一种支持高效并行处理的矢量数据索引方法  

Vector data index method supporting efficient parallel compute

作　　者：褚龙现[1,2] 李晓英[3,2] 陈旭[2] 楚纯洁[4] CHU Longxian;LI Xiaoying;CHEN Xu;CHU Chunjie(School of Software, Pingdingshan University, Pingdingshan, Henan 467000, China;Campus of Nanning, Guilin University of Technology, Nanning 530001, China;State Key Laboratory of Software Engineering, Wuhan University, Wuhan 430072, China;School of Resources and Environmental Science, Pingdingshan University, Pingdingshan, Henan 467000, China)

机构地区：[1]平顶山学院软件学院,河南平顶山467000 [2]武汉大学软件工程国家重点实验室,武汉430072 [3]桂林理工大学南宁分校,南宁530001 [4]平顶山学院资源与环境科学学院,河南平顶山467000

出　　处：《计算机工程与应用》2017年第11期79-84,共6页Computer Engineering and Applications

基　　金：国家自然科学基金青年科学基金(No.41201405);河南省科技厅科技攻关项目(No.152102310202)

摘　　要：分析了HBase的存储模型和Spark的并行处理机制,提出一种矢量空间数据的分布式存储、索引和并行区域查询方法。设计了基于空间对象中心点的行键存储方案,将中心点的Hilbert编码与经纬度小数位结合实现行键的唯一性,保证地理位置接近的要素在表中存储在相邻的行。实现了基于Spark的空间索引并行构建和区域查询方法,借助空间对象中心点的Hilbert编码快速构建索引,通过多边形区域的最小外接矩形过滤查询结果。实验结果表明,索引并行构建可靠性好速度快,区域查询并行处理算法可行且效率高。By analyzing the HBase storage model and the parallel compute mechanism of Spark,a distributed storage,index and parallel regional query method of vector spatial data is proposed.A row key storage scheme which combines the Hilbert code of central point and decimal place of longitude and latitude is designed.This scheme reaches the uniqueness of row key and guarantees the effect that the most nearest elements in geographical position are stored in the adjacent rows.A spatial index parallel build and regional query method based on Spark is realized,which generates index quickly by using the Hilbert code of spatial central points,and filters the query result by the minimum bounding rectangle of polygon regions.Simulation results show that the parallel build of index is reliability and fast,and the parallel compute algorithm based on regional query is feasible and efficient.

关 键 词：SPARK HILBERT 矢量数据 空间索引 分布式存储 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]