摘要
大数据体时空网格可视化涉及的数据量通常非常庞大,并且数据类型多样、结构复杂。同时,随着时间推移,数据的动态性也带来了挑战。处理和分析如此庞大和复杂的数据集,需要强大数据处理方法以及时空数据排序技术,为此,设计大数据体时空网格可视化智能管理方法。通过预处理时空数据,剔除冗余时空数据并补齐缺失时空数据,制定大数据体时空网格化流程。以此为基础,根据时空数据重要程度编码与排序时空网格,确定时空网格的优先级,以地图作为基础底图,充分利用地理信息技术可视化功能,通过地图形式可视化展示时空网格与时空数据,并采用HBase数据库存储时空数据,实现大数据体时空网格可视化智能管理方法的设计。试验数据表明:在不同试验工况背景下,所涉及方法应用后的时空数据网格匹配率最大值为98%,时空数据可视化分辨率最大值为960 ppi,充分证实了该方法的应用效果好。
The spatiotemporal grid visualization of big data volume usually involves a huge amount of data,and the data types are diverse and the structure is complex.At the same time,the dynamic nature of data over time also presents challenges.Processing and analyzing such a large and complex data set requires powerful data processing methods and spatiotemporal data sequencing technology.Therefore,a visualized intelligent management method for spatiotemporal grid of large data volumes was designed.Preprocess spatiotemporal data,eliminate redundant spatiotemporal data and supplement missing spatiotemporal data,and develop spatiotemporal grid process of big data.On this basis,the spatio-temporal grid was coded and sorted according to the importance of spatio-temporal data,and the priority of spatio-temporal grid was determined.The visualization function of geographic information technology was taken as the basic base map,the spatio-temporal grid and spatio-temporal data were visualized in the form of maps,and the spatio-temporal data was stored in the HBase database.The design of visualization intelligent management method of spatiotemporal grid of big data volume.Experimental data show that under different experimental conditions,the maximum matching rate of spatio-temporal data grid after application of the method is 98%,and the maximum spatial and temporal data visualization resolution is 960 ppi,which fully proves that the application effect of the method is better.
作者
张涛
胡中瑞
匡建宇
杨猛
李智明
魏同寿
ZHANG Tao;HU Zhong-rui;KUANG Jian-yu;YANG Meng;LI Zhi-ming;WEI Tong-shou(Beijing Huadian Electronic Commerce Technology Co.,Ltd.,Beijing 100070,China;China Huadian Group Materials Co.,Ltd.,Beijing 100032,China;China Huadian Group Co.,Ltd.,Beijing 100032,China)
出处
《科学技术与工程》
北大核心
2024年第32期13872-13878,共7页
Science Technology and Engineering
基金
北京华电电子商务科技有限公司科技攻关项目(GT202305000071)。
关键词
时空数据
大数据体
网格编码
数据可视化
智能管理
数据处理
spatiotemporal data
big data body
grid encoding
data and information visualization
intelligent management
data proces
