How to optimize IN query statement in mysql

IN in MySQL is a very commonly used operator, which can be used to filter out data that meets specified conditions, such as:

SELECT * FROM example_table WHERE id IN (1, 2, 3);

This SQL statement will return rows with IDs 1, 2, and 3 in the example_table table. When the amount of data is small, the efficiency of IN is very high, but when the amount of data becomes very large, the efficiency of IN will decrease significantly. This article will explain the problems and solutions of the IN query method when the amount of data is particularly large from the following three aspects.

1. When will the efficiency of using IN decrease?

1. There are too many elements following IN

When there are a large number of elements following IN, the query efficiency will decrease significantly. The reason is that MySQL needs to convert all elements following IN into a temporary table, and then perform a JOIN operation with the queried table. When the number of elements following IN is large, the size of the temporary table will become very large, resulting in a decrease in query efficiency.

2. IN query does not use the index

When the number of elements after IN is large, MySQL may choose not to use the index and use a full table scan to query , which will significantly reduce query efficiency.

3. IN query will produce file sorting results

When the number of elements following IN is large, MySQL will save the results in the disk and then sort the files. This This method will also greatly reduce query efficiency.

2. How to optimize queries using IN?

1. LIMIT statement

When the result set returned in the IN query is large, we can consider using the LIMIT statement to limit the result set to an appropriate range. This avoids low query efficiency.

2. UNION statement

Split the large data set into multiple small data sets, and then use the UNION statement to perform combined queries.

3. Paging query

When the result set returned in the IN query is large, we can consider using paging query for optimization, which allows us to optimize during the query process Only the required data is returned.

4. Using EXISTS

When there are very few elements in the IN query, we can consider using the EXISTS operator instead of the IN operator to query, which can effectively improve query efficiency.

5. Cache data

When IN queries are frequently used, we can consider caching them, which can reduce the number of repeated queries and thus improve query efficiency. .

3. Summary

IN query is a very commonly used operator that can help us quickly filter out data that meets the conditions. However, when the amount of data is particularly large, the efficiency of IN query will decrease significantly, and we need to optimize it through some optimization methods. We can improve the efficiency of IN queries by using LIMIT statements, UNION statements, paging queries, using the EXISTS operator, caching data, etc.

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