


PHP and MySQL index failure situations and how to avoid and solve them
Invalid situations of PHP and MySQL indexes and how to avoid and solve them
Introduction:
When developing web applications, PHP and MySQL are often commonly used programming Languages and databases. When processing large amounts of data, indexing is one of the important factors to improve query performance. However, index failure can cause queries to slow down, impacting application performance. This article aims to introduce the failure of PHP and MySQL indexes, and provide some practical solutions and avoidance measures.
1. What is index failure
Index failure means that during the query operation, MySQL does not use the index, but performs a full table scan. When the index becomes invalid, the efficiency of the query is greatly reduced, thus affecting the performance of the application. Index failure usually occurs in the following situations:
1. Index fields are not used as query conditions
When the index fields are not specified as query conditions in the query statement, MySQL cannot use the index for fast data search. , but only a full table scan can be performed, resulting in low query efficiency.
2. Function operations are performed on the index fields
If function operations are performed on the index fields in the query statement, such as using MySQL functions or PHP functions to process the index fields, then MySQL will not be able to use the index When querying, it will be converted to a full table scan.
3. The relationship between the index column and the query condition does not match
When the index column does not completely match the query condition in the query statement, MySQL cannot use the index for query, but can only perform a full table scan. For example, when the index column is of integer type and the query condition is of string type, or vice versa, the index column does not match the query condition type, and the index cannot be used, resulting in index failure.
2. How to avoid index failure
In order to avoid index failure, we can take the following measures:
1. Select the index column correctly
When designing the database, you need to according to the application The program's query requires the correct selection of index columns. Normally, the index should select fields that are frequently queried, such as ID, date, user name, etc. Avoid creating indexes on fields that are not queried frequently to avoid unnecessary overhead.
2. Avoid using functions in query conditions
In query statements, try to avoid performing function operations on index fields. If you must use functions, consider processing query results in your application code rather than in MySQL.
3. Use the correct data type
Ensure that the index column matches the data type of the query condition, and avoid using fields of different data types for index queries. For string type query conditions, you can consider using prefix indexes.
3. How to solve index failure
When index failure occurs, we can take some of the following solutions:
1. Optimize the query statement
By analyzing the query statement, see whether There are reasons for index failure and corresponding optimization should be carried out. You can add or modify indexes, adjust query conditions, etc. to improve query efficiency.
2. Use forced index
In some special cases, we can force MySQL to use a specified index for querying by using a forced index (FORCE INDEX). However, be aware that excessive use of forced indexes may cause other performance issues, so it needs to be used with caution.
3. Redesign the database schema
If the index failure problem persists for a long time, it may be necessary to redesign the database schema. You can consider measures such as splitting the table and adding caching strategies to improve application performance.
Conclusion:
Index failure is an important issue affecting database query performance, and more attention needs to be paid when developing Web applications. This article introduces the failure of PHP and MySQL indexes, and provides some practical solutions and avoidance measures. By correctly selecting index columns, avoiding the use of functions, using correct data types and other measures, you can effectively avoid the problem of index failure. When index failure occurs, it can be solved by optimizing query statements, using forced indexes, and redesigning the database architecture. With proper index design and optimization, application performance and user experience can be improved.
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