引用本文:朱欣焰,周春辉,呙维,夏宇.分布式空间数据分片与跨边界拓扑连接优化方法.软件学报,2011,22(2):269-284
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分布式空间数据分片与跨边界拓扑连接优化方法
朱欣焰1,2, 周春辉3, 呙维1, 夏宇4
1.武汉大学 测绘遥感信息工程国家重点实验室,湖北 武汉 430079;2.武汉大学 空天信息安全与可信计算教育部重点实验室,湖北 武汉 430079;3.武汉理工大学 航运学院,湖北 武汉 430063;4.江西师范大学 地理与环境学院,江西 南昌 330022
摘要:
研究分布式空间数据库(distributed spatial database,简称DSDB)中数据按区域分片时的跨边界片段拓扑连接查询问题,并提出相应的优化方法.首先研究了分布式环境下的空间数据的分片与分布,提出了空间数据分片的扩展原则:空间聚集性、空间对象的不分割性、逻辑无缝保持性.然后,将区域分割分片环境下的片段连接分为跨边界和非跨边界两类;同时,将拓扑关系分为两类,重点研究跨边界的两类片段拓扑连接.提出了跨边界空间片段拓扑连接优化的两个定理,并给出了证明.以此为基础,给出了跨边界空间拓扑连接优化规则,包括连接去除规则和连接优化转化规则.最后设计了详细的实验,对自然连接策略、半连接策略以及所提出的连接策略进行效率比较,结果表明,所提出的方法对跨边界连接优化有明显优势.因此,所提出的理论和方法可以用于分布式跨边界拓扑关系查询的优化.
关键词:  空间数据库  区域分片  跨边界  拓扑连接  分布式查询  优化
DOI:10.3724/SP.J.1001.2011.03798
分类号:
基金项目:国家自然科学基金(40971232, 41023001); 国家高技术研究发展计划(863)(2007AA12Z201); 测绘遥感信息工程国家重点实验室开放基金; 测绘遥感信息工程国家重点实验室专项科研经费; 武汉大学优秀博士论文培育基金(2008-25)
Distributed Spatial Data Fragmentation and Cross-Border Topological Join Optimization
ZHU Xin-Yan1,2, ZHOU Chun-Hui3, GUO Wei1, XIA Yu4
1.State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China;2.Key Laboratory of Aerospace Information Security and Trusted Computing of the Ministry of Education, Wuhan University, Wuhan 43;3.Navigation College, Wuhan University of Technology, Wuhan 430063, China;4.School of Geography and Environment, Jiangxi Normal University, Nanchang, 330022, China
Abstract:
This paper aims at explaining the cross-border topological join queries of spatial fragments of the zone fragmentation data in distributed spatial database (DSDB), and the optimizing methods for such queries are proposed. First, the fragmentation and distribution of spatial data in a distributed environment are discussed, and the extra principles for spatial data fragmentation are put forward, including spatial clustering, non-partitioning on spatial objects, and maintaining logical seamless. Then, the fragment joins in zone fragmentation are classified into two categories: cross-border join and non-cross-border join; the topological relationships are also classified into two categories. Thus, the emphasis is put on the two types of cross-border topological joins. Two theorems for cross-border topological join optimization are proposed and proved. Based on the theorems, the optimizing rules for cross-border spatial topological join are given, including the removing rules and the transforming rules of fragment joins. Finally, tests are designed to compare three join strategies that include Na?ve join strategy, semi-join strategy and the proposed strategies. The results show that the proposed methods greatly improve the cross-border join optimizing efficiency. Therefore, the theorems and methods proposed in this work can be applied to the optimization of distributed cross-border spatial topological queries.
Key words:  spatial database  zonal fragmentation  cross-border  topological join  distributed query  optimization

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