【MySQL/MariaDB】相関サブクエリで詰まった？メインWHERE句での列参照問題を解決する3つの方法

MySQLとMariaDBにおける相関サブクエリとメインのWHERE句における列制限に関する詳細解説

MySQLとMariaDBにおける相関サブクエリは、外部クエリで参照される列を含むサブクエリを指します。この種のサブクエリは、複雑なデータ操作や分析に役立ちますが、メインのWHERE句で列を直接参照できないという制限があります。

本記事では、相関サブクエリとその制限事項について詳細に解説し、代替アプローチとして結合やウィンドウ関数を用いた解決策を紹介します。

相関サブクエリは、外部クエリで参照される列を参照するサブクエリです。具体的には、外部クエリの各行に対してサブクエリが実行され、その結果に基づいて最終的な結果セットが生成されます。

例：相関サブクエリを用いた社員情報と所属部署名の取得

SELECT s.employee_id, s.name, d.department_name
FROM employees AS s
WHERE s.salary > (
    SELECT AVG(salary)
    FROM employees
    WHERE department_id = s.department_id
);

上記の例では、employeesテーブルから給与が部門平均よりも高い社員の情報を取得しています。サブクエリは、各社員の所属部署IDに基づいて部門平均給与を計算し、それを外部クエリのWHERE句で使用しています。

メインのWHERE句における列制限

相関サブクエリにおいて、メインのWHERE句で**直接参照できる列は、外部クエリで定義されている列のみとなります。サブクエリで計算された結果や、外部クエリとは別のテーブルに属する列は直接参照できません。

例：エラーとなる相関サブクエリ

SELECT s.employee_id, s.name, d.department_name
FROM employees AS s
WHERE s.salary > (
    SELECT AVG(salary)
    FROM employees
    WHERE department_id = s.department_id
) AND s.department_name = '営業部';

上記の例では、メインのWHERE句でs.department_name列を参照していますが、これはエラーとなります。department_name列はサブクエリで計算された結果であり、外部クエリで直接参照することはできないためです。

制限の原因と解決策

この制限は、相関サブクエリの処理方法に起因します。MySQLとMariaDBは、相関サブクエリをネストループ結合として処理します。つまり、外部クエリの各行に対してサブクエリが個別に実行され、その結果に基づいて最終的な結果セットが生成されます。

この処理方法により、メインのWHERE句でサブクエリの結果や外部クエリとは別のテーブルの列を直接参照することはできないという制約が生じます。

解決策として、以下の代替アプローチが考えられます。

結合を用いた解決策

相関サブクエリを結合に置き換えることで、メインのWHERE句で列を直接参照することができます。

SELECT s.employee_id, s.name, d.department_name
FROM employees AS s
JOIN departments AS d ON s.department_id = d.department_id
WHERE s.salary > (
    SELECT AVG(salary)
    FROM employees AS e
    JOIN departments AS de ON e.department_id = de.department_id
    WHERE de.department_name = '営業部'
);

上記の例では、employeesテーブルとdepartmentsテーブルを結合し、department_name列を直接参照しています。

ウィンドウ関数を用いた解決策

最近のMySQLとMariaDBバージョンでは、ウィンドウ関数を使用して相関サブクエリを代替することができます。ウィンドウ関数は、特定の行グループにわたって集計や分析を実行する機能を提供します。

SELECT s.employee_id, s.name, d.department_name
FROM employees AS s
JOIN departments AS d ON s.department_id = d.department_id
OVER (PARTITION BY s.department_id)
WHERE s.salary > AVG(salary) OVER (PARTITION BY s.department_id);

上記の例では、AVG()ウィンドウ関数を使用して、各部署の平均給与を算出しています。

その他の注意点

• 相関サブクエリは、非相関サブクエリよりも処理負荷が高くなります

Sample Code: Error due to Column Reference in Main WHERE Clause

SELECT s.employee_id, s.name, d.department_name
FROM employees AS s
WHERE s.salary > (
    SELECT AVG(salary)
    FROM employees
    WHERE department_id = s.department_id
) AND s.department_name = 'Sales';

This query attempts to retrieve employee information and their corresponding department names, filtering based on both salary and department name. However, it fails due to the reference to s.department_name in the main WHERE clause, which is not directly accessible within the correlated subquery.

Sample Code: Join Approach for Retrieving Employee Information and Department Names

SELECT s.employee_id, s.name, d.department_name
FROM employees AS s
JOIN departments AS d ON s.department_id = d.department_id
WHERE s.salary > (
    SELECT AVG(salary)
    FROM employees AS e
    JOIN departments AS de ON e.department_id = de.department_id
    WHERE de.department_name = 'Sales'
);

This query utilizes a join operation to combine data from the employees and departments tables, allowing direct access to the department_name column within the main WHERE clause.

