA framework's RDF partitioning system and Apache Spark for querying the DBpedia knowledge base. This work is motivated by the lack of Big Data SPARQL systems that are capable of exposing large-scale heterogeneous RDF datasets via a Web SPARQL endpoint.

@inproceedings{Stadler2019-cs, abstract = {In this paper we present Sparklify: a scalable software component for efficient evaluation of SPARQL queries over distributed RDF datasets. In particular, we demonstrate a W3C SPARQL endpoint powered by our SANSA framework's RDF partitioning system and Apache Spark for querying the DBpedia knowledge base. This work is motivated by the lack of Big Data SPARQL systems that are capable of exposing large-scale heterogeneous RDF datasets via a Web SPARQL endpoint.}, added-at = {2024-09-10T11:56:37.000+0200}, author = {Stadler, Claus and Sejdiu, Gezim and Graux, Damian and Lehmann, Jens}, biburl = {https://puma.scadsai.uni-leipzig.de/bibtex/24ace2294a8f5e5189dd6785a6587d089/scadsfct}, interhash = {939c65027ee19eb0749c418797649e7a}, intrahash = {4ace2294a8f5e5189dd6785a6587d089}, keywords = {}, publisher = {Zenodo}, timestamp = {2024-09-10T15:15:57.000+0200}, title = {Querying large-scale {RDF} datasets using the {SANSA} framework}, year = 2019 }