How to control MySQL execution plans with hints?

In MySQL, you can use query hints to provide suggestions or directives to the query optimizer about how to generate the execution plan for a specific query. Query hints allow you to have more control over the execution plan and potentially optimize the query’s performance. However, it’s important to note that query hints should be used judiciously and only when necessary, as the query optimizer is generally proficient at generating efficient execution plans on its own.

MySQL supports two types of query hints: optimizer hints and index hints.

Optimizer Hints:

  • STRAIGHT_JOIN: Forces the optimizer to join the tables in the order specified in the query.
  • SQL_NO_CACHE: Instructs MySQL to not cache the query result and retrieve it fresh from the underlying tables.

Example usage:

SELECT STRAIGHT_JOIN column1, column2
FROM table1, table2

Index Hints:

  • USE INDEX(index_name): Suggests using a specific index when executing the query.
  • FORCE INDEX(index_name): Forces the query to use a specific index, even if the optimizer believes another index would be more appropriate.
  • IGNORE INDEX(index_name): Instructs the optimizer to ignore a specific index.

SELECT column1, column2
FROM table1 USE INDEX (index_name)
WHERE column3 = 10;

It’s important to note that query hints can have unintended consequences if used improperly. The query optimizer is generally efficient at choosing the best execution plan based on statistics and available indexes. It’s recommended to thoroughly test and benchmark queries with and without hints to ensure that they indeed improve performance.

Also, keep in mind that query hints can vary depending on the MySQL version, and some hints may have limited or no effect. It’s advisable to consult the MySQL documentation for the specific version you are using to understand the available query hints and their usage details.


While MySQL query hints offer DBAs a way to influence execution plans and potentially enhance performance, they should be used sparingly and with caution. The MySQL query optimizer is adept at generating efficient execution plans based on statistics and available indexes. Testing and benchmarking are crucial to verify the actual impact of query hints on performance.

About Shiv Iyer 452 Articles
Open Source Database Systems Engineer with a deep understanding of Optimizer Internals, Performance Engineering, Scalability and Data SRE. Shiv currently is the Founder, Investor, Board Member and CEO of multiple Database Systems Infrastructure Operations companies in the Transaction Processing Computing and ColumnStores ecosystem. He is also a frequent speaker in open source software conferences globally.