Nesting Functions in SQL

Nesting Functions in SQL

Nesting functions can help you perform sophisticated operations by combining multiple SQL functions. The general syntax for nesting functions is to place one function inside the parentheses of another. Here’s a guide to common scenarios and examples of nested functions:

Nesting Aggregate Functions

Aggregate functions operate on a set of values and return a single value. You can nest aggregate functions to perform complex calculations.

Example

Calculate the average of the maximum salaries per department: 

SELECT AVG(dept_max_salary) AS overall_avg_salary
FROM (
    SELECT department_id,
           MAX(salary) AS dept_max_salary
    FROM employees
    GROUP BY department_id
) AS max_salaries;

In this example:

• The inner query calculates the maximum salary for each department.
• The outer query calculates the average of these maximum salaries.

Nesting String Functions

String functions manipulate text data. You can nest string functions to perform multiple text manipulations in a single expression.

Example

Convert a name to uppercase and then trim any leading or trailing spaces: 

SELECT TRIM(UPPER(employee_name)) AS cleaned_name
FROM employees;

In this example:

• UPPER(employee_name) converts the name to uppercase.
• TRIM() removes any leading or trailing spaces from the result.

Nesting Date Functions

Date functions operate on date and time values. You can nest these functions to format dates or perform date arithmetic.

Example

Get the start of the month for the date one year ago: 

SELECT DATE_TRUNC('month', CURRENT_DATE - INTERVAL '1 year') AS start_of_last_year_month
FROM dual;

In this example:

• CURRENT_DATE – INTERVAL ‘1 year’ calculates the date one year ago.
• DATE_TRUNC(‘month’, …) returns the first day of that month.

Nesting Mathematical Functions

Mathematical functions perform calculations on numeric data. You can nest these functions to apply multiple operations.

Example

Calculate the square root of the sum of squared values: 

SELECT SQRT(SUM(POW(salary, 2))) AS sqrt_of_sum_of_squares
FROM employees;

In this example:

• POW(salary, 2) squares each salary.
• SUM(…) calculates the sum of these squared salaries.
• SQRT(…) takes the square root of this sum.

Nesting Analytical Functions

Analytical functions perform calculations across a set of rows related to the current row. Nesting these functions can help in advanced data analysis.

Example

Calculate the running total of salaries and then rank the employees based on this running total: 

SELECT employee_id, salary,
       RANK() OVER (ORDER BY running_total DESC) AS salary_rank
FROM (
    SELECT employee_id, salary,
           SUM(salary) OVER (ORDER BY employee_id ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS running_total
    FROM employees
) AS running_totals;

In this example:

• The inner query calculates a running total of salaries.
• The outer query ranks employees based on this running total.

Nesting Conditional Functions

Conditional functions, such as CASE, allow you to perform conditional logic within queries. You can nest these functions to handle more complex conditions.

Example

Apply different bonuses based on salary ranges: 

SELECT employee_id, salary,
       CASE
           WHEN salary < 50000 THEN 0.05 * salary
           WHEN salary BETWEEN 50000 AND 100000 THEN 0.10 * salary
           ELSE 0.15 * salary
       END AS bonus
FROM employees;

In this example:

• The CASE statement determines the bonus based on salary ranges.

Summary

Nesting functions in SQL allows you to build complex and powerful queries by combining the results of multiple functions. This technique is useful for performing advanced calculations, data transformations, and analyses. Here’s a quick recap of how nesting can be applied:

• Aggregate Functions: Nesting aggregates to perform multi-step calculations.
• String Functions: Combining text manipulations.
• Date Functions: Performing complex date calculations and formatting.
• Mathematical Functions: Applying multiple mathematical operations.
• Analytical Functions: Advanced data analysis with nested calculations.
• Conditional Functions: Implementing complex conditional logic.