The increasing interest in Semantic Web technologies has led not only to a rapid growth of semantic data on the Web but also to an increasing number of backend applications relying on efficient query processing. Confronted with such a trend, existing centralized state-of-the-art systems for storing RDF and processing SPARQL queries are no longer sufficient. In this paper, we introduce Partout, a distributed engine for fast RDF processing in a cluster of machines. We propose an effective approach for fragmenting RDF data sets based on a query log and allocating the fragments to hosts in a cluster of machines. Furthermore, Partout’s query optimizer produces efficient query execution plans for ad-hoc SPARQL queries.<br/
International audienceLike most data models encountered in the Big Data ecosystem, RDF stores are ma...
We propose techniques for processing SPARQL queries over a large RDF graph in a distributed environm...
Many RDF systems support reasoning with Datalog rules via materialisation, where all conclusions of ...
The increasing interest in Semantic Web technologies has led not only to a rapid growth of semantic ...
The increasing interest in Semantic Web technologies has led not only to a rapid growth of semantic ...
The generation of RDF data has accelerated to the point where many data sets need to be partitioned ...
Abstract—The emerging need for conducting complex analysis over big RDF datasets calls for scale-out...
We present D-SPARQ, a distributed RDF query engine that combines the MapReduce processing framework ...
Querying the ever-growing Web of Data poses a significant challenge in today’s Semantic Web. The com...
The Semantic Web, or the Web of Data, promotes common data formats for representing structured data ...
The Resource Description Framework (RDF) and SPARQL query language are gaining wide popularity and a...
The growing popularity of Resource Description Framework (RDF) as a mode for data exchange and integ...
The flexibility of the RDF data model has attracted an in-creasing number of organizations to store ...
Abstract. As more and more data is provided in RDF format, storing huge amounts of RDF data and effi...
Massive volumes of big RDF data are growing beyond the performance capacity of conventional RDF data...
International audienceLike most data models encountered in the Big Data ecosystem, RDF stores are ma...
We propose techniques for processing SPARQL queries over a large RDF graph in a distributed environm...
Many RDF systems support reasoning with Datalog rules via materialisation, where all conclusions of ...
The increasing interest in Semantic Web technologies has led not only to a rapid growth of semantic ...
The increasing interest in Semantic Web technologies has led not only to a rapid growth of semantic ...
The generation of RDF data has accelerated to the point where many data sets need to be partitioned ...
Abstract—The emerging need for conducting complex analysis over big RDF datasets calls for scale-out...
We present D-SPARQ, a distributed RDF query engine that combines the MapReduce processing framework ...
Querying the ever-growing Web of Data poses a significant challenge in today’s Semantic Web. The com...
The Semantic Web, or the Web of Data, promotes common data formats for representing structured data ...
The Resource Description Framework (RDF) and SPARQL query language are gaining wide popularity and a...
The growing popularity of Resource Description Framework (RDF) as a mode for data exchange and integ...
The flexibility of the RDF data model has attracted an in-creasing number of organizations to store ...
Abstract. As more and more data is provided in RDF format, storing huge amounts of RDF data and effi...
Massive volumes of big RDF data are growing beyond the performance capacity of conventional RDF data...
International audienceLike most data models encountered in the Big Data ecosystem, RDF stores are ma...
We propose techniques for processing SPARQL queries over a large RDF graph in a distributed environm...
Many RDF systems support reasoning with Datalog rules via materialisation, where all conclusions of ...