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Top Three Salaries FAANG SQL Interview Question
Top Three Salaries
FAANG SQL Interview Question
As part of an ongoing analysis of salary distribution within the company, your manager has requested a report identifying high earners in each department. A 'high earner' within a department is defined as an employee with a salary ranking among the top three salaries within that department.
You're tasked with identifying these high earners across all departments. Write a query to display the employee's name along with their department name and salary. In case of duplicates, sort the results of department name in ascending order, then by salary in descending order. If multiple employees have the same salary, then order them alphabetically.
Note: Ensure to utilize the appropriate ranking window function to handle duplicate salaries effectively.
As of June 18th, we have removed the requirement for unique salaries and revised the sorting order for the results.
Schema:
| column_name | type | description |
|---|---|---|
| employee_id | integer | The unique ID of the employee. |
| name | string | The name of the employee. |
| salary | integer | The salary of the employee. |
| department_id | integer | The department ID of the employee. |
| manager_id | integer | The manager ID of the employee. |
Example Input:
| employee_id | name | salary | department_id | manager_id |
|---|---|---|---|---|
| 1 | Emma Thompson | 3800 | 1 | 6 |
| 2 | Daniel Rodriguez | 2230 | 1 | 7 |
| 3 | Olivia Smith | 2000 | 1 | 8 |
| 4 | Noah Johnson | 6800 | 2 | 9 |
| 5 | Sophia Martinez | 1750 | 1 | 11 |
| 6 | Liam Brown | 13000 | 3 | |
| 7 | Ava Garcia | 12500 | 3 | |
| 8 | William Davis | 6800 | 2 | |
| 9 | Isabella Wilson | 11000 | 3 | |
| 10 | James Anderson | 4000 | 1 | 11 |
Schema:
| column_name | type | description |
|---|---|---|
| department_id | integer | The department ID of the employee. |
| department_name | string | The name of the department. |
Example Input:
| department_id | department_name |
|---|---|
| 1 | Data Analytics |
| 2 | Data Science |
Example Output:
| department_name | name | salary |
|---|---|---|
| Data Analytics | James Anderson | 4000 |
| Data Analytics | Emma Thompson | 3800 |
| Data Analytics | Daniel Rodriguez | 2230 |
| Data Science | Noah Johnson | 6800 |
| Data Science | William Davis | 6800 |
The output displays the high earners in each department.
- In the Data Analytics deaprtment, James Anderson leads with a salary of $4,000, followed by Emma Thompson earning $3,800, and Daniel Rodriguez with $2,230.
- In the Data Science department, both Noah Johnson and William Davis earn $6,800, with Noah listed before William due to alphabetical ordering.
The dataset you are querying against may have different input & output - this is just an example!
Solution
Step 1: Identify High Earners in Each Department
To determine the high earners in each department, we assign a ranking to each employee within their respective department based on salary. By using the window function, we generate unique ranks for each employee's salary within their department with higher salaries receiving lower ranks.
‼️ Why use DENSE_RANK() over RANK() or ROW_NUMBER()?
assigns consecutive ranks to rows ensuring that ties in salaries don't create gaps in the ranking sequence.
is similar to , but it might leave gaps in the ranking sequence when there are ties.
simply numbers each row sequentially without considering ties.
Check out our tutorial for more on window functions!
Step 2: Filter to Display Top Three Salaries
Now, we build upon the query in Step 1 by wrapping it within a CTE named .
Then, we filter the results to include only employees who are considered high earners within their departments (those with a ranking of 3 or lower).
Finally, we order the results by department name in ascending order, followed by salary in descending order (to highlight the top three salaries), and employee name in ascending order.