Containerization-based relational database optimization method and device

Abstract

The invention discloses a containerization-based relational database optimization method and device, and the method comprises the steps: obtaining a database access request, carrying out the judgmentbased on the database access request, and carrying out database optimization through a database buffer according to a judgment result, and monitoring whether the memory or CPU utilization rate of thedatabase buffer is higher than a preset threshold value or not in real time, recording a log and sending a log notification when the memory or CPU utilization rate is higher than the preset thresholdvalue, receiving the log notification and analyzing the log to judge changed data, and performing transverse / longitudinal expansion on the database buffer according to a preset value in configuration.

Description

technical field [0001] The present invention relates to the field of database optimization, and more specifically, the present invention relates to a container-based relational database optimization method and device. Background technique [0002] Database computing originated in the 1960s. From the initial simple file system processing to the current database system that handles a large amount of complex data, the application field has also penetrated into all aspects of life. Today, database technology has become a data storage Indispensable tools for managing, sharing and processing data. [0003] With the continuous expansion of the business involved in the database application system, the continuous increase in the number of database users, the gradual increase in the processing business volume, the rapid growth of the database mass storage, the performance problems of the database have become more and more prominent, and the rapid growth of the data volume is the datab...

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Problems solved by technology

[0003] With the continuous expansion of the business involved in the database application system, the continuous increase in the number of database users, the gradual increase in the processing business volume, the rapid growth of the database mass storage, the performance problems of the database have become more and more prominent, and the rapid growth of the data volume is the database The main driving force of performance optimization research. Small-scale databases generally do not have performance problems, and application systems with small data volumes cannot obtain substantial performance improvements from optimization. Database optimization should run through the entire process from demand research to system decommissioning , but in practical applications, data performance is often the last consideration in system implementation. Therefore, it is necessary to propose a container-based relational database optimization method and device, so as to partially solve the problems existing in the prior art

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