Under what circumstances will mysql index fail?

mysql index does not use index columns for query, data type mismatch, improper use of prefix index, use of functions or expressions for query, incorrect order of index columns, frequent data updates and too many indexes or It will fail if it is too little. 1. Do not use index columns for queries. In order to avoid this situation, you should use appropriate index columns in the query; 2. Data types do not match. When designing the table structure, you should ensure that the index columns match the data types of the query; 3. , Improper use of prefix index, you can use prefix index.

The operating environment of this tutorial: windows10 system, mysql8.0.16 version, DELL G3 computer.

MySQL indexes may fail under certain circumstances, resulting in reduced query performance. Here are some common situations:

1. Query without using index columns: If no index columns are used in the query, MySQL will not be able to use the index to optimize the query, so the efficiency of the query may be lower. To avoid this situation, appropriate index columns should be used in the query.

2. Data type mismatch: If an index column is used in a query but the data type does not match, MySQL will not be able to use the index effectively. For example, compare a string type column to a numeric type, or a date type column to text. When designing the table structure, you should ensure that the data types of the index columns and queries match.

3. Improper use of prefix index: In some cases, in order to improve the efficiency of the index and save storage space, prefix index can be used. However, if the length of the prefix index used is too short, the results of the query may be inaccurate. In addition, if the columns of the prefix index are used for sorting or grouping operations, the index will also become invalid.

4. Use functions or expressions to query: If functions or expressions are used in the query, MySQL will not be able to use the index to optimize the query. For example, select * from table where year(date_column) = 2021; In this case, the index on date_column will not be used.

5. Index columns are in incorrect order: A composite index is an index that contains multiple columns. If the order of the columns in the query's conditions is inconsistent with the order of the columns of the composite index, MySQL will not be able to use the index to optimize the query. Therefore, when building a composite index, you should sort according to the most commonly used columns in the query conditions.

6. Frequent data updates: Indexes are created to improve query performance, but when data is frequently updated, indexes can cause performance degradation in insert, update, and delete operations. Therefore, when designing the table structure, you need to weigh the frequency of queries and updates, and determine whether to create an index based on the actual situation.

7. Too many or too few indexes: If a table has too many indexes, query performance may suffer. Each index requires additional storage space, and index consistency needs to be maintained when data is updated. On the other hand, if there are not enough indexes in the table, some queries may become very slow. Therefore, it is necessary to choose indexes reasonably when designing the table structure.

In short, in order to ensure the effective use of MySQL indexes, you should pay attention to data type matching, correct selection of index columns, avoid using functions or expressions for queries, pay attention to the order of compound indexes, reasonably select the number of indexes, and according to Data read and write characteristics for index optimization .

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