Principles of MySQL Database Schema Optimization
Jul 05, 2025 am 01:49 AM
MySQL database performance optimization should start with schema design. First, select the appropriate data type, such as using TINYINT instead of INT to represent the status, avoid abuse of TEXT/BLOB types, and use DATETIME and TIMESTAMP reasonably; second, use indexes reasonably, avoid indexing in low-base sequences, pay attention to the joint index order, regularly analyze SQL execution plans and clean up invalid indexes; third, balance the standardization and anti-standardization of table structure, appropriate redundancy reduces JOIN operations, but the application layer needs to maintain consistency; finally, unified naming specifications improve maintainability, such as using clear table names, field names and foreign key naming rules.
The performance optimization of MySQL databases often starts with architecture design. The design of schema is the most critical part. A reasonable table structure, field type and index settings can significantly improve query efficiency and reduce resource consumption. Don’t wait until the data volume is expanded before making up for it. Designing the schema from the beginning is the long-term solution.
Select the right data type
Many people habitually use VARCHAR(255) or INT when defining fields, but in fact, each field should choose the most appropriate data type based on the actual stored content.
- Smaller data types mean faster access speeds : for example, using
TINYINTinstead ofINTto represent state values ??not only saves space, but also improves I/O efficiency. - Avoid overuse of
TEXTorBLOBtypes : These types of fields usually place data outside the row, adding additional IO overhead. Unless you really need to store large pieces of text or binary data, try to useCHARorVARCHARas much as possible. - Time types should be distinguished for use :
DATETIMEis suitable for recording absolute time points, whileTIMESTAMPis affected by the time zone and has a small range, but it can be automatically updated in some scenarios.
Use indexes reasonably to avoid abuse
Indexing is a powerful tool to improve query efficiency, but the more you add, the better. Indexes affect writing speed and take up additional storage space.
Common misunderstandings include:
- Indexing on low cardinality sequences (such as gender)
- Ignore the order of joint indexes
- Slow query logs are not analyzed regularly, resulting in invalid index pileup
Suggested practices:
- Index fields that often appear in
WHERE,JOIN,ORDER BY - When using joint index, pay attention to the leftmost matching principle
- Regularly use
EXPLAINto analyze SQL execution plans to see if the expected index hits - Delete long-lasting unused indexes and release resources
The balance between table structure normalization and anti-normative
Although the database theory emphasizes normalized design, in practical applications, moderate anti-normatives can sometimes lead to better performance.
For example:
- In systems with more reads and less writes, appropriate redundancy of commonly used fields can reduce JOIN operations
- For some static configuration information, it can be directly embedded in the main table instead of creating table associations separately
However, it should be noted that the benefits of anti-specification come from the expense of consistency, and at this time, it is necessary to cooperate with application layer logic to maintain data synchronization.
Naming specifications and maintainability
Although it does not affect performance, good naming specifications are very important for subsequent maintenance and teamwork.
- Table names and field names should clearly express the meaning to avoid abbreviation ambiguity.
- Use underline styles uniformly, such as
user_profile,created_at - Foreign key fields are best ended with a reference table name, such as
order_user_idcomes from theusertable
In this way, even if the substitution takes over, the structural intention can be quickly understood and the probability of errors can be reduced.
Basically, these key points are not complicated but are easily overlooked. If you spend more time designing a schema, the time spent on a lot of investigation and reconstruction may be saved.
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