Why Does Using SUM() Without GROUP BY Return Unexpected Results?

Understanding the Need for GROUP BY with Aggregate Functions

The example provided showcases a perplexing scenario where summing the salaries of employees without using the GROUP BY clause resulted in the original table being returned as the output. To unravel this mystery, we delve into the purpose and role of GROUP BY when working with aggregate functions like SUM().

GROUP BY, as the name suggests, groups rows based on specified criteria. This grouping becomes particularly crucial when using aggregate functions that perform calculations on groups of rows rather than individual rows. In our case, the SUM() function calculates the sum of MonthlySalary for each unique EmployeeID.

Without using GROUP BY, the query would attempt to calculate the sum of all MonthlySalary values without grouping them by EmployeeID. This would give an erroneous result because it would essentially sum up all salaries in the table, treating them as one massive pool.

Take the following example:

SELECT EmployeeID, SUM(MonthlySalary)
FROM Employee;

The outcome of this query will be a single row with EmployeeID as NULL and the sum of all salaries. This result is meaningless because it does not provide the necessary information about employee-specific salary totals.

By including GROUP BY in the query, we force the database to perform the calculation for each unique EmployeeID, resulting in a meaningful output:

SELECT EmployeeID, SUM(MonthlySalary)
FROM Employee
GROUP BY EmployeeID;

Now, the result will comprise individual rows for each employee, displaying their respective EmployeeIDs and the corresponding summed MonthlySalaries.

In summary, GROUP BY ensures that aggregate functions like SUM() are applied to specific groups of rows, allowing for meaningful aggregations of data. It facilitates the extraction of meaningful insights and prevents the misinterpretation of results.

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