Combining Multiple Window Functions
Combining multiple window functions in a single query lets you perform complex analytics by calculating different metrics side-by-side. This approach is especially useful when you want to compare rankings, aggregations, or distributions within the same result set. For example, you might want to see both the rank of each employee's salary within their department and the total salary paid out in that department, all in one query. By using different window functions—such as RANK(), SUM(), NTILE(), or AVG()—together, you gain a more complete view of your data without needing multiple queries or intermediate tables.
1234567SELECT name, department, salary, RANK() OVER (PARTITION BY department ORDER BY salary DESC) AS salary_rank, SUM(salary) OVER (PARTITION BY department) AS total_department_salary FROM employees;
You might use multiple window functions together for several reasons. In customer segmentation, you could rank customers by purchase frequency while also calculating their total spend within a segment. For category analysis, you might compare each product's sales rank to the total sales in its category. Multi-metric dashboards often require showing both a value's rank and its contribution to a group total. These scenarios benefit from combining window functions, since you can present layered insights—such as how an individual or item compares to its peers and to the whole group—directly in your analytical queries.
1234567SELECT name, department, salary, NTILE(4) OVER (ORDER BY salary DESC) AS salary_quartile, AVG(salary) OVER (PARTITION BY department) AS avg_department_salary FROM employees;
1. Why might you use multiple window functions in a single query?
2. Which of the following is a valid use of two window functions together?
3. Fill in the blank to combine two window functions in one query. Use one function to rank each employee's salary within their department, and another to sum salaries per department.
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Combining multiple window functions in a single query lets you perform complex analytics by calculating different metrics side-by-side. This approach is especially useful when you want to compare rankings, aggregations, or distributions within the same result set. For example, you might want to see both the rank of each employee's salary within their department and the total salary paid out in that department, all in one query. By using different window functions—such as RANK(), SUM(), NTILE(), or AVG()—together, you gain a more complete view of your data without needing multiple queries or intermediate tables.
1234567SELECT name, department, salary, RANK() OVER (PARTITION BY department ORDER BY salary DESC) AS salary_rank, SUM(salary) OVER (PARTITION BY department) AS total_department_salary FROM employees;
You might use multiple window functions together for several reasons. In customer segmentation, you could rank customers by purchase frequency while also calculating their total spend within a segment. For category analysis, you might compare each product's sales rank to the total sales in its category. Multi-metric dashboards often require showing both a value's rank and its contribution to a group total. These scenarios benefit from combining window functions, since you can present layered insights—such as how an individual or item compares to its peers and to the whole group—directly in your analytical queries.
1234567SELECT name, department, salary, NTILE(4) OVER (ORDER BY salary DESC) AS salary_quartile, AVG(salary) OVER (PARTITION BY department) AS avg_department_salary FROM employees;
1. Why might you use multiple window functions in a single query?
2. Which of the following is a valid use of two window functions together?
3. Fill in the blank to combine two window functions in one query. Use one function to rank each employee's salary within their department, and another to sum salaries per department.
¡Gracias por tus comentarios!
