Automatic operation and maintenance method and device for platform database and computer readable storage medium

Abstract

The invention relates to a big data technology, and discloses an automatic operation and maintenance method for a platform database. The method comprises the steps of obtaining a real-time data set generated in a platform database based on the platform database of a user, and performing clustering processing on the real-time data set to generate a standard data set, calculating an autocorrelationfunction set and a partial autocorrelation function set of the standard data set to obtain an autocorrelation function graph set and a partial autocorrelation function graph set, generating a databasequota prediction model according to the autocorrelation function graph set and the partial autocorrelation function graph set, and using the database quota prediction model to identify the platform database needing to be subjected to space quota from the platform database, marking the platform database needing to be subjected to quota and then returning the database to the user, and achieving automatic operation and maintenance of the platform database. The invention further provides an automatic operation and maintenance device for a platform database and a computer readable storage medium.Automatic operation and maintenance of the platform database are realized.

Description

technical field [0001] The present invention relates to the field of big data technology, in particular to a platform database automatic operation and maintenance method, device and computer-readable storage medium. Background technique [0002] In the Internet era where the amount of data is exploding, the amount of data is increasing day by day, which poses a huge challenge to the management and operation and maintenance of the platform database, especially with the horizontal expansion of business volume, the space and number of data warehouses will also increase. , many business platforms have multiple data warehouses at the same time. When the space in the data warehouse is insufficient, the operation and maintenance personnel are usually required to manually perform the expansion configuration. At present, the expansion size is generally "arbitrarily" given by the subjective judgment of the operation and maintenance personnel in the industry. This method has two disadv...

AI Technical Summary

Problems solved by technology

When the space in the data warehouse is insufficient, the operation and maintenance personnel are usually required to manually perform the expansion configuration. At present, the expansion size is generally given "arbitrarily" based on the subjective judgment of the operation and maintenance personnel in the industry. This method has two disadvantages: 1. The number of platform databases is huge, and manual maintenance is relatively cumbersome; 2. The expansion space may be large or small. If the configuration is too large, resources will be wasted. If the configuration is too small, it will need to be reconfigured later, which increases a lot of workload.

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