【作者】 康大维； 毛雪岷；

【Author】 Kang Da-Wei;Mao Xue-Min;School of Management,Hefei University of Technology;Key Laboratory of Process Optimization and Intelligent Decision-Making,Ministry of Education;

【机构】 合肥工业大学管理学院； 合肥工业大学过程优化与智能决策教育部重点实验室；

【摘要】 随着大数据与互联网技术发展,移动终端的数量不断增加,从而形成海量空间数据,空间数据的存储与分析已经成为当下研究的热点。传统方法无法存储与处理海量数据,并且中文处理能力欠佳。基于此,本文提出了基于云端Hadoop处理框架。该处理框架利用云端部署Hadoop集群,HBase存储,Lucene等技术建立了中文空间数据存储与检索处理流程,克服了地址查询、长字段查询等查询功能上的局限性。实验结果表明:基于云端hadoop海量空间数据存储与检索对处理中文数据有很强的优势。本文提出的处理框架,对于大数据环境下,海量空间数据的信息的检索与存储具有重要的启示。更多还原

【Abstract】 With the development of large data and Internet technology,the number of mobile terminals is increasing,thus forming huge amounts of spatial data.The storage and analysis of spatial data has become the focus of current research.Traditional methods are unable to store and process large amounts of data and have poor processing ability in chinese.Based on this,this paper proposes a framework for cloud based Hadoop processing.The framework uses cloud deployment Hadoop cluster,HBase storage,Lucene technology has established Chinese interest point data storage and retrieval process,overcomes the limitation of address query,query query length field function.The experimental results show that cloud based Hadoop data storage and retrieval has great advantages in processing Chinese data.The framework proposed in this paper has important implications for the retrieval and storage of massive spatial data in large data environment.更多还原