LeetCode #1741 — EASY

Find Total Time Spent by Each Employee

Build confidence with an intuition-first walkthrough focused on core interview patterns fundamentals.

The Problem

Problem Statement

Table: Employees

+-------------+------+
| Column Name | Type |
+-------------+------+
| emp_id      | int  |
| event_day   | date |
| in_time     | int  |
| out_time    | int  |
+-------------+------+
(emp_id, event_day, in_time) is the primary key (combinations of columns with unique values) of this table.
The table shows the employees' entries and exits in an office.
event_day is the day at which this event happened, in_time is the minute at which the employee entered the office, and out_time is the minute at which they left the office.
in_time and out_time are between 1 and 1440.
It is guaranteed that no two events on the same day intersect in time, and in_time < out_time.

Write a solution to calculate the total time in minutes spent by each employee on each day at the office. Note that within one day, an employee can enter and leave more than once. The time spent in the office for a single entry is out_time - in_time.

Return the result table in any order.

The result format is in the following example.

Example 1:

Input: 
Employees table:
+--------+------------+---------+----------+
| emp_id | event_day  | in_time | out_time |
+--------+------------+---------+----------+
| 1      | 2020-11-28 | 4       | 32       |
| 1      | 2020-11-28 | 55      | 200      |
| 1      | 2020-12-03 | 1       | 42       |
| 2      | 2020-11-28 | 3       | 33       |
| 2      | 2020-12-09 | 47      | 74       |
+--------+------------+---------+----------+
Output: 
+------------+--------+------------+
| day        | emp_id | total_time |
+------------+--------+------------+
| 2020-11-28 | 1      | 173        |
| 2020-11-28 | 2      | 30         |
| 2020-12-03 | 1      | 41         |
| 2020-12-09 | 2      | 27         |
+------------+--------+------------+
Explanation: 
Employee 1 has three events: two on day 2020-11-28 with a total of (32 - 4) + (200 - 55) = 173, and one on day 2020-12-03 with a total of (42 - 1) = 41.
Employee 2 has two events: one on day 2020-11-28 with a total of (33 - 3) = 30, and one on day 2020-12-09 with a total of (74 - 47) = 27.

Step 01

Brute Force Baseline

Problem summary: Table: Employees +-------------+------+ | Column Name | Type | +-------------+------+ | emp_id | int | | event_day | date | | in_time | int | | out_time | int | +-------------+------+ (emp_id, event_day, in_time) is the primary key (combinations of columns with unique values) of this table. The table shows the employees' entries and exits in an office. event_day is the day at which this event happened, in_time is the minute at which the employee entered the office, and out_time is the minute at which they left the office. in_time and out_time are between 1 and 1440. It is guaranteed that no two events on the same day intersect in time, and in_time < out_time. Write a solution to calculate the total time in minutes spent by each employee on each day at the office. Note that within one day, an employee can enter and leave more than once. The time spent in the office for a single entry is

Baseline thinking

Start with the most direct exhaustive search. That gives a correctness anchor before optimizing.

Pattern signal: General problem-solving

Example 1

{"headers":{"Employees":["emp_id","event_day","in_time","out_time"]},"rows":{"Employees":[["1","2020-11-28","4","32"],["1","2020-11-28","55","200"],["1","2020-12-3","1","42"],["2","2020-11-28","3","33"],["2","2020-12-9","47","74"]]}}

Step 02

Core Insight

What unlocks the optimal approach

No official hints in dataset. Start from constraints and look for a monotonic or reusable state.

Interview move: turn each hint into an invariant you can check after every iteration/recursion step.

Step 03

Algorithm Walkthrough

Iteration Checklist

Define state (indices, window, stack, map, DP cell, or recursion frame).
Apply one transition step and update the invariant.
Record answer candidate when condition is met.
Continue until all input is consumed.

Use the first example testcase as your mental trace to verify each transition.

Step 04

Edge Cases

Minimum Input

Single element / shortest valid input

Validate boundary behavior before entering the main loop or recursion.

Duplicates & Repeats

Repeated values / repeated states

Decide whether duplicates should be merged, skipped, or counted explicitly.

Extreme Constraints

Upper-end input sizes

Re-check complexity target against constraints to avoid time-limit issues.

