ERA-RJN: A SPARQL-Rank Based Top-k Join Query Optimization

  • Zhengrong XiaoEmail author
  • Fengjiao Chen
  • Fangfang Xu
  • Jinguang Gu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9544)


With the wide use of RDF data, searching and ranking semantic data with SPARQL has become a research hot-spot. While there is no much research work on top-k join queries optimization in RDF native stores. This paper proposes a new rank-join operator algorithm ERA-RJN on the basis of SPARQL-RANK algebra, making use of the advantage of random access availability in RDF native storage. This paper implements the ERA-RJN operator on the ARQ-RANK platform, and performs experiments, verifies the high efficiency of ERA-RJN algorithm dealing with SPARQL top-k join query in RDF native storage .


RDF native storage Top-k join Rank-join operator SPARQL-RANK 



This topic research is done under the guidance of Professor JinGuang Gu. Avail ourselves of this opportunity to express heartfelt thanks to Professor Gu. And student Fangfang Xu, YuWei Zou helped with some technical stuff. This work is supported by the Natural Science Foundation Project of Hubei Province (2013CFB334), the Scientific Research Project of Hubei Provincial Education Department (Q20101110, D2009110) and the Outstanding Young Scientific and Technological Innovation Team Project of Hubei Provincial Colleges and Universities (T201202), much thanks with it.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Zhengrong Xiao
    • 1
    • 2
    Email author
  • Fengjiao Chen
    • 1
    • 2
  • Fangfang Xu
    • 1
    • 2
  • Jinguang Gu
    • 1
    • 2
  1. 1.College of Computer Science and TechnologyWuhan University of Science and TechnologyWuhanChina
  2. 2.Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial SystemWuhanChina

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