How to implement MySQL underlying optimization: the working principle and tuning method of the query optimizer

How to realize MySQL underlying optimization: the working principle and tuning method of the query optimizer

In database applications, query optimization is one of the important means to improve database performance. . As a commonly used relational database management system, MySQL’s query optimizer’s working principle and tuning method are very important. This article will introduce how the MySQL query optimizer works and provide some specific code examples.

1. The working principle of the MySQL query optimizer

1. Query parsing phase
   The work of the query optimizer begins in the query parsing phase. MySQL first performs lexical analysis and syntax analysis on the SQL query statement and converts it into a query tree (Query Tree). The query tree contains the semantic information of the query.

Sample code:

SELECT name, age FROM users WHERE gender = 'male';

Query Tree diagram:

SELECT / name WHERE | gender / male

2. Query optimization phase
   In the query optimization phase, the MySQL query optimizer will The query tree is optimized and an executable query plan is generated. The optimizer will select the optimal query plan based on statistical information, index information, and other optimization rules.

Sample code:

EXPLAIN SELECT name, age FROM users WHERE gender = 'male';

Query plan diagram:

id select_type table type possible_keys key key_len ref rows Extra 1 SIMPLE users ref gender gender 2 const 5000 Using where

3. Query execution phase
   In the query execution phase, MySQL will execute according to the query plan Query operations and return query results.

2. Tuning methods for MySQL query optimization

1. Use appropriate indexes
   Indexes are one of the important means to improve query performance. You can speed up queries by adding indexes to fields that are frequently queried. But too many or unreasonable indexes will increase the cost of insert, update, and delete operations.

Sample code:

ALTER TABLE users ADD INDEX idx_gender (gender);

2. Avoid full table scan
   Full table scan is one of the main reasons for low query efficiency. Full table scans should be avoided as much as possible through appropriate query conditions, reasonable indexes, and partitions.

Sample code:

SELECT name, age FROM users WHERE gender = 'male';

3. Use appropriate data types
   Appropriate data types can improve query performance. Using data types that are too long or inappropriate increases storage and query overhead.

Sample code:

CREATE TABLE users ( id INT PRIMARY KEY, name VARCHAR(100), age TINYINT UNSIGNED, gender ENUM('male', 'female') );

4. Avoid large table joins
   Large table joins are one of the main causes of low query performance. Join operations between large tables should be avoided as much as possible, and queries can be optimized by partitioning and using temporary tables.

Sample code:

SELECT u.name, o.order_id FROM users u JOIN orders o ON u.id = o.user_id;

5. Pay attention to the performance of subqueries
   Subqueries are one of the difficulties in query optimization. Complex subqueries should be avoided as much as possible, and subqueries can be optimized through temporary tables, table connections, etc.

Sample code:

SELECT name, age FROM users WHERE id IN (SELECT user_id FROM orders);

Summary:
The working principle of the MySQL query optimizer is to improve query performance by optimizing the query tree and generating an executable query plan. . Tuning methods include using appropriate indexes, avoiding full table scans, using appropriate data types, avoiding large table joins, and optimizing subqueries. Proper use of these tuning methods can significantly improve the performance of the MySQL database.

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