Invalid / Corner Shape

Empty collections, zeros, or disconnected structures

Handle special-case structure before the core algorithm path.

Step 05

Full Annotated Code

Source-backed implementations are provided below for direct study and interview prep.

// Accepted solution for LeetCode #1741: Find Total Time Spent by Each Employee
// Auto-generated Java example from rust.
class Solution {
    public void exampleSolution() {
    }
}
// Reference (rust):
// // Accepted solution for LeetCode #1741: Find Total Time Spent by Each Employee
// pub fn sql_example() -> &'static str {
//     r#"
// -- Accepted solution for LeetCode #1741: Find Total Time Spent by Each Employee
// # Write your MySQL query statement below
// SELECT event_day AS day, emp_id, SUM(out_time - in_time) AS total_time
// FROM Employees
// GROUP BY 1, 2;
// "#
// }

// Accepted solution for LeetCode #1741: Find Total Time Spent by Each Employee
// Auto-generated Go example from rust.
func exampleSolution() {
}
// Reference (rust):
// // Accepted solution for LeetCode #1741: Find Total Time Spent by Each Employee
// pub fn sql_example() -> &'static str {
//     r#"
// -- Accepted solution for LeetCode #1741: Find Total Time Spent by Each Employee
// # Write your MySQL query statement below
// SELECT event_day AS day, emp_id, SUM(out_time - in_time) AS total_time
// FROM Employees
// GROUP BY 1, 2;
// "#
// }

# Accepted solution for LeetCode #1741: Find Total Time Spent by Each Employee
# Auto-generated Python example from rust.
def example_solution() -> None:
    return
# Reference (rust):
# // Accepted solution for LeetCode #1741: Find Total Time Spent by Each Employee
# pub fn sql_example() -> &'static str {
#     r#"
# -- Accepted solution for LeetCode #1741: Find Total Time Spent by Each Employee
# # Write your MySQL query statement below
# SELECT event_day AS day, emp_id, SUM(out_time - in_time) AS total_time
# FROM Employees
# GROUP BY 1, 2;
# "#
# }

// Accepted solution for LeetCode #1741: Find Total Time Spent by Each Employee
pub fn sql_example() -> &'static str {
    r#"
-- Accepted solution for LeetCode #1741: Find Total Time Spent by Each Employee
# Write your MySQL query statement below
SELECT event_day AS day, emp_id, SUM(out_time - in_time) AS total_time
FROM Employees
GROUP BY 1, 2;
"#
}

// Accepted solution for LeetCode #1741: Find Total Time Spent by Each Employee
// Auto-generated TypeScript example from rust.
function exampleSolution(): void {
}
// Reference (rust):
// // Accepted solution for LeetCode #1741: Find Total Time Spent by Each Employee
// pub fn sql_example() -> &'static str {
//     r#"
// -- Accepted solution for LeetCode #1741: Find Total Time Spent by Each Employee
// # Write your MySQL query statement below
// SELECT event_day AS day, emp_id, SUM(out_time - in_time) AS total_time
// FROM Employees
// GROUP BY 1, 2;
// "#
// }

Step 06

Interactive Study Demo

Use this to step through a reusable interview workflow for this problem.

Custom checkpoints (one per line)

Press Step or Run All to begin.

Step 07

Complexity Analysis

Time

O(n)

Space

O(1)

Approach Breakdown

BRUTE FORCE

O(n²) time

O(1) space

Two nested loops check every pair or subarray. The outer loop fixes a starting point, the inner loop extends or searches. For n elements this gives up to n²/2 operations. No extra space, but the quadratic time is prohibitive for large inputs.

OPTIMIZED

O(n) time

O(1) space

Most array problems have an O(n²) brute force (nested loops) and an O(n) optimal (single pass with clever state tracking). The key is identifying what information to maintain as you scan: a running max, a prefix sum, a hash map of seen values, or two pointers.

Shortcut: If you are using nested loops on an array, there is almost always an O(n) solution. Look for the right auxiliary state.

Coach Notes

Common Mistakes

Review these before coding to avoid predictable interview regressions.

Off-by-one on range boundaries

Wrong move: Loop endpoints miss first/last candidate.

Usually fails on: Fails on minimal arrays and exact-boundary answers.

Fix: Re-derive loops from inclusive/exclusive ranges before coding.