SQL SELECT SUM

The SQL SELECT SUM() function is a strong aggregate function that returns the total sum of a numeric column in a database. It is widely used in data analysis and reporting to get the total value of an expression across multiple records.

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SQL SUM() Syntax

SELECT SUM(expression)  
FROM table_name  
WHERE conditions;  

• expression: This is the numeric field or formula that needs to be summed.
• table_name: The name of the table from which data is retrieved.
• conditions: (Optional) Specifies which records should be included in the sum calculation.

Example 1: SQL SUM with a Single Column

Let’s consider an employees table with the following data:

ID	EMPLOYEE_NAME	SALARY
1	RAHUL SHARMA	45000
2	ANANYA SINGH	28000
3	VIKRAM PATEL	39000
4	MEGHA AGRAWAL	23000

Query:

If we want to find the total salary of all employees earning more than 25,000, we can use:

SELECT SUM(salary) AS "Total Salary"  
FROM employees  
WHERE salary > 25000;  

Result:

Total Salary: 112,000

This query returns the total salary of employees who earn more than 25,000 per month.

Example 2: SQL SUM with DISTINCT Values

We can use the DISTINCT keyword to sum only unique salary values:

SELECT SUM(DISTINCT salary) AS "Total Salary"  
FROM employees  
WHERE salary > 25000;  

This ensures that duplicate salaries are not counted more than once.

Example 3: SQL SUM with GROUP BY

The GROUP BY statement allows us to calculate the total sales per department.

Consider the following sales_data table:

ID	DEPARTMENT	DATE	DAILY_SALES
1	IT	2023-07-10	500
2	HR	2023-07-10	200
3	IT	2023-07-11	600
4	HR	2023-07-11	300
5	FINANCE	2023-07-10	400

Query:

SELECT department, SUM(daily_sales) AS "Total Sales"  
FROM sales_data  
GROUP BY department;  

Result:

DEPARTMENT	TOTAL SALES
IT	1100
HR	500
FINANCE	400

This query groups the sales data by department and calculates the total sales per department.

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Conclusion

The SQL SUM() function is a crucial tool for performing aggregate calculations in databases. Whether you are summing individual fields, working with distinct values, or using GROUP BY for detailed reports, SUM() simplifies data analysis effectively.

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