A Fully Parallel Framework for Fast Analyzing RDF Data
Aus International Center for Computational Logic
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), October 2014. CEUR Workshop Proceedings
A Fully Parallel Framework for Fast Analyzing RDF Data
P&D Track of the 13th International Semantic Web Conference (ISWC'14), October 2014. CEUR Workshop Proceedings
- 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: Wissensbasierte SystemeKnowledge-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 = {CEUR Workshop Proceedings},
year = {2014},
month = {October}
}