PHP study notes: database optimization and index design
PHP study notes: Database optimization and index design
When developing Web applications, database operation is a very critical link. Database performance directly affects the response speed and user experience of web applications. In order to improve the efficiency and query speed of the database, we need to perform database optimization and index design.
1. Database optimization
-
Database architecture optimization:
- Formalized design: follow the database paradigm and reduce redundant data.
- Split tables and databases: Split data into different tables and databases according to certain rules to reduce the amount of data in a single table.
- Vertical split and horizontal split: Split a large table into multiple tables, or split a large database into multiple small databases to improve query efficiency.
- Use views: Perform data query through views to reduce the pressure of complex queries on the database.
-
Query optimization:
- Avoid using character wildcards at the beginning of index columns: When using LIKE queries, try not to use % at the beginning of index columns wildcard, which causes the index to be invalid. Query conditions can be rewritten into a form suitable for indexing.
- Add reasonable indexes: According to business needs and query frequency, select the indexes that need to be added to avoid excessive index usage or index failure caused by too many indexes.
- Avoid using complex queries: Complex queries often lead to a decrease in database performance. Try to avoid using multiple levels of nested subqueries and multiple JOIN operations.
-
SQL optimization:
- Use batch operations: For the execution of multiple identical SQL statements, you can use batch operations to reduce interaction with the database frequency.
- Use prepared statements: Prepared statements can pre-compile SQL statements, reducing the performance loss of each SQL statement execution.
- Reduce deadlocks and long transactions: Reduce the occurrence of deadlocks and long transactions by rationally designing transactions to avoid affecting database performance.
2. Index design
Database index is an important means to improve query efficiency. Reasonable index design can speed up query speed and reduce database IO operations.
-
Common index types:
- Primary key index: used to uniquely identify a record, usually the primary key field of the table.
- Unique index: used to ensure the uniqueness of a field, which can speed up queries and restrictions on this field.
- Clustered index: The physical sorting of data in the table can speed up queries.
- Non-clustered index: The logical sorting of data in the table can speed up queries.
-
Index design principles:
- Choose appropriate fields as index fields: select fields with high query frequency and significant query effects as index fields. Avoid too many redundant indexes.
- Do not abuse indexes: Too many indexes will increase the storage space and maintenance costs of the database, and will also reduce the performance of insert and update operations.
- Joint index optimization query: For fields that are often queried together, you can consider creating a joint index to improve query efficiency.
- Update statistical information regularly: Statistical information includes the distribution of tables and indexes. Regularly updating statistical information can improve query performance.
Sample code:
- Create index
CREATE INDEX idx_username ON users(username);
- Use index
SELECT * FROM users WHERE username = 'admin';
- Joint index
CREATE INDEX idx_user_role ON user_roles(user_id, role_id);
SELECT * FROM user_roles WHERE user_id = 1 AND role_id = 2;
To sum up, database optimization and index design are important means to improve the performance of web applications. Through reasonable database architecture optimization, query optimization and index design, we can improve the efficiency and query speed of the database, and improve the response speed and user experience of web applications. At the same time, in actual development, optimization is carried out based on specific business needs and database characteristics to effectively reduce the load on the database and improve system stability and performance.
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