# Compare window functions to Grouping

Windowing and Grouping are conceptually related by also different. It is helpful to understand this relationship.

## Use aggregation and Grouping

The following query uses an aggregation to calculate the total salary for all employees:

``````@result =
SELECT
SUM(Salary) AS TotalSalary
FROM @employees;
``````

The result is a single row with a single column. The \$165000 is the sum of of the Salary value from the whole table.

TotalSalary
165000

The following statement use the GROUP BY clause to calculate the total salary for each department:

``````@result=
SELECT DeptName, SUM(Salary) AS SalaryByDept
FROM @employees
GROUP BY DeptName;
``````

The results are:

DeptName SalaryByDept
Engineering 60000
Executive 50000
HR 30000
Marketing 25000

The sum of the SalaryByDept column is \$165000, which matches the amount in the last script. In both these cases the number of there are fewer output rows than input rows: Without GROUP BY, the aggregation collapses all the rows into a single row. With GROUP BY, there are N output rows where N is the number of distinct values that appear in the data, In this case, you will get 4 rows in the output.

## Use a window function

The OVER clause in the following sample is empty. This defines the "window" to include all rows. The SUM in this example is applied to the OVER clause that it precedes. You could read this query as: “The sum of Salary over a window of all rows”.

``````@result=
SELECT
EmpName,
SUM(Salary) OVER( ) AS SalaryAllDepts
FROM @employees;
``````

Unlike GROUP BY, there are as many output rows as input rows:

EmpName SalaryAllDepts
Noah 165000
Sophia 165000
Liam 165000
Emma 165000
Jacob 165000
Olivia 165000
Mason 165000
Ava 165000
Ethan 165000

The value of 165000 (the total of all salaries) is placed in each output row. That total comes from the "window" of all rows, so it includes all the salaries. The next example demonstrates how to refine the "window" to list all the employees, the department, and the total salary for the department. PARTITION BY is added to the OVER clause.

``````@result=
SELECT
EmpName,
DeptName,
SUM(Salary) OVER( PARTITION BY DeptName ) AS SalaryByDept
FROM @employees;
``````

The results are:

EmpName DeptName SalaryByDept
Noah Engineering 60000
Sophia Engineering 60000
Liam Engineering 60000
Mason Executive 50000
Emma HR 30000
Jacob HR 30000
Olivia HR 30000
Ava Marketing 25000
Ethan Marketing 25000

Again, there are the same number of input rows as output rows. However each row has a total salary for the corresponding department.