Table of Contents
introduction
Review of basic knowledge
Core concept or function analysis
Window Functions
Common Table Expressions (CTEs)
Stored procedures
Example of usage
Basic usage
Advanced Usage
Common Errors and Debugging Tips
Performance optimization and best practices
Home Database SQL SQL Deep Dive: Mastering Window Functions, Common Table Expressions (CTEs), and Stored Procedures

SQL Deep Dive: Mastering Window Functions, Common Table Expressions (CTEs), and Stored Procedures

Apr 04, 2025 am 12:20 AM
sql 窗口函数

SQL provides three powerful functions: window functions, common table expressions (CTEs), and stored procedures. 1. Window functions allow grouping and sorting operations without changing the data set. 2.CTEs provide temporary result sets to simplify complex queries. 3. Stored procedures are precompiled SQL code blocks that can be executed repeatedly to improve efficiency and consistency.

introduction

In a data-driven world, SQL is not just a query language, but also an art. Today, we will dive into three powerful features in SQL: window functions, common table expressions (CTEs), and stored procedures. Through this article, you will learn how to use these tools to deal with complex data problems, improve your SQL skills, and be at ease in data analysis and management.

Review of basic knowledge

The charm of SQL lies in its simplicity and powerful functions. Window functions allow you to group and sort data without changing the data set. CTEs provide a temporary result set way to make complex queries more readable and managed. Stored procedures are precompiled SQL code blocks that can be executed repeatedly to improve efficiency and consistency.

Core concept or function analysis

Window Functions

Window functions are a magical tool in SQL that allows you to group and sort data without changing the data set. They are very useful in data analysis because they can help you calculate moving averages, rankings, cumulative sums, and more.

 SELECT 
    Employee_id,
    Salarary,
    AVG(salary) OVER (PARTITION BY department) AS avg_department_salary,
    RANK() OVER (ORDER BY salary DESC) AS salary_rank
FROM 
    employees;
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In this example, we calculate the average salary for each employee’s department and rank the employees based on their salary. The power of window functions is that they allow you to perform multiple calculations in the same query without using subqueries or self-joins.

Common Table Expressions (CTEs)

CTEs are temporary result sets in SQL that simplify the structure of complex queries and make the code more readable and maintained. CTEs are particularly useful in recursive queries because they can refer to themselves.

 WITH RECURSIVE employee_hierarchy AS (
    SELECT employee_id, manager_id, 0 AS level
    FROM employees
    WHERE manager_id IS NULL
    UNION ALL
    SELECT e.employee_id, e.manager_id, eh.level 1
    FROM employees e
    JOIN employee_hierarchy eh ON e.manager_id = eh.employee_id
)
SELECT * FROM employee_hierarchy;
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In this example, we use CTE to build the hierarchy of employees. The recursive nature of CTE allows us to easily traverse the entire employee tree without writing complex self-connection queries.

Stored procedures

Stored procedures are precompiled blocks of SQL code that can be executed repeatedly. They are useful when you need to perform complex logic or improve performance because they reduce network traffic and compile time.

 CREATE PROCEDURE get_employee_details(IN emp_id INT)
BEGIN
    SELECT 
        e.employee_id,
        e.first_name,
        e.last_name,
        d.department_name
    FROM 
        Employees e
    JOIN 
        departments d ON e.department_id = d.department_id
    WHERE 
        e.employee_id = emp_id;
END;
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In this example, we create a stored procedure to get employee details. The advantage of stored procedures is that they can encapsulate complex logic and can be called multiple times, improving code reusability and consistency.

Example of usage

Basic usage

The basic usage of window functions is very simple. You can use the OVER clause to define the window and use various aggregate functions to calculate the result.

 SELECT 
    product_id,
    sale_date,
    sale_amount,
    SUM(sale_amount) OVER (PARTITION BY product_id ORDER BY sale_date) AS running_total
FROM 
    sales;
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In this example, we calculate the accumulated sales for each product. PARTITION BY clause groups data, and ORDER BY clause defines the order of windows.

The basic usage of CTEs is also very simple. You can use the WITH keyword to define a CTE and then reference it in subsequent queries.

 WITH top_sellers AS (
    SELECT product_id, SUM(sale_amount) AS total_sales
    FROM sales
    GROUP BY product_id
    ORDER BY total_sales DESC
    LIMIT 10
)
SELECT * FROM top_sellers;
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In this example, we use CTE to find the 10 products with the highest sales. CTE makes query structure clearer and easier to manage.

The basic usage of stored procedures is also very simple. You can use the CREATE PROCEDURE statement to define a stored procedure, and then use the CALL statement to call it.

 CALL get_employee_details(1);
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In this example, we call the previously defined stored procedure to get employee details with employee ID 1.

Advanced Usage

Advanced usage of window functions includes using ROWS or RANGE clauses to define the scope of a window, and using LAG and LEAD functions to access the data of the front and back rows.

