A Fully Parallel Framework for Fast Analyzing RDF Data

Long ChengLong Cheng, Spyros KotoulasSpyros Kotoulas, Tomas E. WardTomas E. Ward, Georgios TheodoropoulosGeorgios Theodoropoulos

Long Cheng, Spyros Kotoulas, Tomas E. Ward, Georgios Theodoropoulos
A Fully Parallel Framework for Fast Analyzing RDF Data
P&D Track of the 13th International Semantic Web Conference (ISWC'14), September 2014. ACM

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KurzfassungAbstract
We introduce the design of a fully parallel framework for quickly analyzing large-scale RDF data over distributed architectures. We present three core operations of this framework: dictionary encoding, parallel joins and indexing processing. Preliminary experimental results on a commodity cluster show that we can load large RDF data very fast while remaining within an interactive range for query processing.
Weitere Informationen unter:Further Information: Link
Projekt:Project: DIAMOND
Forschungsgruppe:Research Group: Knowledge SystemsKnowledge-Based Systems

@inproceedings{CKWT2014,
  author    = {Long Cheng and Spyros Kotoulas and Tomas E. Ward and Georgios
               Theodoropoulos},
  title     = {A Fully Parallel Framework for Fast Analyzing {RDF} Data},
  booktitle = {P\&D Track of the 13th International Semantic Web Conference
               (ISWC'14)},
  publisher = {ACM},
  year      = {2014},
  month     = {September},
  doi       = {10.1145/2631775.2631789}
}