Selectivity estimation based on cumulative annular bucket histogram in spatial database

被引：0

作者：

Cheng C. ^{[1
]}

Hu X. ^{[2
]}

Song X. ^{[2
]}

Chen C. ^{[3
]}

机构：

[1] Academy of Disaster Reduction and Emergency Management, Beijing Normal University, Beijing

[2] Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing

[3] State Key Laboratory of Information Security, Institute of Information Engineering, CAS, Beijing

来源：

Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University | 2016年 / 41卷 / 09期

基金：

中国国家自然科学基金;

关键词：

Cumulative AB histogram; Selectivity estimation; Spatial query optimization; Spatial selection query;

D O I：

10.13203/j.whugis20140627

中图分类号：

学科分类号：

摘要：

Selectivity estimation for spatial databases is a core scientific problem in query optimization. The exiting spatial histograms violate theintegrity of spatial objects, so it is difficult to precisely calculate the selectivity of spatial data to deduce the histograms of query results. In view of the above problems, we propose a forward cumulative annular bucket histogram, referred to as the cumulative AB histogram. This histogram establishes annular buckets to receive all spatial area objects. Therefore, it maintains the integrity of area objects and achieves better performance on the selectivity estimation and histogram deduction in fine spatial topological query. We discuss some theories of the cumulative AB-histogram in detail and propose selectivity estimation methods for fine topological queries. We take land use data as example to show accuracy of selectivity estimation and discusstopics relevant to the efficiency and scope of applications. © 2016, Research and Development Office of Wuhan University. All right reserved.

引用

页码：1183 / 1191

页数：8

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