International Conference on Web-Age Information Management

WAIM 2015: Web-Age Information Management pp 3-15 | Cite as

A Distributed RDF Storage and Query Model Based on HBase

  • Keran LiEmail author
  • Bin Wu
  • Bai Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9391)


Now we are living in an interconnected world and the amount of heterogeneous information data such as RDF is continually increasing. A lot has been done to find the solution to manage huge amount of RDF data. The solutions based on RDBMS have significant scalability issues considering the magnitude of data in modern time. In this paper we describe our solution to store and query RDF data in the cloud based on HBase and MapReduce. A vertical-partitioning-like model is used in HBase to reduce the table size and to obtain a good performance of SPARQL query. For complex query on large data, we propose to use cascading MapReduce job on HBase to enhance efficiency. Our experiments on LUBM show that our system can store large RDF graphs and can obtain good query efficiency.


RDF Heterogeneous Hbase Vertical partition Mapreduce 



This work is supported in part by the National Key Basic Research and Department (973) Program of China (No. 2013CB329606), and the Co-construction Project of Beijing Municipal Commission of Education.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Beijing Key Laboratory of Intelligent Telecommunications Software and MultimediaBeijing University of Posts and TelecommunicationsBeijingChina

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