Diplo Cloud:Efficient and Scalable Management of RDF Data in the Cloud
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In spite of the latest improvements in distributed RDF data management, processing a large number of RDF data on the cloud remains difficult. Despite its apparent simplicity, RDFstores rich and complicated graphs that include both schema-level information and instance. Typical strategies for splitting such data with the graph by the use of old min-cut algorithms result in incomplete distributed performance and a significant quantity of joins. In this work, we describe Diplo Cloud, a cloud-based distributed RDF data management system that is both efficient and scalable. Diplo Cloud performs a p...
In spite of the latest improvements in distributed RDF data management, processing a large number of RDF data on the cloud remains difficult. Despite its apparent simplicity, RDFstores rich and complicated graphs that include both schema-level information and instance. Typical strategies for splitting such data with the graph by the use of old min-cut algorithms result in incomplete distributed performance and a significant quantity of joins. In this work, we describe Diplo Cloud, a cloud-based distributed RDF data management system that is both efficient and scalable. Diplo Cloud performs a physiological examination of both instance and schema data before splitting the data in contrast to earlier techniques.
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