 SELECT 
    product_id,
    sale_date,
    sale_amount,
    LAG(sale_amount) OVER (PARTITION BY product_id ORDER BY sale_date) AS previous_sale,
    LEAD(sale_amount) OVER (PARTITION BY product_id ORDER BY sale_date) AS next_sale
FROM 
    sales;
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In this example, we use LAG and LEAD functions to get the previous and next sales of each product. Such advanced usage can help you perform more complex data analysis.

Advanced usage of CTEs includes using recursive CTEs to process hierarchical data, and using multiple CTEs to simplify complex queries.

 WITH RECURSIVE category_hierarchy AS (
    SELECT category_id, parent_category_id, 0 AS level
    FROM categories
    WHERE parent_category_id IS NULL
    UNION ALL
    SELECT c.category_id, c.parent_category_id, ch.level 1
    FROM categories c
    JOIN category_hierarchy ch ON c.parent_category_id = ch.category_id
),
product_categories AS (
    SELECT p.product_id, ch.category_id, ch.level
    FROM products p
    JOIN category_hierarchy ch ON p.category_id = ch.category_id
)
SELECT * FROM product_categories;
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In this example, we use recursive CTE to build the hierarchy of the product category, and then use another CTE to associate the product with its category. Such advanced usage can help you deal with complex hierarchical data.

Advanced usage of stored procedures includes the use of cursors, exception handling, and transaction management to implement complex business logic.

 CREATE PROCEDURE update_employee_salary(IN emp_id INT, IN new_salary DECIMAL(10, 2))
BEGIN
    DECLARE exit handler for sqlexception
    BEGIN
        ROLLBACK;
        RESIGNAL;
    END;

    START TRANSACTION;
    UPDATE employees
    SET salary = new_salary
    WHERE employee_id = emp_id;
    COMMIT;
END;
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In this example, we create a stored procedure to update employee salaries. Stored procedures use transaction management and exception handling to ensure data consistency and integrity.

Common Errors and Debugging Tips

A common mistake when using window functions is to forget to use the OVER clause. This causes the SQL engine to fail to parse window functions correctly.

 -- Error Example SELECT 
    Employee_id,
    Salarary,
    AVG(salary) -- Missing OVER clause FROM 
    employees;
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To avoid this error, make sure that the OVER clause is always included when using the window function.

When using CTEs, a common mistake is to forget to define all required columns in the CTE. This will cause subsequent queries to fail to correctly reference data in the CTE.

 -- Error Example WITH top_sellers AS (
    SELECT product_id -- total_sales column missing FROM sales
    GROUP BY product_id
    ORDER BY total_sales DESC
    LIMIT 10
)
SELECT * FROM top_sellers;
Copy after login

To avoid this error, make sure to include all required columns when defining the CTE.

A common mistake when using stored procedures is forgetting to handle exceptions. This may cause stored procedures to fail to roll back the transaction correctly when they encounter an error.

 -- Error example CREATE PROCEDURE update_employee_salary(IN emp_id INT, IN new_salary DECIMAL(10, 2))
BEGIN
    UPDATE employees
    SET salary = new_salary
    WHERE employee_id = emp_id;
END;
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To avoid this error, make sure to include exception handling and transaction management in the stored procedure.

Performance optimization and best practices

When using window functions, a key point in performance optimization is to select the appropriate window frame. Using ROWS or RANGE clauses can significantly improve query performance because they can reduce the computational volume of window functions.

 -- Optimization Example SELECT 
    product_id,
    sale_date,
    sale_amount,
    SUM(sale_amount) OVER (PARTITION BY product_id ORDER BY sale_date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS running_total
FROM 
    sales;
Copy after login

In this example, we use the ROWS clause to define the window framework, which can improve query performance.

When using CTEs, a key point in performance optimization is to avoid using complex calculations in CTEs. CTEs are temporary result sets that may affect query performance if they contain complex calculations.

 -- Optimization example WITH sales_summary AS (
    SELECT product_id, SUM(sale_amount) AS total_sales
    FROM sales
    GROUP BY product_id
)
SELECT * FROM sales_summary;
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In this example, we put complex calculations outside of CTE to improve query performance.

When using stored procedures, a key point in performance optimization is to avoid using cursors in stored procedures. Cursors can cause performance degradation because they need to process data line by line.

 -- Optimization example CREATE PROCEDURE update_employee_salaries()
BEGIN
    UPDATE employees
    SET salary = salary * 1.1;
END;
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In this example, we avoid using cursors and use batch update operations to improve performance.

When writing SQL code, best practices include using meaningful alias, annotating code, and keeping the code readable and maintainable.

 -- Best Practice Example SELECT 
    e.employee_id AS emp_id, -- use meaningful alias e.first_name, -- comment code e.last_name,
    d.department_name -- Keep code readability and maintainability FROM 
    Employees e
JOIN 
    departments d ON e.department_id = d.department_id;
Copy after login

By following these best practices, you can write more efficient and more maintainable SQL code.

In the process of exploring SQL, we not only mastered the basic and advanced usage of window functions, CTEs and stored procedures, but also learned how to avoid common errors and optimize performance. I hope this article can help you better understand and apply these powerful SQL features and achieve greater success in data analysis and management.

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