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How to realize MySQL underlying optimization: table design specifications and performance optimization techniques
In database management systems, MySQL is a commonly used relational database. During the development process, it is crucial to properly design the database table structure and optimize database performance. This article will introduce how to implement MySQL underlying optimization from two aspects: table design specifications and performance optimization techniques, and provide specific code examples.
1. Table design specifications
1. Choose the appropriate data type
When designing the table structure, you should choose the appropriate data type according to actual needs. For example, for fields that store integers, you should use the INT type instead of the VARCHAR type; for fields that store dates and times, you should use the DATE and TIMESTAMP types instead of the VARCHAR type. Avoiding the use of overly large or unnecessary data types can reduce database storage space usage and improve data access efficiency.
Example:
CREATE TABLE user ( id INT NOT NULL AUTO_INCREMENT, name VARCHAR(50) NOT NULL, age TINYINT UNSIGNED NOT NULL, birthday DATE, PRIMARY KEY (id) );
2. Reasonably design the table structure
When designing the database table structure, you should follow the principles of normalized design to avoid data redundancy and unnecessary fields . Proper use of primary keys, foreign keys and indexes can improve data query efficiency. At the same time, fields should be appropriately constrained and verified according to business needs to ensure data integrity and consistency.
Example:
CREATE TABLE order ( id INT NOT NULL AUTO_INCREMENT, user_id INT NOT NULL, amount DECIMAL(10, 2) NOT NULL, create_time TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP, PRIMARY KEY (id), FOREIGN KEY (user_id) REFERENCES user(id) );
3. Standardized naming convention
In order to improve the readability and maintainability of the code, certain naming conventions should be followed to name database tables and fields. , index and other objects. Usually use lowercase letters and underscores for names, and avoid using special characters and keywords.
Example:
CREATE TABLE product ( id INT NOT NULL AUTO_INCREMENT, name VARCHAR(100) NOT NULL, price DECIMAL(10, 2) NOT NULL, PRIMARY KEY (id) );
2. Performance optimization skills
1. Reasonable use of indexes
Indexes can speed up database queries, but too many indexes It will increase the overhead of data writing. Therefore, the fields that need to be indexed should be reasonably selected based on actual query needs, and unnecessary indexes should be avoided. In addition, the usage of indexes should be checked regularly, and indexes that have not been used for a long time should be deleted or rebuilt.
Example:
CREATE INDEX idx_user_name ON user(name);
2. Optimize query statements
For frequently executed query statements, optimization should be performed to reduce the query load of the database. Avoid using SELECT * to query all fields, but only select the required fields; avoid using functions in the WHERE clause and avoid calculations on columns, which can improve query efficiency.
Example:
SELECT id, name FROM user WHERE age > 18;
3. Use partitioned tables appropriately
For tables with large amounts of data, you can consider using partitioned tables to improve query efficiency. Partitioned tables can store table data in different partitions, thereby reducing the amount of data in a single query operation and improving query speed.
Example:
CREATE TABLE orders ( id INT NOT NULL AUTO_INCREMENT, user_id INT NOT NULL, amount DECIMAL(10, 2) NOT NULL, create_time TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP, PRIMARY KEY (id) ) PARTITION BY RANGE (TO_DAYS(create_time)) ( PARTITION p0 VALUES LESS THAN (TO_DAYS('2022-01-01')), PARTITION p1 VALUES LESS THAN (TO_DAYS('2022-02-01')), PARTITION p2 VALUES LESS THAN (TO_DAYS('2022-03-01')) );
In summary, through reasonable table design specifications and performance optimization techniques, the underlying optimization of the MySQL database can be achieved and the performance and stability of the database can be improved. In actual development, these optimization techniques should be flexibly applied according to specific business needs and data characteristics, and the database system should be continuously optimized and improved to improve the overall performance and stability of the system.
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