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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