Detailed explanation of index optimization techniques in MySQL

MySQL is an open source relational database management system that is widely used in various websites and applications. Indexes are one of the key performance optimization methods in MySQL, which are especially important for large data tables. This article will introduce index optimization techniques in MySQL and attach corresponding code examples.

1. What is an index
An index is a special data structure used to speed up database queries. It is similar to the table of contents of a book, and you can quickly find the required data rows through the index. In MySQL, the B-Tree index structure is mainly used.

2. Select the correct index column

1. Uniqueness: Select a column with a high degree of uniqueness as the index column. For example: user name, email, etc. in the user table.
2. Frequent queries: Select frequently queried columns as index columns. For example: order number, user ID, etc. in the order table.
3. Combined index: When multiple conditions need to be queried at the same time, combined indexes can be used to improve query efficiency. For example: user ID and order status in the orders table.

3. Create an index
Creating an index in MySQL is very simple and can be achieved using the CREATE INDEX statement. Here is some sample code:

1. Create a single column index:
   CREATE INDEX idx_username ON users (username);
2. Create a combined index:
   CREATE INDEX idx_user_status ON orders ( user_id, status);

4. Index optimization skills

1. Avoid too many indexes: Each index needs to occupy storage space and needs to be maintained when the data is updated. index. Excessive indexes not only waste storage space but also increase data update time.
2. Avoid using SELECT : If you only need to query the data of a certain column, do not use SELECT . This can reduce the number of indexes used.
3. Use covering index: When the query statement only needs to obtain the required column data from the index, you can use the covering index to avoid querying table data and further improve query efficiency. For example: SELECT user_id FROM users WHERE username = 'abc'.
4. Adjust index order: In a combined index, the order of index columns also affects query efficiency. Generally speaking, placing highly selective columns at the front can improve the efficiency of the index.
5. Optimize the index regularly: As data is added and updated, the performance of the index may decrease. Regularly using the OPTIMIZE TABLE command for index optimization can improve query results.

5. Actual Case
Suppose there is a product table product, containing the following fields:

CREATE TABLE product (

id INT PRIMARY KEY,
name VARCHAR(100),
category VARCHAR(50),
price DECIMAL(10,2),
create_time DATETIME

);

We can create indexes on the name, category and create_time fields respectively. The sample code is as follows:

CREATE INDEX idx_name ON product (name);
CREATE INDEX idx_category ON product (category);
CREATE INDEX idx_create_time ON product (create_time);

When querying products with a price lower than 100 in a certain category, you can improve query efficiency by combining indexes. The sample code is as follows:

SELECT *
FROM product
WHERE category = 'mobile phone'

AND price < 100;

The above code can optimize query efficiency by creating a combined index. The sample code is as follows:

CREATE INDEX idx_category_price ON product (category , price);

6. Summary
Index is one of the important optimization methods in MySQL. Correct index design can significantly improve query efficiency. Choosing appropriate index columns, creating appropriate types of indexes, and optimizing according to actual conditions are all keys to improving database performance. Through the introduction and code examples of this article, I hope it can help readers better understand and apply index optimization techniques.

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