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基于代理的并行空间查询语言 被引量:2

Parallel Spatial Query Language Based on Proxy
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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.
出处 《计算机工程》 CAS CSCD 2013年第11期61-64,共4页 Computer Engineering
基金 国家"863"计划基金资助项目(2012AA12A401)
关键词 空间查询语言 并行空间数据处理 网络地图服务 并行数据库 空间查询 空间数据划分 spatial query language parallel spatial data processing Web Mapping Service(WMS) parallel database spatial query spatial data partitioning
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  • 1Kriegel H P,Brinkhoff T,Schneider R.Efficient spatial query processing in geographic database systems.Data Engineering Bulletin,1993,16:10-15.
  • 2DeWitt D,Gray J.Parallel database systems:the future of high performance database systems.Communications of the ACM,1992,35:85-98.
  • 3Dittrich J,Seeger B.Data redundancy and duplicate detection in spatial join processing.In:Proceedings of the 16th International Conference on Data Engineering,San Diego,CA,USA,2000.535-546.
  • 4Zhang S,Han J,Liu Z,et al.Parallelizing spatial join with MapReduce.In:Proceedings of the 2009 IEEE International Conference on Cluster Computing,New Orleans,Louisiana,USA,2009.
  • 5U.S.Bureau of the Census.TIGER/Line files(TM),2007 technical documentation.Washington,DC,USA,2007.
  • 6Mckee L.Building the GSDI.Wayland,USA:The Open GIS Consortium,1996.
  • 7Patel J,Yu J,Kabra N,et al.Building a scalable geo-spatial DBMS:technology,implementation,and evaluation.In:Proceedings of the 1997 ACM SIGMOD International Conference on Management of Data,Tucson,Arizona,1997.336-347.
  • 8Dean J,Ghemawat S.MapReduce:simplified data processing on large clusters.In:Proceedings of 6th Symposium on Operating System Design and Implementation,San Francisco,CA,2004.137-150.
  • 9Wikipedia.MapReduce.http://en.wikipedia.org/wiki/Map/reduce,2008.
  • 10Yang H,Dasdan A,Hsiao R L,et al.Map-reduce-merge:simplified relational data processing on large clusters.In:Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data,New York,NY,USA,2007.1029-1040.

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