Grid point data processing method and related equipment thereof

Abstract

The invention provides a grid point data processing method which comprises the following steps: creating a database table in a database according to a preset lattice point data structure, wherein the database table comprises a grid point data field and at least one attribute field; reading multiple groups of to-be-processed grid point data and at least one piece of attribute information corresponding to each group of grid point data from the data set; for each group of grid point data, packaging the grid point data into a grid point data object according to a preset grid point data object structure; and for each group of grid point data, writing the grid point data object into a grid point data field of a data record of the database table, and respectively writing the at least one piece of attribute information into an attribute field corresponding to the at least one piece of attribute information in the data record. Corresponding to the grid point data processing method, the invention further provides a grid point data processing device, electronic equipment and a computer readable storage medium.

Description

technical field [0001] One or more embodiments of the present disclosure relate to data processing technologies, and in particular, to a grid point data processing method, a grid point data processing device, electronic equipment, and a computer-readable storage medium. Background technique [0002] With the increase of the types of meteorological observation data and the increase of observation frequency, the amount of meteorological data is increasing. Meteorological data is a typical type of big data, which has the characteristics of large data volume, high timeliness, and rich data types. At present, many meteorological data are stored in the form of grid point data, also known as meteorological grid point data, for example, precipitation data or temperature data in a certain area, and so on. Meteorological grid point data usually divides the space into multiple grids according to latitude and longitude, each grid is called a grid point, and the position of the entity r...

AI Technical Summary

Problems solved by technology

However, this method of adding a relational database to a file system is often difficult to withstand the increase in the number of files with a large amount of data, and the tree structure of the file directory cannot well meet the characteristics of sequential access to data. When querying or analyzing point data, the file system needs to download all meteorological grid point data from the relational database before analyzing and processing them, resulting in a very long processing time

Therefore, this model cannot well meet the processing requirements of meteorological grid data

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