IMPLEMENTATION AND OPTIMIZATION OF RDF QUERY USING HADOOP

YanWen Chen, Fabrice Huet, YiXiang Chen

Abstract

With the prevalence of semantic web, a great deal of RDF data is created and has reached to tens of petabytes, which attracts people to pay more attention to processing data with high performance. In recent years, Hadoop, building on MapReduce framework, provides us a good way to process massive data in parallel. In this paper, we focus on using Hadoop to query RDF data from large data repositories. First, we proposed a prototype to process a SPARQL query. Then, we represented several ways to optimize our solution. Result shows that a better performance has been achieved, almost 70% improvement due to the optimization.

References

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Paper Citation


in Harvard Style

Chen Y., Huet F. and Chen Y. (2011). IMPLEMENTATION AND OPTIMIZATION OF RDF QUERY USING HADOOP . In Proceedings of the 1st International Conference on Cloud Computing and Services Science - Volume 1: CLOSER, ISBN 978-989-8425-52-2, pages 512-515. DOI: 10.5220/0003387805120515


in Bibtex Style

@conference{closer11,
author={YanWen Chen and Fabrice Huet and YiXiang Chen},
title={IMPLEMENTATION AND OPTIMIZATION OF RDF QUERY USING HADOOP},
booktitle={Proceedings of the 1st International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,},
year={2011},
pages={512-515},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003387805120515},
isbn={978-989-8425-52-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 1st International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,
TI - IMPLEMENTATION AND OPTIMIZATION OF RDF QUERY USING HADOOP
SN - 978-989-8425-52-2
AU - Chen Y.
AU - Huet F.
AU - Chen Y.
PY - 2011
SP - 512
EP - 515
DO - 10.5220/0003387805120515