地理要素的分布式空间近似查询处理方法

针对传统空间查询无法满足地理数据交互式可视化对处理时间要求的问题,以窗口查询为例,提出了一种空间近似查询处理方法。该方法包括预处理和查询两步:在预处理阶段,利用分布化的线简化算法对空间对象进行顾及误差的预处理采样,将采样过程及误差值用树型结构保存;在查询阶段,以豪斯多夫距离定义数据可视化的误差,进行误差可知的顶点即时采样与截取,从而实现针对可视化应用的高效的空间近似查询处理。在Hadoop集群上利用77GB的OpenStreetMap数据集进行了实验,证实了本方法的效力与效率。

Distributed approximate spatial query processing method of geographical features

Interactive visualization of global scale fine detailed geographic data calls for high performance spatial query processing especially the windowing queries.This paper studies the approximate spatial query processing,which is dedicated for data visualization,to tackle the performance problem.Taking the geographic features as the target dataset and hausdorff distance of original and simplified feature as visualization error,it presents the distributed approximate spatial query processing techniques which comprise two stages.In the first stage,features are preprocessed using Ramer-Douglas-Peuker algorithm to sample points considering visualization error,then the order during the points sampling and the errors are preserved in binary trees.In the second stage,points of features are retrieved by binary trees' breadth-first-searching with error priority queue and spatial constraint.Extensive experiments on real-world data show the effectiveness and efficiency of the introduced method.