How to implement MySQL underlying optimization: data type selection and storage space optimization

MySQL is a widely used relational database management system, and its underlying optimization is crucial to the performance and stability of the database. This article will introduce MySQL data type selection and storage space optimization in detail, and give practical code examples.

1. Data type selection and optimization

1. Introduction to common data types

MySQL supports multiple data types, including integer, floating point, string, Date type, time type, etc. When selecting a data type, you should select it based on actual needs to avoid wasting storage space and affecting query efficiency.

2. Integer type

Integer type is one of the most common data types in MySQL and is usually used to store quantities or counters. When choosing an integer type, you should choose it based on the range and precision of the stored data, and avoid using an integer type that is too large or too small.

Common integer types include:

• TINYINT: range is -128 ~ 127, one byte.
• SMALLINT: The range is -32768 ~ 32767, two bytes.
• MEDIUMINT: The range is -8388608 ~ 8388607, three bytes.
• INT: The range is -2147483648 ~ 2147483647, four bytes.
• BIGINT: The range is -9223372036854775808 ~ 9223372036854775807, eight bytes.

3. Floating point type

Floating point type is used to store decimals, usually used to store monetary amounts, ratios, etc. When choosing a floating-point type, you should choose based on precision and storage space, and avoid using floating-point types that are too large or too small.

Common floating-point types include:

• FLOAT: single-precision floating-point type, occupies four bytes, and has a precision of 6 bits.
• DOUBLE: double-precision floating point type, occupies eight bytes, and has a precision of 15 bits.
• DECIMAL: High-precision floating point type, occupying a fixed length of storage space. The precision and storage space can be flexibly selected according to actual needs.

4. String type

The string type is used to store string data, usually used to store text information such as names, addresses, descriptions, etc. When selecting a string type, you should choose based on the size and type of stored data to avoid wasting storage space by using unnecessary character sets and lengths.

Common string types include:

• CHAR: fixed-length string, occupying fixed-length storage space, suitable for fixed-length data.
• VARCHAR: Variable-length string, occupying variable-length storage space, suitable for data with variable length.
• TEXT: Used to store larger length text data, generally using the utf8mb4 character set.
• BLOB: used to store binary data, generally using storage space.

5. Date type

The date type is used to store date and time data, usually used to store birthdays, entry dates, operating times, etc. When choosing a date type, you should choose it based on actual needs and avoid using unnecessary formats and time zones.

Common date types include:

• DATE: used to store date data in the format of "YYYY-MM-DD".
• TIME: used to store time data in the format of "HH:MM:SS".
• DATETIME: used to store date and time data in the format of "YYYY-MM-DD HH:MM:SS".
• TIMESTAMP: Used to store standard time and time zone, in the format of Greenwich Mean Time.

6. Stored procedures

In MySQL, stored procedures are one of the important methods to improve database performance and security. Stored procedures can reduce network transmission data, reduce database server load, improve security, etc.

For example, the following is a simple stored procedure to query information about employees whose scores are greater than 90 points:

CREATE PROCEDURE get_employee_score()
BEGIN

DECLARE score INT;
SELECT score INTO score FROM employee WHERE score > 90;
SELECT * FROM employee WHERE score = score;

END ;

2. Storage space optimization

1. Choose the appropriate storage engine

MySQL supports a variety of storage engines, such as InnoDB, MyISAM, Memory, etc. Different storage engines support different features and optimization strategies. The appropriate storage engine should be selected based on actual needs to achieve the best performance.

2. Avoid excessive indexing

MySQL index is one of the important tools to improve query performance and speed up data retrieval. However, over-indexing wastes storage space, reduces write performance, and causes index failure. Necessary indexes should be selected based on actual needs to avoid excessive indexing.

3. Use compressed tables

After MySQL 5.7, the compressed table function is supported, which can compress data and indexes to reduce storage space and improve performance. When selecting a compression table, you should select it based on actual needs to avoid performance degradation caused by excessive compression.

The following is a simple compressed table example:

CREATE TABLE members (

`id` INT(11) NOT NULL AUTO_INCREMENT,
`name` VARCHAR(25) NOT NULL,
`address` VARCHAR(50) NOT NULL,
`email` VARCHAR(50) NOT NULL,
PRIMARY KEY (`id`)

) ENGINE=InnoDB ROW_FORMAT=COMPRESSED KEY_BLOCK_SIZE=4;

4. Delete unnecessary data

Unnecessary data in MySQL includes unused tables and columns, useless indexes, expired data, etc. This unnecessary data takes up storage space, reduces database performance, and increases the complexity of backup and recovery operations. Unnecessary data should be deleted regularly to improve database performance and efficiency.

For example, the following is a simple deletion example for deleting employee information with a score of 0:

DELETE FROM employee WHERE score = 0;

Conclusion

Through reasonable selection of data types and storage space optimization, the performance and efficiency of the MySQL database can be greatly improved. It is recommended to regularly check and optimize the database structure, avoid using data types that are too large or too small, delete unnecessary data, and use optimization strategies such as compressed tables and stored procedures.

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