MySQL explain optimizes SQL statements based on query plans

Various applications often use MySQL to store data. MySQL is a common relational database management system. When a large amount of data is involved, the performance of database queries becomes a key factor. At this time, MySQL's explain function is needed to help optimize query statements.

1. What is MySQL explain

The MySQL explain tool is a tool used to analyze and optimize query statements. If you want to evaluate the performance of a query statement, you can use the explain command to view the MySQL execution plan. Through the explain command, you can obtain detailed information about query execution, such as the index used in the query, the connection method between tables, the execution steps, etc. With this information, you can optimize query statements and improve query performance.

2. How to use MySQL explain

You can easily use the explain function of MySQL by just adding the keyword explain before the query statement. For example, suppose we have the following query statement:

SELECT * FROM user WHERE name = '小明';

We can obtain the execution plan of the query through the following command:

EXPLAIN SELECT * FROM user WHERE name = '小明';

This command will return a table containing the query execution plan , where each row represents an execution step. The columns of the table include:

id: the unique identifier of each SELECT. If there is a subquery, there will be multiple id values.

select_type: Query type, common ones include Simple, Primary, Subquery, Derived, Union and Union Result.

table: The name of the table involved in the query.

partitions: Query the name of the partition involved.

type: join type, including system, const, eq_ref, ref, range, index and all.

possible_keys: Possible indexes to use.

key: The actual index used.

key_len: The length of the index used.

ref: The relationship between columns and indexes.

rows: Number of rows returned.

filtered: The number of rows returned as a percentage of the total number of rows.

Extra: Other additional information, such as which indexes are used, which algorithms are used, etc.

We can analyze the query execution plan to find out the performance problems in the query statement so that we can further optimize it. The following are some common performance problems and solutions:

• Unnecessary columns are used in the query statement

If the query statement uses Unnecessary columns will waste system resources and query time. In the query execution plan, this situation will usually appear as "using filesort" or "using temporary" information. The way to solve this problem is to try to only query the required columns and avoid querying unnecessary columns. You can use the column list in the SELECT clause to specify the columns that need to be returned by the query.

• The OR operator is used in the query statement

When using subqueries in the query statement, EXISTS and NOT EXISTS statements are also commonly used for optimization tool, they are generally more efficient than IN and NOT IN statements. Use the EXISTS statement to verify whether the subquery returns results, and use the NOT EXISTS statement to verify whether the subquery returns no results. The following is an example of using the EXISTS statement:

SELECT *
FROM orders o
WHERE EXISTS (
   SELECT 1
   FROM customers c
   WHERE o.customer_id = c.customer_id
   AND c.country = '中国'
);

This query returns all customer orders in China. If there are Chinese customers in the customer table, the subquery will return that row of data, otherwise nothing will be returned. By concatenating outer queries and subqueries using the EXISTS statement, unnecessary data can be filtered out.

Excessive subqueries will increase the execution time of the query. Special attention should be paid when using subqueries. When the subquery is deeply nested, the JOIN statement can be used to replace the subquery.

In addition to the previously mentioned techniques for optimizing queries, there are other ways to improve query performance. For example, use indexes, avoid using SELECT *, avoid using functions or wildcards. The appropriate optimization method needs to be selected based on the specific situation.

At the same time, if aggregate functions (such as SUM, AVG, COUNT, etc.) are used in the query statement, you can use the EXPLAIN EXTENDED statement to obtain more detailed information. Using the SHOW WARNINGS statement, you can view warning information generated by the query optimizer after executing the statement.

In the process of query optimization, you also need to pay attention to some common problems, such as:

• Avoid using SELECT * because it will query all columns, causing performance problems of waste.

• Avoid using subqueries as they may affect query performance.

• Using appropriate indexes can speed up queries.

• Avoid using functions in WHERE statements as it will invalidate the index.

In the MySQL database, optimizing query statements is crucial because it can significantly improve query efficiency and reduce system load. By using the EXPLAIN statement, you can understand the execution process of the MySQL optimizer and make corresponding adjustments and optimizations based on the query results to make the query more efficient.

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