基于Hadoop平台的语义数据查询策略研究.pdf
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ISSN 1673 -9418 CODEN JKYTA8 E-mail: fcst@
Journal of Frontiers of Computer Science and Technology
1673-9418/2000/00(00)-0000-00 Tel : +86- 10
doi: 10.3778/j.issn.1673-9418.1509010
基于Hadoop 平台的语义数据查询策略研究*
胡志刚,景冬梅,陈柏林,杨柳+
中南大学软件工程学院,长沙 410073
*
ResearchonSemantic Data Query Method Based on Hadoop
HU Zhigang,JING Dongmei, CHEN B ailin,YANG Liu+
College of Software Engineering, Central South University, Changsha410073 ,China
+ Corresponding author: E -mail : yangliu@
HU Zhigang,JING Dongmei, CHEN B ailin, et al. Researchon Semantic D ata Query Method
B ased on Hadoop.Journal of Frontiers of Computer Science and Technology, 2000, 0(0): 1 -000.
Abstract : In order to achieve the efficient query for large-scale RDF (Resource Description
Framework)data, this paper analyzes the storage method of RDF triples in HBase and design sa
two -phase query strategy for large-scale RDF data based on MapReduce , which is divided into two
stages: the SPARQL(Simple Protocol and RDF Query Language) pretreatment stage and the distributed
query execution stage. In the SPARQL pretreatment stage, an SPARQL query classification
algorithm-JOVR(Join on Variable Relation) is implemented , which determines the join order of
connection variablesby calculating the correlation between the variables in a SPARQL query statement,
then the join between SPARQL clauses is dividedinto the minimum numberof MapReduce jobs
according to the connection variables . The distributed query execution phase accomplishes large -scale
RDF data query concurrentlybased on MapRdecue jobs from SPARQL pretreatment stage.The
experimental resul
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