Find Followers Count - Practice Coding Problems

Find Followers Count - Problem

Database Easy

Social Media Followers Analysis

You're working as a data analyst for a popular social media platform! Your task is to help the platform understand user engagement by calculating how many followers each user has.

You have access to the Followers table which records every follower relationship on the platform. Each row represents one user following another user.

Table Structure:

Column Name	Type	Description
user_id	int	The ID of the user being followed
follower_id	int	The ID of the user who is following

Your Mission: Write a SQL query that returns each user and their total follower count, ordered by user_id in ascending order.

Example: If user 123 has 5 people following them, your result should show user_id: 123, followers_count: 5

Input & Output

basic_followers.sql — Basic Case

$ Input: Followers table: +--------+-----------+ |user_id |follower_id| +--------+-----------+ | 1 | 101 | | 2 | 102 | | 1 | 103 | | 2 | 104 | | 1 | 105 | +--------+-----------+

› Output: +--------+----------------+ |user_id |followers_count | +--------+----------------+ | 1 | 3 | | 2 | 2 | +--------+----------------+

💡 Note: User 1 has 3 followers (101, 103, 105) and User 2 has 2 followers (102, 104). Results are ordered by user_id ascending.

single_follower.sql — Single Followers

$ Input: Followers table: +--------+-----------+ |user_id |follower_id| +--------+-----------+ | 10 | 20 | | 11 | 21 | | 12 | 22 | +--------+-----------+

› Output: +--------+----------------+ |user_id |followers_count | +--------+----------------+ | 10 | 1 | | 11 | 1 | | 12 | 1 | +--------+----------------+

💡 Note: Each user has exactly one follower. The GROUP BY counts one row per user_id.

popular_user.sql — One Very Popular User

$ Input: Followers table: +--------+-----------+ |user_id |follower_id| +--------+-----------+ | 1 | 100 | | 1 | 101 | | 1 | 102 | | 1 | 103 | | 1 | 104 | | 5 | 200 | +--------+-----------+

› Output: +--------+----------------+ |user_id |followers_count | +--------+----------------+ | 1 | 5 | | 5 | 1 | +--------+----------------+

💡 Note: User 1 is very popular with 5 followers, while User 5 has only 1 follower. This tests the aggregation with uneven distribution.

Visualization

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Single Scan: Read each follower relationship once2. Auto-Group: SQL automatically groups by celebrity (user_id)3. Count: COUNT(follower_id) gives us the magic numbers4. Sort: ORDER BY user_id for clean results⚡ Time: O(n) | Space: O(k) where k = unique users

Understanding the Visualization

Scan Sign-up Sheet

Read through the follower relationships once

Group by Celebrity

Organize fans by which celebrity they follow

Count Each Group

Count fans in each celebrity group

Sort by Celebrity ID

Order results by celebrity ID ascending

Key Takeaway

🎯 Key Insight: SQL's GROUP BY is like having a super-efficient assistant who can sort and count in one pass, making follower analytics blazingly fast!

Time & Space Complexity

Time Complexity

⏱️

O(n)

Single scan through all n rows in the table, plus O(n log n) for sorting by user_id

✓ Linear Growth

Space Complexity

O(k)

Where k is the number of distinct users (for storing group counts and sorting)

✓ Linear Space

Constraints

1 ≤ user_id, follower_id ≤ 10⁹
1 ≤ number of rows in Followers table ≤ 10⁴
Each (user_id, follower_id) pair is unique
A user cannot follow themselves (user_id ≠ follower_id)

Asked in

f Meta 45 📷 Instagram 38 🐦 Twitter 35 in LinkedIn 25 🎵 TikTok 22

The optimal solution uses GROUP BY aggregation to count followers in a single table scan. By grouping rows by user_id and using COUNT(follower_id), we efficiently calculate follower counts with O(n) time complexity. The key insight is leveraging SQL's built-in aggregation optimization rather than using inefficient subqueries.

Common Approaches

Approach	Time	Space	Notes
✓ GROUP BY Aggregation (Optimal)	O(n)	O(k)	Use GROUP BY to count followers in a single table scan
Subquery Approach (Inefficient)	O(n²)	O(1)	Use a subquery to count followers for each user individually

GROUP BY Aggregation (Optimal) — Algorithm Steps

Scan the Followers table once
Group all rows by user_id (users being followed)
Count the number of rows in each group (follower_id entries)
Order the results by user_id in ascending order

Visualization

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Step-by-Step Walkthrough

Single Table Scan

Read each row once and group by user_id

Count Accumulation

Maintain running count for each group

Sort and Return

Sort groups by user_id and return results

Code -

solution.c — C

// SQL Solution (GROUP BY Approach - Optimal)
#include <stdio.h>

int main() {
    char* selectQuery = """
SELECT \n"
"    user_id,\n"
"    COUNT(follower_id) as followers_count\n"
"FROM Followers\n"
"GROUP BY user_id\n"
"ORDER BY user_id ASC;\n";
    
    printf("%s", selectQuery);
    return 0;
}

Time & Space Complexity

Time Complexity

⏱️

O(n)

Single scan through all n rows in the table, plus O(n log n) for sorting by user_id

✓ Linear Growth

Space Complexity

O(k)

Where k is the number of distinct users (for storing group counts and sorting)

✓ Linear Space

Constraints

1 ≤ user_id, follower_id ≤ 10⁹
1 ≤ number of rows in Followers table ≤ 10⁴
Each (user_id, follower_id) pair is unique
A user cannot follow themselves (user_id ≠ follower_id)

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Input & Output

Visualization

Time & Space Complexity

Related Problems

Constraints

Common Approaches

GROUP BY Aggregation (Optimal) — Algorithm Steps

Visualization

Code -

Time & Space Complexity

Constraints

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