#3611
Medium Database Find overbooked employees
Database
45.4% acceptance
Feb 27, 2026
41
10
Table: employees
+---------------+---------+
| Column Name | Type |
+---------------+---------+
| employee_id | int |
| employee_name | varchar |
| department | varchar |
+---------------+---------+
employee_id is the unique identifier for this table.
Each row contains information about an employee and their department.
Table: meetings
+---------------+---------+
| Column Name | Type |
+---------------+---------+
| meeting_id | int |
| employee_id | int |
| meeting_date | date |
| meeting_type | varchar |
| duration_hours| decimal |
+---------------+---------+
meeting_id is the unique identifier for this table.
Each row represents a meeting attended by an employee. meeting_type can be 'Team', 'Client', or 'Training'.
Write a solution to find employees who are meeting-heavy - employees who spend more than 50% of their working time in meetings during any given week.
Assume a standard work week is 40 hours
Calculate total meeting hours per employee per week (Monday to Sunday)
An employee is meeting-heavy if their weekly meeting hours > 20 hours (50% of 40 hours)
Count how many weeks each employee was meeting-heavy
Only include employees who were meeting-heavy for at least 2 weeks
Return the result table ordered by the number of meeting-heavy weeks in descending order, then by employee name in ascending order.
The result format is in the following example.
Solution
SQL
#
# Table: employees
# +---------------+---------+
# | Column Name | Type |
# +---------------+---------+
# | employee_id | int |
# | employee_name | varchar |
# | department | varchar |
# +---------------+---------+
# employee_id is the unique identifier for this table.
# Each row contains information about an employee and their department.
# Table: meetings
# +---------------+---------+
# | Column Name | Type |
# +---------------+---------+
# | meeting_id | int |
# | employee_id | int |
# | meeting_date | date |
# | meeting_type | varchar |
# | duration_hours| decimal |
# +---------------+---------+
# meeting_id is the unique identifier for this table.
# Each row represents a meeting attended by an employee. meeting_type can be 'Team', 'Client', or 'Training'.
# Write a solution to find employees who are meeting-heavy - employees who spend more than 50% of their working time in meetings during any given week.
# Assume a standard work week is 40 hours
# Calculate total meeting hours per employee per week (Monday to Sunday)
# An employee is meeting-heavy if their weekly meeting hours > 20 hours (50% of 40 hours)
# Count how many weeks each employee was meeting-heavy
# Only include employees who were meeting-heavy for at least 2 weeks
# Return the result table ordered by the number of meeting-heavy weeks in descending order, then by employee name in ascending order.
# The result format is in the following example.
# Example:
# Input:
# employees table:
# +-------------+----------------+-------------+
# | employee_id | employee_name | department |
# +-------------+----------------+-------------+
# | 1 | Alice Johnson | Engineering |
# | 2 | Bob Smith | Marketing |
# | 3 | Carol Davis | Sales |
# | 4 | David Wilson | Engineering |
# | 5 | Emma Brown | HR |
# +-------------+----------------+-------------+
# meetings table:
# +------------+-------------+--------------+--------------+----------------+
# | meeting_id | employee_id | meeting_date | meeting_type | duration_hours |
# +------------+-------------+--------------+--------------+----------------+
# | 1 | 1 | 2023-06-05 | Team | 8.0 |
# | 2 | 1 | 2023-06-06 | Client | 6.0 |
# | 3 | 1 | 2023-06-07 | Training | 7.0 |
# | 4 | 1 | 2023-06-12 | Team | 12.0 |
# | 5 | 1 | 2023-06-13 | Client | 9.0 |
# | 6 | 2 | 2023-06-05 | Team | 15.0 |
# | 7 | 2 | 2023-06-06 | Client | 8.0 |
# | 8 | 2 | 2023-06-12 | Training | 10.0 |
# | 9 | 3 | 2023-06-05 | Team | 4.0 |
# | 10 | 3 | 2023-06-06 | Client | 3.0 |
# | 11 | 4 | 2023-06-05 | Team | 25.0 |
# | 12 | 4 | 2023-06-19 | Client | 22.0 |
# | 13 | 5 | 2023-06-05 | Training | 2.0 |
# +------------+-------------+--------------+--------------+----------------+
# Output:
# +-------------+----------------+-------------+---------------------+
# | employee_id | employee_name | department | meeting_heavy_weeks |
# +-------------+----------------+-------------+---------------------+
# | 1 | Alice Johnson | Engineering | 2 |
# | 4 | David Wilson | Engineering | 2 |
# +-------------+----------------+-------------+---------------------+
# Explanation:
# Alice Johnson (employee_id = 1):
# Week of June 5-11 (2023-06-05 to 2023-06-11): 8.0 + 6.0 + 7.0 = 21.0 hours (> 20 hours)
# Week of June 12-18 (2023-06-12 to 2023-06-18): 12.0 + 9.0 = 21.0 hours (> 20 hours)
# Meeting-heavy for 2 weeks
# David Wilson (employee_id = 4):
# Week of June 5-11: 25.0 hours (> 20 hours)
# Week of June 19-25: 22.0 hours (> 20 hours)
# Meeting-heavy for 2 weeks
# Employees not included:
# Bob Smith (employee_id = 2): Week of June 5-11: 15.0 + 8.0 = 23.0 hours (> 20), Week of June 12-18: 10.0 hours (< 20). Only 1 meeting-heavy week
# Carol Davis (employee_id = 3): Week of June 5-11: 4.0 + 3.0 = 7.0 hours (< 20). No meeting-heavy weeks
# Emma Brown (employee_id = 5): Week of June 5-11: 2.0 hours (< 20). No meeting-heavy weeks
# The result table is ordered by meeting_heavy_weeks in descending order, then by employee name in ascending order.
#
# Write your MySQL query statement below
WITH weekly_hours AS (
SELECT employee_id,
YEARWEEK(meeting_date, 1) AS week_num,
SUM(duration_hours) AS total_hours
FROM meetings
GROUP BY employee_id, YEARWEEK(meeting_date, 1)
),
heavy_weeks AS (
SELECT employee_id, COUNT(*) AS meeting_heavy_weeks
FROM weekly_hours
WHERE total_hours > 20
GROUP BY employee_id
HAVING COUNT(*) >= 2
)
SELECT e.employee_id, e.employee_name, e.department, h.meeting_heavy_weeks
FROM employees e
JOIN heavy_weeks h ON e.employee_id = h.employee_id
ORDER BY meeting_heavy_weeks DESC, e.employee_name ASC;