How to use MySQL’s explain analysis tool to understand query performance

With the continuous development of Internet technology, databases have become one of the important data storage methods. In actual development work, optimizing database query performance is particularly important. MySQL is one of the widely used relational database management systems, and using MySQL's explain analysis tool can provide a good understanding of query performance. This article will introduce how to use MySQL's explain analysis tool to optimize query performance.

1. What is MySQL's explain analysis tool

MySQL's explain analysis tool is a tool used to analyze query performance and understand query optimizer and index usage. By using the explain analysis tool, you can view the query optimization process of the MySQL optimizer, the execution plan of the query operation, and obtain the analysis results to help us optimize query performance.

2. How to use MySQL’s explain analysis tool

The following will introduce the steps of using MySQL’s explain analysis tool to analyze query performance:

1. Execute query statements

First, you need to execute the query statement. For example, execute the following query statement:

SELECT * FROM table WHERE column = 'value';

2. Use the explain statement

Then, in the query statement Add the explain keyword before executing the following explain statement:

EXPLAIN SELECT * FROM table WHERE column = 'value';

At this time, MySQL will return a table containing the query statement execution plan. This table can be used to help us analyze query performance.

3. View execution plan

The execution plan is the core part of the explain analysis tool, which includes the execution process of the query optimizer, the execution plan of the query operation, and the used index. Understanding the execution plan can help us understand where the query performance bottleneck is, and we can improve query performance by optimizing indexes and other means.

The execution plan table will list the tables involved in our query statement, the indexes used, the query sequence, and the execution time of each query operation. The following is an example of a typical execution plan table:

id	select_type	table	type	possible_keys	key	key_len	ref	rows	filtered	Extra
1	SIMPLE	table	ref	column	column	4	const	100000	100.00	Using index

Among them, the meaning of each column is as follows:

• id: query operation number. There may be multiple query operations in the same query statement.
• select_type: Query type, including SIMPLE, PRIMARY, SUBQUERY, UNION, etc.
• table: The name of the table involved.
• type: The index type involved in this query, including const, eq_ref, ref, range, index, ALL, etc.
• possible_keys: List of indexes that may be used.
• key: The actual index used.
• key_len: The index length used.
• ref: The referenced index column.
• rows: The number of rows in the query result.
• filtered: The filtering ratio of query results.
• Extra: Contains special information, such as the use of indexes, sorting methods, etc.

3. How to optimize query performance based on the execution plan

According to the execution plan, you can have a good understanding of the query performance bottleneck and then optimize it.

1. Optimize index

In the execution plan, we can see the usage of the index and optimize it based on the usage of the index. For example, if no index is used or the index used is not the best choice, consider adding a new index or modifying the index.

2. Modify the query statement

The execution plan also contains information such as the execution order and execution time of the query operation. You can modify the order of the query statement or modify the query conditions, etc. and other methods to optimize query performance.

3. Optimize query operations

In the execution plan, you can also see information such as the execution time of the query operation. You can optimize the query operation based on the information, such as using it more efficiently. query methods, etc.

4. Summary

MySQL's explain analysis tool is a very practical tool that can better understand query performance and optimize indexes, modify query statements, or optimize query operations. Improve query performance. Therefore, when developing related MySQL databases, we must make full use of explain analysis tools to optimize query performance, improve system stability and scalability, and provide users with better services.

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