HardSQL challenge #276WINDOW FUNCTIONPARTITIONANALYTICS

Show Each Salary's Gap to Its Department Average

Return every employee with how far their salary sits above or below their department's average.

The challenge runs on the SQLabHub practice database (SQLite) and uses the employees table. You can solve it in the browser, with nothing to install.

Solve This SQL Challenge

The task

Find difference between salary and department average.

A correct answer returns 120 rows with 13 columns: id, first_name, last_name, email, department, department_id, title, salary, hire_date, manager_id, city, status, diff.

Tables used in this challenge

`employees` 120 rows

id INTEGER (PK) · first_name TEXT · last_name TEXT · email TEXT · department TEXT · department_id INTEGER · title TEXT · salary REAL · hire_date TEXT · manager_id INTEGER · city TEXT · status TEXT

First 3 rows of the employees table
id	first_name	last_name	email	department	department_id	title	salary	hire_date	manager_id	city	status
1	William	Lewis	wlewis18@corp.io	Customer Success	7	Senior CS Manager	61774	2022-07-24	NULL	San Diego	active
2	John	Miller	jmiller51@corp.io	Legal	8	Paralegal	191694	2021-08-09	NULL	San Diego	active
3	Daniel	Rivera	drivera50@corp.io	Engineering	1	VP Engineering	135067	2016-06-06	NULL	Houston	active

The first rows of each table are shown. See how all the tables relate on the database schema page.

Expected output

Expected output of the challenge
id	first_name	last_name	email	department	department_id	title	salary	hire_date	manager_id	city	status	diff
1	William	Lewis	wlewis18@corp.io	Customer Success	7	Senior CS Manager	61774	2022-07-24	NULL	San Diego	active	-72365.93333333332
15	Barbara	Baker	bbaker4@corp.io	Customer Success	7	Senior CS Manager	188280	2018-12-15	8	Philadelphia	on_leave	54140.06666666668
18	Robert	Green	rgreen61@corp.io	Customer Success	7	CS Manager	73118	2023-08-04	9	San Diego	active	-61021.93333333332
20	Edward	Ramirez	eramirez83@corp.io	Customer Success	7	Senior CS Manager	137737	2016-11-10	9	Indianapolis	active	3597.0666666666802
21	Charles	Allen	callen32@corp.io	Customer Success	7	CS Director	162901	2023-02-14	8	Houston	active	28761.06666666668

First 5 of 120 rows. This is the output of the model solution on the practice database. The task does not fix a sort order, so your rows may come back in a different order.

What you practise

Attaching a total or average to every row with an aggregate OVER ()
Restarting a window calculation for each group with PARTITION BY
Deriving a new column from an expression and naming it with an alias

Hint and approach

Try the challenge first. Open these only when you need them.

Show the hint

AVG OVER partition

Show the step-by-step approach

How the model solution is built, in the order the database evaluates it:

Read from the employees table.
Compute AVG(salary) as a window function over each department, so the group's value is repeated on every one of its rows.
Combine those values into diff: salary - AVG(salary) OVER (PARTITION BY department).

Model solution

Checking your session…

What to watch for

AVG(salary) OVER (PARTITION BY department) attaches the department average to each employee row. The differences inside a department sum to zero.

Window aggregates. A window aggregate keeps every row, while a plain aggregate collapses them. Mixing the two in one SELECT without GROUP BY is an error.
PARTITION BY. PARTITION BY is not GROUP BY: it keeps every row and only decides which rows a window function looks at.
Calculated columns. Dividing one integer by another truncates the result in SQLite. Multiply one side by 1.0 to get decimals.