A must-have MySQL design protocol for technical students to help you become a database optimization expert!

A must-have MySQL design protocol for technical students to help you become a database optimization expert!

With the rapid development of the Internet, large-scale data storage and efficient query have become the basis for the development of various industries. As one of the most popular relational databases, MySQL has powerful capabilities in data storage and query. However, to take full advantage of MySQL, we need to follow some design disciplines and optimization strategies. This article will introduce some necessary MySQL design specifications for technical students, and provide some code examples to help you become a database optimization expert.

The first rule: Reasonably select data types
MySQL supports multiple data types, such as integers, floating point numbers, characters, etc. When designing database tables, data types should be selected reasonably based on the actual needs of the data to avoid storage waste or insufficient storage caused by data types that are too large or too small. The following is an example:

CREATE TABLE users (
id INT(11) NOT NULL AUTO_INCREMENT PRIMARY KEY,
name VARCHAR(50) NOT NULL,
age TINYINT UNSIGNED NOT NULL,
email VARCHAR(100) NOT NULL
);

In the above example, for the user table users, id is an auto-incrementing primary key, and the INT data type is used, which is suitable for saving the user's unique identifier; name, age, email use appropriate character types and integer types to store the user's name, age, and email address.

The second rule: establishing appropriate indexes
Indexes are an important means to improve query performance. When designing database tables, appropriate indexes should be established based on query frequency and efficiency requirements. Too many or too few indexes will affect database performance. The following is an example:

CREATE TABLE orders (
id INT(11) NOT NULL AUTO_INCREMENT PRIMARY KEY,
user_id INT(11) NOT NULL,
order_date DATETIME NOT NULL,
status ENUM('paid', 'unpaid', 'cancelled') NOT NULL,
INDEX idx_user_id (user_id),
INDEX idx_status (status)
);

In the above example , the order table orders has established two indexes, user_id and status, to improve the efficiency of querying based on user ID and order status.

The third rule: avoid frequent use of fuzzy search
Fuzzy search (LIKE) is a convenient query method, but because it needs to match each character, the query efficiency is often low. Therefore, try to avoid using fuzzy search frequently, especially in tables with large data volumes. If you must use fuzzy search, you can consider using a full-text index (FULLTEXT INDEX) to improve query performance.

Article 4: Proper use of transactions
Transactions are an important concept in MySQL, which can ensure the atomicity, consistency, isolation, and durability of a set of operations. Using transactions can ensure data integrity and consistency when operating multiple tables or records concurrently. Here is an example:

START TRANSACTION;
INSERT INTO orders (user_id, order_date, status) VALUES (1, NOW(), 'unpaid');
UPDATE users SET last_order_date = NOW( ) WHERE id = 1;
COMMIT;

In the above example, use START TRANSACTION to start a transaction, then insert an order record and update the last order date of the user table, and finally use COMMIT to commit the transaction.

Article 5: Set up cache appropriately
MySQL provides a variety of caching mechanisms, such as query caching, key value caching, query result caching, etc. When designing and optimizing the database, set the cache strategy and cache size reasonably according to the characteristics and frequency of the query.

Summary:
MySQL is a powerful relational database. When designing and optimizing the database, we need to follow some regulations and strategies. Reasonable selection of data types, establishment of appropriate indexes, avoidance of frequent use of fuzzy searches, appropriate use of transactions, and reasonable setting of caches are all important means to improve database performance. Through the introduction and code examples of this article, I believe you can become an excellent database optimization expert!

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