Statement early warning method and device, equipment and computer readable storage medium

Abstract

The invention discloses a statement early warning method. The method comprises the steps of obtaining a structured query statement of an application program accessing a preset production database; obtaining an execution plan of the structured query statement, and extracting preset parameters related to slow query from the execution plan; judging whether the extracted preset parameters meet a preset slow query early warning condition or not; and when the preset parameter satisfies a preset slow query early warning condition, adding the corresponding structured query statement into a preset early warning list. The invention further discloses a statement early warning device, equipment and a computer readable storage medium. The optimization cost of slow query can be reduced on the premise that the performance of the production database is not influenced.

Description

technical field [0001] The invention relates to the technical field of financial technology (Fintech), in particular to a sentence early warning method, device, equipment and a computer-readable storage medium. Background technique [0002] With the continuous development of financial technology (Fintech), especially Internet technology finance, more and more technologies are applied in the financial field. MySQL is currently one of the most popular relational database management systems, and SQL (Structured Query Language, Structured Query Language) used by MySQL is the most commonly used standardized language for accessing databases. In the process of using SQL language to query the database, the phenomenon that the query response time exceeds the specified time is called slow query. Slow query will affect the performance of the database and application system, and in severe cases, it will affect the availability of the application system. [0003] At present, in order to...

AI Technical Summary

Problems solved by technology

The disadvantages of this method are: 1) When an abnormality is detected, the slow query in the production database has already formed, and the formed slow query often means that the data scale of the target table of the query has grown relatively large, forming a large table, while When the optimization plan involves operations such as adding indexes, adding fields, and partitioning to large tables, it will be accompanied by a long period of time for the production database to lock the table. During this period, the business that has write operations on the large table cannot be carried out normally. , which results in higher optimization costs for slow queries

2) The monitoring logic has query operations on the production database, which objectively increases the load on the production database. In addition, the monitoring logic and the production database are deployed on the same physical resource, which will also cause certain resource contention and affect the performance of the production database.

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