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Table of Contents
Query cost model is the core mechanism
Index selection is not always "use if there is an index"
Optimizer tips and rewrite techniques
at last
Home Database Mysql Tutorial Understanding the MySQL optimizer's behavior

Understanding the MySQL optimizer's behavior

Jul 08, 2025 am 02:56 AM
mysql optimizer

The MySQL query optimizer selects the optimal execution plan based on statistical information. The core mechanism is a cost-based model (CBO), which estimates I/O and CPU costs to determine the execution path; 1. Execute ANALYZE TABLE regularly to ensure the accuracy of statistical information; 2. Indexes are not always used, such as querying large amounts of data or function operations may fail; 3. It is recommended to use EXPLAIN to view the execution plan, create overwrite indexes, and avoid implicit type conversion; 4. The optimizer can be booted through USE INDEX or FORCE INDEX, but be cautious; 5. Rewriting the SQL structure and controlling the connection order can also affect the optimization results. Mastering these logic and combining tool analysis can help to optimize efficiently.

Understanding the MySQL optimizer\'s behavior

MySQL's query optimizer is the key to efficient operation of databases. It is responsible for analyzing SQL statements and selecting an "optimal" execution plan to obtain data. Understanding its behavior can help you write more efficient queries, design more reasonable indexes, and even avoid detours when tuning.

Understanding the MySQL optimizer's behavior

Query cost model is the core mechanism

MySQL uses a cost-based optimizer (CBO), which means it estimates the cost of different execution paths based on statistics and then selects the least cost scheme. This cost mainly reflects the number of I/O and CPU operations.

Understanding the MySQL optimizer's behavior

For example: When you perform SELECT * FROM orders WHERE customer_id = 123 on a table, the optimizer will consider whether there is any index available, how the data is distributed, the size of the table, etc. to decide whether to scan the full table or use index search.

But it should be noted that this model relies on accurate statistics. If the index or table statistics are inaccurate, such as not doing ANALYZE TABLE for a long time, the optimizer may make a wrong decision.

Understanding the MySQL optimizer's behavior
  • Ensure regular execution of ANALYZE TABLE , especially large tables
  • If using InnoDB, note that its statistics are sampled and estimated, and may not be completely accurate

Index selection is not always "use if there is an index"

Many people think that as long as the index is created, the query will go through the index. In fact, the optimizer will determine whether it is worth indexing. For example:

  • When a query returns a large number of rows (such as more than 20% of data), the optimizer may give up the index and directly scan the full table, because frequent table reversion will be less efficient.
  • For some function operations, such as WHERE YEAR(create_time) = 2024 , the optimizer cannot effectively use the normal B-tree index.
  • If the index column participates in expression operations, it may also cause the index to fail.

Therefore, you cannot blindly believe that the existence of indexes can improve performance. suggestion:

  • Use EXPLAIN to view the actual execution plan
  • Try creating Covering Index to avoid backing tables
  • Pay attention to implicit type conversion problems, such as the mixing of strings and numbers may cause index failure

Optimizer tips and rewrite techniques

Sometimes the selection of the optimizer does not match expectations, and you can boot it in a few ways:

  • Use USE INDEX or FORCE INDEX to specify which index to use (use with caution)
  • Rewrite the SQL structure, such as breaking the OR into UNION, or rewriting the subquery to JOIN
  • Controlling the connection order: When multi-table association, it is usually faster to check the small result set first, and the optimizer can be affected by adjusting the JOIN order.

However, these practices belong to "intervention optimizers" and should be based on sufficient testing. Overuse can make queries vulnerable, especially when data volume changes easily.

at last

The MySQL optimizer behavior is complex but has traceability. Master its basic logic, combined with the EXPLAIN tool, slow query logs and actual data situations, most performance problems can be located and solved. Basically that's it.

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