基于Hadoop平台的语义数据查询策略研究.pdfVIP

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