In SQL, the MIN and MAX functions are used to retrieve the smallest and largest values from a set of data, respectively. These functions are essential for data analysis, allowing users to quickly identify extreme values in datasets.
The syntax for using MIN and MAX is straightforward. You can apply these functions to any numeric column to find the minimum or maximum value.
SELECT MIN(salary) AS LowestSalary FROM employees;
SELECT MAX(salary) AS HighestSalary FROM employees;
You can use the WHERE clause to filter records before applying the MIN and MAX functions. This is useful for finding extreme values within specific subsets of data.
SELECT MIN(salary) AS LowestSalary FROM employees WHERE department = 'Sales';
SELECT MAX(salary) AS HighestSalary FROM employees WHERE department = 'IT';
The GROUP BY clause can be combined with MIN and MAX to find extreme values for each group in a dataset. This is particularly useful for segmenting data by categories.
SELECT department, MIN(salary) AS LowestSalary FROM employees GROUP BY department;
SELECT department, MAX(salary) AS HighestSalary FROM employees GROUP BY department;
You can combine MIN and MAX with other aggregate functions such as COUNT, AVG, and SUM to perform comprehensive data analysis.
SELECT department, MIN(salary) AS LowestSalary, MAX(salary) AS HighestSalary, AVG(salary) AS AverageSalary FROM employees GROUP BY department;
The MIN and MAX functions can also be applied to date columns to find the earliest and latest dates in a dataset.
SELECT MIN(hire_date) AS FirstHire FROM employees;
SELECT MAX(hire_date) AS LastHire FROM employees;
By default, MIN and MAX ignore NULL values. However, you can handle NULLs explicitly using COALESCE or similar functions if needed.
SELECT MIN(COALESCE(salary, 0)) AS LowestSalary FROM employees;
SELECT MAX(COALESCE(salary, 0)) AS HighestSalary FROM employees;
Using MIN and MAX on indexed columns can significantly improve query performance. Ensure that relevant columns are indexed for optimal efficiency.
Console Output Example:
LowestSalary: 30000
HighestSalary: 120000
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