Optimizing SQL Queries with the EXPLAIN Statement

The EXPLAIN statement in SQL is a powerful diagnostic tool that helps you understand and optimize your database queries, especially in relational databases like MySQL.

By using EXPLAIN, you can see how your queries interact with your tables, which indexes are used, and the estimated costs of each operation. Understanding the output of EXPLAIN is essential for improving query performance and ensuring your application runs smoothly.

In this article, we’ll break down how to use EXPLAIN, go through each part of the output in detail, and provide examples of how to optimize different types of queries.

How to Use the EXPLAIN Statement

Add the word EXPLAIN at starting of the query

explain SELECT * FROM movies_live WHERE id=567;

This command will output a table of information describing how the database intends to execute the query. Each part of this table reveals how MySQL plans to retrieve data, including details about tables, joins, indexes, and filters.

Output

Understanding the Columns in EXPLAIN Output

• id
  • Represents the order of execution. Higher id values are executed after lower values.
  • If multiple queries are executed (for example, with a union), each will have its own id.
• select_type
  • Describes the type of query (e.g., SIMPLE, PRIMARY, UNION, SUBQUERY).
  • Common values include:
    • SIMPLE: A simple SELECT without any subqueries or unions.
    • PRIMARY: The outermost query in a subquery.
    • UNION: Part of a UNION query.
    • DEPENDENT SUBQUERY: A subquery that depends on the outer query.
• table
  • The table being referenced by the row.
• partitions
  • If the table is partitioned, this column will show the relevant partitions.
  • Displays NULL if there are no partitions involved.
• type
  • Indicates the type of join used in the query, affecting performance:
    • ALL: Full table scan (least efficient).
    • INDEX: Full index scan.
    • RANGE: Index range scan.
    • REF: Indexed join.
    • EQ_REF: Exact match join (very efficient).
    • CONST: Querying a constant value (fastest).
    • NULL: No access necessary (e.g., due to optimization).
• possible_keys
  • Lists the indexes the query could potentially use.
  • Allows you to assess if the correct indexes are in place for optimizing the query.
• key
  • The actual index used by the query.
  • If NULL, no index is used, which may indicate a performance issue.
• key_len
  • The length of the key used.
  • Helpful to ensure the database uses as few bytes as possible, as excessive length can slow down queries.
• ref
  • Shows which column or constant is compared to the index.
  • Useful to understand how indexes are used to optimize the query.
• rows
  • Estimated number of rows examined to execute the query.
  • Lower values indicate better performance, though this isn’t always precise.
• filtered
  • Percentage estimate of rows filtered by conditions in the WHERE clause.
  • The closer to 100%, the more selective the condition.
• Extra
  • Additional information about the query execution.
  • Common values include:
    • Using index: The query only uses the index to retrieve columns, which is optimal.
    • Using where: The WHERE clause filters the rows.
    • Using temporary: Temporary tables are used, which may slow down the query.
    • Using filesort: Indicates sorting using an extra operation, often a sign the query could be optimized.

Example

Query 1

EXPLAIN SELECT * FROM orders WHERE order_id = 100;

Output

Query 2

EXPLAIN SELECT o.order_id, c.customer_name 
FROM orders o 
JOIN customers c ON o.customer_id = c.customer_id
WHERE o.order_date > '2024-01-01';

This might output:

Optimizing SQL Queries with the EXPLAIN Statement

Optimizing SQL queries is essential for maintaining a fast and efficient database. When you analyze queries with the EXPLAIN statement, the insights gained can reveal areas to target for optimization. Here, we’ll dive into some best practices and techniques for optimizing queries based on common issues revealed by EXPLAIN.

Conclusion

Query optimization is a crucial skill for ensuring database performance. By using EXPLAIN, you can identify bottlenecks such as full table scans, unnecessary sorts, and inefficient joins. Addressing these issues through strategic indexing, limiting row processing, and avoiding redundant operations can drastically improve query speed. Following best practices and regularly analyzing your queries will keep your database fast and efficient, especially as your data grows.

Resources

• SQL Query Optimization
• Geeksforgeeks