SELECT s.employee_id, s.name, d.department_name
FROM employees AS s
JOIN departments AS d ON s.department_id = d.department_id
OVER (PARTITION BY s.department_id)
WHERE s.salary > AVG(salary) OVER (PARTITION BY s.department_id);

This query employs a window function, AVG(), to calculate the average salary within each department, enabling the comparison against individual employee salaries without relying on a correlated subquery.

Explanation of Sample Code:

Sample Code 1:

• The main query selects employee information (employee_id, name) and the corresponding department name (department_name) from the employees and departments tables, respectively.
• The WHERE clause filters the results based on two conditions:
  1. s.salary > (SELECT AVG(salary) FROM employees WHERE department_id = s.department_id): This portion utilizes a correlated subquery to retrieve the average salary for each department. However, the attempt to reference s.department_name within the subquery leads to an error.
  2. s.department_name = 'Sales': This condition further filters the results to include only employees from the 'Sales' department.

• The WHERE clause remains the same, using a correlated subquery to calculate the average salary for each department.
• However, the join allows direct access to the department_name column from the departments table within the subquery, enabling the comparison against individual employee salaries.

• The WHERE clause filters the results based on the condition s.salary > AVG(salary) OVER (PARTITION BY s.department_id).

These sample codes illustrate the limitations of correlated subqueries in referencing columns from the main query and demonstrate alternative approaches using joins and window functions to achieve the desired results.

Alternative Approaches to Correlated Subqueries in MySQL and MariaDB

A materialized subquery involves storing the results of a subquery as a temporary table or materialized view. This can be useful for frequently executed subqueries or those with complex logic, as it avoids the overhead of re-executing the subquery for each row in the main query.

Example:

CREATE MATERIALIZED VIEW emp_salary_avg_by_dept AS
SELECT department_id, AVG(salary) AS avg_salary
FROM employees
GROUP BY department_id;

SELECT s.employee_id, s.name, d.department_name
FROM employees AS s
JOIN departments AS d ON s.department_id = d.department_id
WHERE s.salary > (
    SELECT avg_salary
    FROM emp_salary_avg_by_dept
    WHERE department_id = s.department_id
);

Derived tables are similar to materialized views, but they exist only for the duration of the current query. They can be useful for one-time or temporary subqueries that don't need to be persisted.

SELECT s.employee_id, s.name, d.department_name
FROM employees AS s
JOIN departments AS d ON s.department_id = d.department_id
WHERE s.salary > (
    SELECT AVG(salary)
    FROM (
        SELECT department_id, AVG(salary) AS avg_salary
        FROM employees
        GROUP BY department_id
    ) AS dept_avg
    WHERE dept_avg.department_id = s.department_id
);

Common Table Expressions (CTEs):

CTEs are similar to derived tables but offer more flexibility in terms of referencing and modifying data within the subquery. They can be particularly useful for complex subqueries that involve multiple steps or data manipulation.

WITH dept_avg AS (
    SELECT department_id, AVG(salary) AS avg_salary
    FROM employees
    GROUP BY department_id
)
SELECT s.employee_id, s.name, d.department_name
FROM employees AS s
JOIN departments AS d ON s.department_id = d.department_id
WHERE s.salary > (
    SELECT avg_salary
    FROM dept_avg
    WHERE dept_avg.department_id = s.department_id
);

Scalar subqueries return a single value, which can be directly used in the main query. However, they are limited to simple operations and may not be suitable for complex subqueries.

SELECT s.employee_id, s.name, d.department_name
FROM employees AS s
JOIN departments AS d ON s.department_id = d.department_id
WHERE s.salary > (
    SELECT AVG(salary)
    FROM employees
    WHERE department_id = s.department_id
);

Temporary tables can be used to store intermediate results or transformed data, allowing for more complex operations and data manipulation before incorporating them into the main query.

CREATE TEMPORARY TABLE emp_salary_with_dept_avg AS
SELECT e.employee_id, e.name, d.department_name, AVG(salary) AS avg_salary
FROM employees AS e
JOIN departments AS d ON e.department_id = d.department_id
GROUP BY e.employee_id, e.name, d.department_name;

SELECT *
FROM emp_salary_with_dept_avg
WHERE salary > avg_salary;

These alternative approaches provide various strategies for handling complex queries and overcoming the limitations of correlated subqueries in MySQL and MariaDB. The choice of method depends on the specific requirements, data volume, and performance considerations of the query at hand.