Popularity Percentage - Practice Coding Problems

Popularity Percentage - Problem

Database Hard

Given a Friends table containing friendship relationships, calculate the popularity percentage for each user on Meta/Facebook.

The popularity percentage is defined as:

Total number of friends the user has
Divided by total number of users on the platform
Multiplied by 100 and rounded to 2 decimal places

Return results ordered by user1 in ascending order.

Note: Friendship is bidirectional - if user A is friends with user B, then user B is also friends with user A.

Table Schema

Friends

Column Name	Type	Description
`user1` PK	int	First user in friendship pair
`user2` PK	int	Second user in friendship pair

Primary Key: (user1, user2)

Note: Each row represents a bidirectional friendship between user1 and user2

Input & Output

Example 1 — Basic Friendship Network

Input Table:

user1	user2
1	2
1	3
2	3

Output:

user1	percentage
1	66.67
2	66.67
3	66.67

💡 Note:

There are 3 total users (1, 2, 3). Each user has 2 friends:

User 1 is friends with users 2 and 3
User 2 is friends with users 1 and 3
User 3 is friends with users 1 and 2

Popularity percentage = (2 friends / 3 total users) × 100 = 66.67%

Example 2 — Unequal Popularity

Input Table:

user1	user2
1	2
1	3
1	4

Output:

user1	percentage
1	75
2	25
3	25
4	25

💡 Note:

There are 4 total users. User 1 has 3 friends (75.00%), while users 2, 3, and 4 each have only 1 friend (25.00%).

Constraints

1 ≤ user1, user2 ≤ 1000
user1 ≠ user2
All friendships are unique pairs
Friendship is bidirectional

Visualization

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Understanding the Visualization

Input

Friendship pairs table

Union

Create bidirectional relationships

Group & Calculate

Count friends and compute percentages

Key Takeaway

🎯 Key Insight: Use UNION ALL to handle bidirectional relationships in social network data

Asked in

M Meta 28 G Google 15 A Amazon 12

Use UNION ALL to create bidirectional friendship pairs, then GROUP BY to count friends per user and calculate percentages with ROUND().

Table Schema

Friends

Column Name	Type	Description
`user1` PK	int	First user in friendship pair
`user2` PK	int	Second user in friendship pair

Primary Key: (user1, user2)

Note: Each row represents a bidirectional friendship between user1 and user2

Common Approaches

Approach	Time	Space	Notes
✓ Union and Group By Approach	O(n log n)	O(n)	UNION both directions of friendship, then GROUP BY to count friends per user

Union and Group By Approach — Algorithm Steps

Step 1: UNION user1 and user2 columns to get all user-friend pairs
Step 2: GROUP BY user to count total friends per user
Step 3: Calculate percentage using total user count and ROUND to 2 decimal places

Visualization

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Step-by-Step Walkthrough

Union

Create both directions of friendship

Group

Count friends per user

Calculate

Compute percentages

Code -

solution.c — C

Time & Space Complexity

Time Complexity

⏱️

O(n log n)

UNION and GROUP BY operations with sorting

⚡ Linearithmic

Space Complexity

O(n)

Temporary storage for UNION results

⚡ Linearithmic Space

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Smart Actions

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Table Schema

Input & Output

Constraints

Visualization

Related Problems

Table Schema

Common Approaches

Union and Group By Approach — Algorithm Steps

Visualization

Code -

Time & Space Complexity

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