MySQL is a commonly used relational database management system, and indexes are crucial for optimizing the performance of database queries. However, sometimes it is found that even if an index is built, the query is still very slow. At this time, it is necessary to consider the cause of index failure and perform corresponding optimization. Among them, in query may be one of the common causes of index failure.
1. In query
In query is a commonly used query method in MySQL, which can match multiple values or multiple ranges in one query. For example:
SELECT * FROM table WHERE col1 IN (1,2,3);
This SQL statement will find all rows in the col1 column that are equal to 1, 2, or 3. During the processing of the in query, MySQL will compare each value in the brackets with the index, so the in query will have a certain impact on the efficiency of the index.
2. Reasons for index failure
When the query range is too large, MySQL will consider that the full table scan ratio is passed Indexes are more efficient to find data. For example, there are 100,000 records in a table, and if the query range exceeds more than 25% of the records, MySQL will choose a full table scan instead of using the index for query. Therefore, if the query range is too large, it may cause index failure.
In the in query, if there are too many values to match, MySQL will think that a full table scan is more time-consuming than finding the data through the index. To be efficient. At this time, the meaning of indexing is not great. Therefore, when using in queries, you should try to reduce the number of matching values as much as possible.
3. Optimization method
Reduce the scope of the query and the number of values that need to be matched as much as possible. You can use the following methods Methods to optimize query statements:
a. Optimize the where condition of the query, use AND logical connectors as much as possible, and reduce the use of OR logical connectors.
b. Use range query instead of in query. For example, use BETWEEN and AND operators instead of IN.
c. Reduce the value list in the in query as much as possible and use subqueries to optimize it. For example:
SELECT * FROM table WHERE col1 IN (SELECT col1 FROM table WHERE col2='xxx');
When creating a table, set the columns that need to be queried as index columns, which can improve the efficiency of the query and reduce the number of in queries as much as possible. use.
4. Summary
The index is a very important part of MySQL query optimization, but when a large number of in queries are used, the index may fail. By optimizing query statements and using correct indexes, index failure problems can be avoided and reduced to the greatest extent. It is worth mentioning that the effect of the index is also affected by many other factors, such as table size, field type, sorting method, etc. Therefore, in actual query optimization, reasonable optimization needs to be carried out according to the specific situation.
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