Research on Guangdong Province Meteorological Data Analysis System under Hadoop Environment

Zhuxin Liu

doi:10.62051/znetn254

Authors

Zhuxin Liu

DOI:

https://doi.org/10.62051/znetn254

Keywords:

Hadoop; Guangdong Province; Meteorological Data; Analysis System.

Abstract

In order to better monitor and manage the real-time transmission of meteorological information in Guangdong Province and improve communication quality, the Guangdong Meteorological Information Center has organized the development of the Guangdong Meteorological Data Analysis System. The system has the characteristics of intuitive and easy to use, strong real-time performance, and convenient query and statistics, which better meets the real-time monitoring and time management requirements of meteorological information transmission in Guangdong Province. Hadoop is a popular big data computing oriented, open-source big data processing system. Its characteristics of high throughput, high fault tolerance and easy expansion make it widely used in all walks of life. Therefore, this article focuses on the characteristics of real-time reception of meteorological information in Guangdong Province, and introduces the development ideas, use of some new technologies, and page implementation of the Guangdong Meteorological Data Analysis System under Hadoop environment. In the Hadoop environment, it is possible to dynamically exchange data with the server without refreshing the entire page, improving the efficiency of data transmission between the server and client, making browsing more intuitive and convenient. Enriched the methods and capabilities of data processing.

Downloads

Download data is not yet available.

References

Xiaofang W, Zhengquan C, Liping J,et al Analysis of a Rare Cryogenic Freezing Rain and Snow Event in Cold Wave Weather over Guangdong Province in 2016[J].Meteorological Science and Technology, 2022, 32(16):31-39.

Zhang Y, Chen X, Bi S, et al. Design and Application of Integrated Monitoring Model for Provincial Meteorological Observation Data Transmission[J]. Journal of Earth Science and Environmental Protection, 2019, 7(5):11-20.

Lin-Gen Y, Jing-Yong Z, Computer D O. Design of LTE Performance Analysis and Prediction System Based on Hadoop[J]. Modern Computer, 2019, 12(4):16-20.

Huanli L, Zenglu F, Chan L. Comprehensive Assessment and Analysis of National Surface Meteorological Observation Stations: A Case Study of Hebei Province[J]. Meteorological and Environmental Research: English Version, 2019, 10(4):7-16.

Jinqing Y, Yaobo H, Xiqing L U, et al. Application of Agrometeorological Proverbs in the Climate Prediction of Precipitation in Flood Seasons[J]. Chinese Journal of Tropical Agriculture, 2021, 25(4):19-26.

Hua W, Yaodong D, Yu Z, et al. Insurance Risk Zoning of Late Rice Cold Dew Wind in Guangdong[J]. Meteorological and Environmental Sciences, 2018.

Pang Guqian, He Jian, Liu Chang, et al. Hazard Analysis of Severe Convective Weather in Guangdong Province, China[J]. Journal of Tropical Meteorology: English Edition, 2021, 27(2):8-18.

Cui W, Chen-Xian Z, Si-Yuan H. Analysis of A Warm-sector Heavy Rain in Qingyuan, Guangdong[J]. Guangdong Meteorology, 2022, 18(5):16-24.

Xiaowei R, Zhi H, Liqun Z. The application of Hadoop in the storage of meteorological data[J].Journal of Meteorological Research and Application, 2022, 36(20):25-36.

Zhi H, Liqun Z, Xiaowei R, et al. Query and Statistical Analysis of Mass Automatic Station Data Based on SparkSQL in Hadoop Environment[J]. Meteorological Science and Technology, 2019, 32(5):11-16.