摘要
洪灾数据类型多样、结构复杂、数据量巨大,随着时间累积给传统平台带来巨大压力。针对这个问题,通过结合大数据处理技术,将洪灾数据存储到云平台中,提高洪灾数据查询效率。根据洪灾数据的特征,将类型和种类进行分类,并通过HBase与HDFS相结合对洪灾数据存储进行设计。最终实现了洪灾数据的分布式存储、查询与管理,通过设计索引,提高了洪灾数据的查询效率和速度。应用结果表明,随着数据增长,研究设计的存储方案查询时间逐渐接近并小于传统平台的查询时间,能够提高洪灾数据利用效率。
Absrtact:Flood data is of various types,complex structure and huge amount,which brings huge pressure to traditional platforms over time.In view of this problem,by combining with big data processing technology,the flood data is stored in the cloud platform to improve the efficiency of flood data query.According to the characteristics and types of flood data,it can be divided into three data types and six data types,and the design of flood data storage is carried out by the combination of HBase and HDFS.Finally,the distributed storage,query and management of flood data are realized.Through the design of index,the query efficiency and speed of flood data are improved.The application results show that with the growth of data,the query time of the storage scheme is gradually close to and less than that of the traditional platform,which can improve the utilization efficiency of flood data.
作者
邹聪聪
范哲南
徐笑笑
李冰
Zou Congcong;Fan Zhenan;Xu Xiaoxiao;Li Bing(School of Civil and Surveying&Mapping Engineering Jiangxi University of Science and Technolog,Ganzhou 341000,Jiangxi,China)
出处
《长江信息通信》
2021年第9期76-78,共3页
Changjiang Information & Communications
