基于Google S2的大数据时空索引及区域查询算法  

Spatial-temporal Index and Region Query Algorithm for Big Data Based on Google S2

作　　者：丁琛 DING Chen(Nanjing University of Science and Technology ZiJin College,Nanjing 210046,Jiangsu)

机构地区：[1]南京理工大学紫金学院,江苏南京210046

出　　处：《电脑与电信》2022年第12期54-57,共4页Computer & Telecommunication

摘　　要：随着时代的发展,轨迹数据的数据量越来越大。提出使用LevelDB作为存储轨迹数据的数据库,解决了数据快速入库、短时间捞出大量数据的问题;同时使用Google S2作为轨迹数据的时空索引,并提出了一种区域查询算法。经实验证明,使用该索引进行区域查询,无论是在查询数据的精准度上,还是查询时间上,均优于基于GeoHash作为轨迹数据时空索引。With the development of the times,the amount of track data is increasing.In this paper,LevelDB is proposed as a database to store track data,which solves the problem of fast data storage and large amount of data retrieved in a short time.At the same time,Google S2 is used as the space-time index of track data,and a region query algorithm is proposed.Experiments have shown that using this index for regional queries is superior to using GeoHash as a spatial-temporal index for track data,both in accuracy and in query time.

关 键 词：轨迹数据 LevelDB Google S2 S2编码 索引组织 区域查询算法 

分 类 号：P208[天文地球—地图制图学与地理信息工程]