MySQL Scalar Subquery Unnesting transformation

Scalar subquery unnesting is a transformation technique used by the MySQL optimizer to optimize queries that involve scalar subqueries. Scalar subqueries are subqueries that return a single value, typically used in expressions or as part of the SELECT clause.

When scalar subquery unnesting is applied, the optimizer transforms the query by rewriting the scalar subquery as a join or by merging it into the outer query. This transformation aims to improve performance by reducing the number of subquery executions and optimizing the query execution plan.

Here’s an example to illustrate the transformation:

Original query with scalar subquery:

SELECT column1, (SELECT MAX(column2) FROM table2) AS max_value
FROM table1;

Transformed query after scalar subquery unnesting:

SELECT table1.column1, subquery.max_value
FROM table1
CROSS JOIN (SELECT MAX(column2) AS max_value FROM table2) AS subquery;

In the transformed query, the scalar subquery (SELECT MAX(column2) FROM table2) is transformed into a derived table subquery that returns the single value. This derived table is then joined with table1 using a cross join to combine the results.

The scalar subquery unnesting transformation can help improve query performance by eliminating redundant subquery executions and allowing the optimizer to generate more efficient execution plans. However, it’s important to note that not all scalar subqueries are suitable for unnesting, and the optimizer decides whether to apply this transformation based on various factors, including the query structure and optimizer settings.

It’s recommended to analyze the query plans and performance implications before and after the transformation to ensure it provides the desired optimization benefits. Additionally, keep in mind that the effectiveness of scalar subquery unnesting can vary depending on the specific query and database statistics.


MySQL’s scalar subquery unnesting transformation optimizes queries with scalar subqueries by converting them into joins or merging them with the outer query. While it can enhance performance by reducing subquery executions, its effectiveness varies and requires careful analysis to ensure desired optimization benefits.

About Shiv Iyer 456 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.