基于代理的并行空间查询语言
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摘要
目前针对并行空间数据处理的研究主要集中在空间数据划分及其在其基础上的并行空间算法,对空间并行数据库平台本身的可用性,如应用程序的开发模式、高并发请求支持等研究较少。为此,对开源并行关系数据库查询语言进行空间查询扩展,提出一种基于代理的并行空间查询语言,并实现相应的并行数据库平台原型。基于该平台开发标准的网络地图绘图服务,在高并发环境下使用该服务对海量矢量数据进行实时渲染。实验结果表明,该平台具有与传统关系数据库一致的开发应用模式,可提供无缝的衔接方式,在海量数据高并发的情况下具有较高的可用性及查询性能。
Currently, researches on parallel spatial processing are focusing on data declustering and the corresponding algorithms. Less attention is paid on the spatial parallel database platform, especially, on issues like development mode support and intensive concurrent visits. Therefore, this paper proposes a parallel spatial query language based on proxy mechanism, and implements a prototype platform based on it. This paper develops the standard Web Mapping Service(WMS) based on this platform, and uses WMS to render large scale vector datasets. Experimental result shows that this platform is consistent with same development and application mode of the traditional relational database. It can provide seamless connection, and has high availability and query performance under the condition of the mass data high concurrency.
Currently, researches on parallel spatial processing are focusing on data declustering and the corresponding algorithms. Less attention is paid on the spatial parallel database platform, especially, on issues like development mode support and intensive concurrent visits. Therefore, this paper proposes a parallel spatial query language based on proxy mechanism, and implements a prototype platform based on it. This paper develops the standard Web Mapping Service(WMS) based on this platform, and uses WMS to render large scale vector datasets. Experimental result shows that this platform is consistent with same development and application mode of the traditional relational database. It can provide seamless connection, and has high availability and query performance under the condition of the mass data high concurrency.
引文
[1]龚卫华.数据库集群系统的关键技术研究[D].武汉:华中科技大学,2006.
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[7]Ramirez M R,de Souza J M.Distributed Spatial Query Processing over MPI[D].Rio de Janeiro,Brazil:Universidade Federal do Rio de Janeiro,2003.
[8]王璟.基于MPI和MySQL的并行数据库系统的研究与实现[D].北京:中国科学院研究生院,2004.
[9]PgFoundry.PgFoundry:PL/Proxy:Project Info[EB/OL].[2012-10-11].http://pgfoundry.org/projects/plproxy/.
[10]Shekhar S,Ravada S,Kumar V,et al.Declustering and Load-balancing Methods for Parallelizing Geographic Information Systems[J].IEEE Transactions on Knowledge and Data Engineering,1998,10(4):632-655.
[11]Dittrich J P,Seeger B.Data Redundancy and Duplicate Detection in Spatial Join Processing[C]//Proc.of ICDE’00.San Diego,USA:IEEE Press,2000.
[12]Chung W,Park S Y,Bae H Y.Efficient Parallel Spatial Join Processing Method in a Shared-nothing Database Cluster System[C]//Proc.of ICESS’05.Xi’an,China:[s.n.],2005.
[13]张书彬,韩冀中,刘志勇,等.基于MapReduce实现空间查询的研究[J].高技术通讯,2010,20(7):719-726.
[2]Madden S,DeWitt D,Stonebraker M.Database Parallelism Choices Greatly Impact Scalability[EB/OL].[2012-10-11].http://www.databasecolumn.com/2007/10/database-parallelism choices.html.
[3]田光.并行计算环境中矢量空间数据的划分策略研究与实现[D].武汉:中国地质大学,2011.
[4]Patel J M,DeWitt D J.Partition Based Spatial-merge Join[C]//Proc.of ACM SIGMOD International Conference on Management of Data.New York,USA:ACM Press,1996.
[5]Patel J,Yu Jiebing,Kabra N,et al.Building a Scaleable Geo-spatial DBMS:Technology,Implementation,and Evaluation[C]//Proc.of ACM SIGMOD International Conference on Management of Data.New York,USA:ACM Press,1997.
[6]赵春宇.高性能并行GIS中矢量空间数据存取与处理关键技术研究[D].武汉:武汉大学,2006.
[7]Ramirez M R,de Souza J M.Distributed Spatial Query Processing over MPI[D].Rio de Janeiro,Brazil:Universidade Federal do Rio de Janeiro,2003.
[8]王璟.基于MPI和MySQL的并行数据库系统的研究与实现[D].北京:中国科学院研究生院,2004.
[9]PgFoundry.PgFoundry:PL/Proxy:Project Info[EB/OL].[2012-10-11].http://pgfoundry.org/projects/plproxy/.
[10]Shekhar S,Ravada S,Kumar V,et al.Declustering and Load-balancing Methods for Parallelizing Geographic Information Systems[J].IEEE Transactions on Knowledge and Data Engineering,1998,10(4):632-655.
[11]Dittrich J P,Seeger B.Data Redundancy and Duplicate Detection in Spatial Join Processing[C]//Proc.of ICDE’00.San Diego,USA:IEEE Press,2000.
[12]Chung W,Park S Y,Bae H Y.Efficient Parallel Spatial Join Processing Method in a Shared-nothing Database Cluster System[C]//Proc.of ICESS’05.Xi’an,China:[s.n.],2005.
[13]张书彬,韩冀中,刘志勇,等.基于MapReduce实现空间查询的研究[J].高技术通讯,2010,20(7):719-726.