Scalable Distributed Reasoning Using MapReduce

  • Jacopo Urbani
  • Spyros Kotoulas
  • Eyal Oren
  • Frank van Harmelen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5823)


We address the problem of scalable distributed reasoning, proposing a technique for materialising the closure of an RDF graph based on MapReduce. We have implemented our approach on top of Hadoop and deployed it on a compute cluster of up to 64 commodity machines. We show that a naive implementation on top of MapReduce is straightforward but performs badly and we present several non-trivial optimisations. Our algorithm is scalable and allows us to compute the RDFS closure of 865M triples from the Web (producing 30B triples) in less than two hours, faster than any other published approach.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Jacopo Urbani
    • 1
  • Spyros Kotoulas
    • 1
  • Eyal Oren
    • 1
  • Frank van Harmelen
    • 1
  1. 1.Department of Computer ScienceVrije Universiteit AmsterdamThe Netherlands

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