How to avoid common database errors and problems through MySQL design conventions? A must-have experience summary for technical students!

How to avoid common database errors and problems through MySQL design conventions? A must-have experience summary for technical students!

Abstract:
MySQL is a widely used relational database management system. However, in actual applications, due to improper design, configuration problems or improper use, a series of database errors and question. This article summarizes some common MySQL database errors and problems, and proposes targeted design protocols to help technical students avoid these errors and problems and improve database performance and stability.

Introduction:
In modern software development, databases play a vital role, and MySQL, as a common and powerful relational database management system, is widely used in various Web applications in programs and enterprise-wide systems. However, due to the complexity and flexibility of MySQL, some common database errors and problems can easily occur. This article will introduce some common MySQL database errors and problems, and provide some design rules to help technical students avoid these problems and make their database more robust and efficient.

1. Data type selection error
When designing a database, it is crucial to choose the appropriate data type. Wrong data type selection can lead to a waste of data storage space and reduced query performance. The following are some common data type selection errors and conventions:

1. Use INT to store IP address: The IP address is a 32-bit unsigned integer, so it can be stored using UNSIGNED INT instead of VARCHAR or CHAR type.
2. Use VARCHAR to store fixed-length data: If the length of a field is fixed, the CHAR type should be used instead of the VARCHAR type. The VARCHAR type requires additional storage space to record the length of the string, while the CHAR type uses fixed storage space.
3. Use TEXT or BLOB to store smaller text or binary data: If the length of a field does not exceed a certain range, it should be stored using the appropriate VARCHAR type and avoid using the TEXT or BLOB type. TEXT or BLOB types require special handling and additional storage space.

2. Lack of index or wrong index selection
Good index design can greatly improve query performance, while lack of index or wrong index selection will lead to a decrease in query performance. Here are some common index design mistakes and conventions:

1. Lack of primary key or use of inappropriate primary key: Each table should have a primary key that uniquely identifies each row of data. The primary key should be a unique, short, static and immutable field, and avoid using auto-incrementing ID as the primary key.
2. Wrong index selection: When designing indexes, you should select fields that are frequently used for filtering and join queries. Avoid creating indexes on fields with high update frequency, and avoid creating indexes on smaller tables or fields.
3. Lack of index statistics update: In MySQL, index statistics are an important basis for optimizing query plans. Therefore, index statistics should be updated regularly to ensure query plan accuracy and performance.

3. Excessive use of subqueries
Subquery is a powerful query technology, but excessive use of subqueries will lead to a decrease in query performance. The following are some common mistakes and conventions about subqueries:

1. Multiple levels of nested subqueries: Avoid multiple levels of nested subqueries, especially in the case of large data volumes. Subqueries can cause severe performance degradation.
2. Unnecessary subqueries: In some cases, a simpler, more efficient join query can be used instead of a subquery. Each subquery should be evaluated for necessity and unnecessary subqueries should be avoided.
3. Use EXISTS instead of IN: In some cases, using EXISTS subquery can be more efficient than IN subquery. The EXISTS subquery only cares about whether there are records that meet the conditions, while the IN subquery will load the result set into memory for comparison.

4. Lack of data validation and constraints
Good data validation and constraints can ensure the integrity and consistency of data and avoid dirty data and incorrect query results. The following are some conventions about data validation and constraints:

1. Use NOT NULL constraints: For fields that cannot be null, NOT NULL constraints should be added explicitly. This can avoid data anomalies caused by inserting null or NULL values.
2. Use UNIQUE constraints: For fields that require uniqueness, UNIQUE constraints should be added. This ensures the uniqueness of data and avoids insertion and query errors of duplicate records.
3. Use foreign key constraints: When related queries involving multiple tables, appropriate foreign key relationships should be defined and foreign key constraints added. Foreign key constraints can ensure the integrity of associated data and avoid erroneous query results and inconsistent data.

Conclusion:
By following the design protocols mentioned above, technical students can help avoid common MySQL database errors and problems and improve the performance and stability of the database. When designing a database, you should choose data types wisely, design indexes correctly, avoid excessive use of subqueries, and add appropriate data validation and constraints. Not only that, database performance optimization and maintenance work should also be carried out regularly to ensure the normal operation of the database. Through continuous accumulation of experience and summary, technical students can become experts in MySQL database design and optimization, providing strong support for the company's business development.

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