LeetCode #1789 — EASY

Primary Department for Each Employee

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

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The Problem

Problem Statement

Table: Employee

+---------------+---------+
| Column Name   |  Type   |
+---------------+---------+
| employee_id   | int     |
| department_id | int     |
| primary_flag  | varchar |
+---------------+---------+
(employee_id, department_id) is the primary key (combination of columns with unique values) for this table.
employee_id is the id of the employee.
department_id is the id of the department to which the employee belongs.
primary_flag is an ENUM (category) of type ('Y', 'N'). If the flag is 'Y', the department is the primary department for the employee. If the flag is 'N', the department is not the primary.

Employees can belong to multiple departments. When the employee joins other departments, they need to decide which department is their primary department. Note that when an employee belongs to only one department, their primary column is 'N'.

Write a solution to report all the employees with their primary department. For employees who belong to one department, report their only department.

Return the result table in any order.

The result format is in the following example.

Example 1:

Input: 
Employee table:
+-------------+---------------+--------------+
| employee_id | department_id | primary_flag |
+-------------+---------------+--------------+
| 1           | 1             | N            |
| 2           | 1             | Y            |
| 2           | 2             | N            |
| 3           | 3             | N            |
| 4           | 2             | N            |
| 4           | 3             | Y            |
| 4           | 4             | N            |
+-------------+---------------+--------------+
Output: 
+-------------+---------------+
| employee_id | department_id |
+-------------+---------------+
| 1           | 1             |
| 2           | 1             |
| 3           | 3             |
| 4           | 3             |
+-------------+---------------+
Explanation: 
- The Primary department for employee 1 is 1.
- The Primary department for employee 2 is 1.
- The Primary department for employee 3 is 3.
- The Primary department for employee 4 is 3.

Roadmap

  1. Brute Force Baseline
  2. Core Insight
  3. Algorithm Walkthrough
  4. Edge Cases
  5. Full Annotated Code
  6. Interactive Study Demo
  7. Complexity Analysis
Step 01

Brute Force Baseline

Problem summary: Table: Employee +---------------+---------+ | Column Name | Type | +---------------+---------+ | employee_id | int | | department_id | int | | primary_flag | varchar | +---------------+---------+ (employee_id, department_id) is the primary key (combination of columns with unique values) for this table. employee_id is the id of the employee. department_id is the id of the department to which the employee belongs. primary_flag is an ENUM (category) of type ('Y', 'N'). If the flag is 'Y', the department is the primary department for the employee. If the flag is 'N', the department is not the primary. Employees can belong to multiple departments. When the employee joins other departments, they need to decide which department is their primary department. Note that when an employee belongs to only one department, their primary column is 'N'. Write a solution to report all the employees with

Baseline thinking

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

Pattern signal: General problem-solving

Example 1

{"headers":{"Employee":["employee_id","department_id","primary_flag"]},"rows":{"Employee":[["1","1","N"],["2","1","Y"],["2","2","N"],["3","3","N"],["4","2","N"],["4","3","Y"],["4","4","N"]]}}
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

  1. Define state (indices, window, stack, map, DP cell, or recursion frame).
  2. Apply one transition step and update the invariant.
  3. Record answer candidate when condition is met.
  4. 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 #1789: Primary Department for Each Employee
// Auto-generated Java example from rust.
class Solution {
    public void exampleSolution() {
    }
}
// Reference (rust):
// // Accepted solution for LeetCode #1789: Primary Department for Each Employee
// pub fn sql_example() -> &'static str {
//     r#"
// -- Accepted solution for LeetCode #1789: Primary Department for Each Employee
// # Write your MySQL query statement below
// SELECT employee_id, department_id
// FROM Employee
// WHERE primary_flag = 'Y'
// UNION
// SELECT employee_id, department_id
// FROM Employee
// GROUP BY 1
// HAVING COUNT(1) = 1;
// "#
// }
Step 06

Interactive Study Demo

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

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.