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Resource Description Framework (RDF) is a data representation of the Semantic Web, and its data volume is growing rapidly. Cloud-based systems provide a rich platform for managing RDF data. However, there is a performance challenge in the distributed environment when RDF queries, which contain multiple join operations, such as network reshuffle and memory overhead, are processed. To get over this challenge, this paper proposes a Spark-based RDF query architecture, which is based on Semanticdoi:10.1186/s13638-019-1588-9 fatcat:gchrslcjundhjftqkjpfgujzmi