Data normalization methods in MySQL

MySQL is a widely used relational database management system. In order to achieve efficient, reliable and secure management of data, certain data standardization methods must be adopted. This article will introduce the data normalization method in MySQL, including what normalization is, the purpose of normalization, the level of normalization, how to normalize, etc.

1. What is standardization?

Standardization refers to adjusting the design of the data table so that the data table meets certain standards. Through standardization, redundant data can be eliminated, the data storage space utilization of the data table can be improved, the structure of the data table can be ensured to be concise and clear, and the efficiency of data processing can be improved.

2. The purpose of normalization

The purpose of normalization is to optimize the design of the database so that the database has excellent scalability, reliability and flexibility, and can ensure data consistency and integrity. At the same time, it can also reduce the storage of duplicate data, improve data retrieval speed, and reduce database maintenance costs.

3. Levels of normalization

The levels of normalization are from one to five, which are called first normal form (1NF), second normal form (2NF), third normal form (3NF), and Coder normal form (BCNF) and fourth normal form (4NF). The data table structures corresponding to different levels of normalization reflect different characteristics.

1. First Normal Form (1NF)

The first normal form is the most basic form of normalization. It requires that all attributes of each record must be indivisible basic data items. That is, any data item cannot be split into smaller data items.

2. Second Normal Form (2NF)

The second normal form is a further restriction of the first normal form. It requires that all non-keyword attributes in the data table must depend on on the primary key. That is to say, in a relationship, if an attribute only depends on some attributes of the primary key, it needs to be separated from the relationship and form a new relationship separately.

3. Third Normal Form (3NF)

In the third normal form, any non-keyword attribute cannot depend on other non-keyword attributes. That is, every non-primary attribute must directly depend on the primary key. If a non-primary attribute depends on other non-primary attributes, it needs to be separated into different relationships to ensure that each relationship table is clear and unambiguous.

4. Bus-Code Normal Form (BCNF)

BCNF is proposed based on the third normal form. If every relationship in a database table satisfies BCNF, there is no data redundancy in the table.

5. Fourth Normal Form (4NF)

The fourth normal form ensures the atomicity of data for storing complex data types, such as multi-valued dependencies, arrays, structures and other data types. sex.

4. How to standardize

1. Analyze the attributes in the data table

First of all, unnecessary data needs to be screened and filtered. Remove unnecessary attributes and redundant attributes to optimize the data table.

2. Eliminate duplicate data

For duplicate data, you can consider creating a separate table to store the data to eliminate data redundancy.

3. Normalized expression

Generally speaking, a table should only contain one actual data entity. For different entities, different tables should be created respectively.

4. Design appropriate relationships

When normalizing data, you need to design appropriate relationships. If you store data directly in a table, the table structure will be complicated and the data access efficiency will be reduced. Dividing multiple attributes into multiple tables for storage can eliminate redundant data and improve table access efficiency.

In short, data normalization is a very important task. For the standardized processing of data, it is necessary to refer to some basic principles and standards in the industry, comprehensively consider the actual situation and needs of DBAs, database administrators, etc., and continuously improve the standardized standards of the database system to ensure the management efficiency and data quality of the database management system. and data security.

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