周芹, 钟耳顺, 黄耀欢, 郭会. 大型空间数据库的并发索引策略CQR树[J]. 武汉大学学报 ( 信息科学版), 2009, 34(7): 856-858.
引用本文: 周芹, 钟耳顺, 黄耀欢, 郭会. 大型空间数据库的并发索引策略CQR树[J]. 武汉大学学报 ( 信息科学版), 2009, 34(7): 856-858.
ZHOU Qin, ZHONG Ershun, HUANG Yaohuan, GUO Hui. CQR-Tree:Concurrent Strategy for Spatial Index Structure in Spatial Database[J]. Geomatics and Information Science of Wuhan University, 2009, 34(7): 856-858.
Citation: ZHOU Qin, ZHONG Ershun, HUANG Yaohuan, GUO Hui. CQR-Tree:Concurrent Strategy for Spatial Index Structure in Spatial Database[J]. Geomatics and Information Science of Wuhan University, 2009, 34(7): 856-858.

大型空间数据库的并发索引策略CQR树

CQR-Tree:Concurrent Strategy for Spatial Index Structure in Spatial Database

  • 摘要: 提出了适用于客户端模式空间数据库引擎并发控制的空间索引结构——CQR树,将静态R树与四叉树相结合,采用四叉树编码与空间对象绑定的方式管理被编辑过的对象,仅在删除叶子结点包中的对象时对相关索引包加锁,缩短系统响应时间。算法简单易实现,在保证空间查询效率的前提下解决多客户端并发操作的问题,同时降低了索引的维护难度。

     

    Abstract: R-tree is incapable of managing spatial objects in concurrent environment.We proposes the CQR-tree(concurrent quad-tree & R-tree) to satisfy this situation,which is easy to integrate with existing R-tree systems.Firstly,we point out the limitation of R-tree in concurrent environment and the limitation of the R-link tree in the special system.Secondly,we introduce the CQR-tree to solve the problem.Thirdly,we list the algorithms of the CQR-tree,including insert,add,and delete operators,and the query strategy.Then,some experimental results confirm that the proposed CQR-tree performs well in concurrent environment.

     

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