How to Use MySQL EXPLAIN for Query Performance Tuning

By 佐川 直弘 | Naohiro Sagawa (運営者)

※記事内に広告を含みます。Amazonアソシエイトとして適格販売により収入を得ています。　

1. Overview of MySQL EXPLAIN

MySQL’s EXPLAIN command is a crucial tool for analyzing query execution plans and providing optimization hints. Especially in large-scale database environments, optimizing queries significantly impacts overall performance.

What is EXPLAIN?

EXPLAIN visualizes how MySQL executes a query. This allows you to get detailed information about the query execution method, such as index usage, table scans, and join order.

Importance of EXPLAIN

Query optimization is essential for improving database performance. By using EXPLAIN, you can identify performance bottlenecks and create efficient queries. This leads to faster data retrieval and efficient utilization of server resources.

2. Basic Usage of MySQL EXPLAIN

This section explains the basic usage of the EXPLAIN command and how to interpret its output.

Basic EXPLAIN Usage

EXPLAIN is used by preceding the query you want to analyze. For example:

EXPLAIN SELECT * FROM users WHERE age > 30;

This command displays the query execution plan, allowing you to check index usage and whether table scans are performed.

Interpreting the EXPLAIN Output

The output includes columns such as:

 
• id: Identifier assigned to each part of the query

 

• select_type: Type of query (simple, subquery, etc.)

 

• table: Name of the table used

 

• type: Method of accessing the table (ALL, index, range, etc.)

 

• possible_keys: Indexes available for the query

 

• key: Index actually used

 

• rows: Estimated number of rows to be scanned

 

• Extra: Additional information (Using index, Using temporary, etc.)

You can use this information to evaluate the query execution efficiency and find areas for optimization.

3. Query Optimization Using EXPLAIN

We will explain how you can optimize queries using EXPLAIN.

Appropriate Use of Indexes

Indexes are essential for improving query performance. Use EXPLAIN to check if your queries are using indexes appropriately.

EXPLAIN SELECT * FROM orders USE INDEX (order_date_idx) WHERE order_date > '2024-01-01';

From this result, you can determine if the index is being used effectively or if an additional index is needed.

Minimizing Row Scans

The rows column in EXPLAIN shows the number of rows scanned by the query. A large number of scanned rows degrades performance, so it is important to minimize the number of rows by setting appropriate indexes.

4. Advanced Features of EXPLAIN

EXPLAIN has advanced features to analyze query execution plans in more detail.

Selecting Output Format

EXPLAIN provides output in the following formats:

 
• Traditional: Default tabular format

 

• JSON: JSON format containing detailed information (MySQL 5.7 and later)

 

• Tree: Displays the query execution structure in a tree format (MySQL 8.0.16 and later)

For example, you can specify the JSON format output as follows:

EXPLAIN FORMAT = JSON SELECT * FROM users WHERE age > 30;

This allows for a deeper analysis of the query execution plan details.

Real-time Query Analysis

By using EXPLAIN FOR CONNECTION, you can obtain the execution plan of a currently running query in real-time. This allows you to evaluate the load a specific query places on the database in real-time.

5. Practical Use Cases

Here, we introduce concrete examples of optimizing queries using EXPLAIN.

Analyzing Simple Queries

First, apply EXPLAIN to a simple query.

EXPLAIN SELECT * FROM employees WHERE department = 'Sales';

This result helps you check if an index is being used appropriately or if a full table scan is being performed.

Optimizing Complex Queries

Analyze the execution plan of a query that joins multiple tables.

EXPLAIN SELECT e.name, d.name FROM employees e INNER JOIN departments d ON e.department_id = d.id WHERE e.salary > 50000;

From this output, you can determine if the join order and index usage are optimal.

Visualizing Execution Plans

Visualize the query execution plan in a tree format.

EXPLAIN FORMAT = tree SELECT * FROM employees WHERE department = 'Sales';

Visual analysis in a tree format is very helpful for optimizing complex queries.

6. Best Practices for EXPLAIN

Here are some best practices for effectively using EXPLAIN.

Iterative Query Execution

Since query execution speed is affected by the cache state, when using EXPLAIN, execute the query multiple times to evaluate performance when the cache is warmed up.

Using in Conjunction with SHOW STATUS

By using the SHOW STATUS command to check the status after query execution, you can obtain detailed information such as the actual number of rows read and index usage, which can be helpful for optimization.

7. Common Issues and Misunderstandings

We will explain points to note when using EXPLAIN and common misunderstandings.

Difference Between EXPLAIN Estimates and Reality

The output of EXPLAIN is based on estimates by the MySQL optimizer, so it may differ from the actual query execution results. It is important not to over-rely on estimates and to check actual performance.

Over-reliance on Indexes and Their Effectiveness

Indexes are effective for improving query efficiency, but they are not a panacea in all cases. If there are too many indexes, overhead occurs during data insertion and updates. Also, if index usage is not appropriate, MySQL may ignore the index and choose a full table scan.

8. Conclusion

This article explained query analysis and optimization using MySQL’s EXPLAIN command.

Summary of Key Points

 
• Basic Usage: Use EXPLAIN to check the query execution plan and evaluate index usage and table access methods.

 

• Advanced Features: Detailed execution plan analysis is possible using JSON or Tree formats. Real-time query analysis allows evaluating the load of running queries.

 

• Best Practices: Considering the impact of caching, it is important to execute the query multiple times to evaluate stable execution time. Also, use SHOW STATUS to analyze the actual query execution results and help with optimization.

Next Steps for Query Optimization

Continuously optimize queries based on the results of EXPLAIN to improve overall database performance. This includes adding or modifying indexes, improving query structure, and reviewing table design.

Finally

The EXPLAIN command is a fundamental and powerful tool for database query optimization. By using it appropriately, you can improve query efficiency and optimize overall database performance. Please refer to the content introduced in this article for your daily database management and query optimization efforts. Query optimization is a continuous process and requires adjustments based on changes in database size and usage. Utilize EXPLAIN to aim for efficient database operation.