Dynamic mapping method for meteorological numerical forecasting product based on NoSql database

Abstract

The invention provides a dynamic mapping method for meteorological numerical forecasting product based on an NoSql database. The method comprises the following steps of loading and analyzing meteorological metadata information; acquiring plane data and attribute data information thereof related to quick drawing; splicing the meteorological attribute data of the NoSql database to generate a Key / Value key value pair; according to query parameters dynamically transmitted in real time, dynamically reading requested data in real time in a Key / Value key value pair form, and finally, processing readblock data in parallel in a graphic algorithm device to generate a PNG format picture, so that real-time, efficient and rapid drawing of meteorological data is realized, and redundant storage of datais avoided; a non-relational NoSql database is adopted for data storage, so that the problems of I / O bottleneck and high concurrency caused by a relational database are avoided, and the data processing and analysis efficiency is improved.

Description

technical field [0001] The invention relates to a dynamic mapping method for meteorological numerical forecast products based on a NoSql database, and belongs to the technical field of dynamic mapping of meteorological data. Background technique [0002] Business units such as my country's meteorological field and numerical weather prediction center are still widely using the NetCDF dataset, which includes plane data in raster format and attribute data in descriptive form. Due to the large amount of data in a single NetCDF file of numerical weather prediction, the degree of unstructuredness is high, and the number of image files is large, resulting in a large amount of calculation data and poor real-time dynamic calculation. [0003] At present, the mapping technology of meteorological numerical forecast products generally needs to process the original data in advance according to business requirements (including regional customization, scale setting, etc.), and then store a...

AI Technical Summary

Problems solved by technology

This meteorological mapping method stores the original data and picture data, the data redundancy is large, the real-time performance of the mapping is not high, and it is difficult to achieve the WYSIWYG of the data (you need to use the mapping function of other systems to obtain your own data based on the data) desired result)

Moreover, a single plane data in meteorological data often reaches hundreds of gigabytes in size, which is not conducive to the rapid retrieval of data, especially when only single-point data is obtained, responding to all plane data will greatly reduce data processing. Analyze performance

In addition, with relational database storage, I / O bottlenecks and high concurrency problems become more serious

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