Research on Meteorological Data Storage Technology Based on NetCDF

With the rapid development of sensor technology and Internet technology, the amount of data collected in meteorological and scientific fields has soared. The data stored in NetCDF format is faced with the challenges of being damaged, difficult to recover, and frequent calls to disk resources. Although Hadoop distributed storage solutions have obvious advantages, HDFS based file system tools cannot be directly used for data processing due to their lack of support for the NetCDF format. Therefore, this article delves into the storage and write mechanism and block architecture of HDFS, and extends the read and write interface of NetCDF data to improve data portability, access efficiency, and sharing convenience, thereby providing strong support for scientific computing.

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Publication Details

Published
2024-08-04
DOI
https://doi.org/10.1109/icma61710.2024.10633094
Primary Topic
Advanced Computational Techniques and Applications
Type
article
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article

Research on Meteorological Data Storage Technology Based on NetCDF

Yachen Liu, Qi Wang
Advanced Computational Techniques and Applications
article

Research on Meteorological Data Storage Technology Based on NetCDF

Yachen Liu, Qi Wang
article en

Abstract

With the rapid development of sensor technology and Internet technology, the amount of data collected in meteorological and scientific fields has soared. The data stored in NetCDF format is faced with the challenges of being damaged, difficult to recover, and frequent calls to disk resources. Although Hadoop distributed storage solutions have obvious advantages, HDFS based file system tools cannot be directly used for data processing due to their lack of support for the NetCDF format. Therefore, this article delves into the storage and write mechanism and block architecture of HDFS, and extends the read and write interface of NetCDF data to improve data portability, access efficiency, and sharing convenience, thereby providing strong support for scientific computing.

Tianjin Meteorological Bureau (CN)
Climate action
Openalex Percentile: Top 89%
Advanced Computational Techniques and Applications
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