Most Popular Video Creator - Practice Coding Problems

🎥 Most Popular Video Creator

You're working as a data analyst for a video streaming platform similar to YouTube. Your task is to identify the most popular content creators based on their total view counts across all their videos.

Given three arrays:

creators[i] - the name of the creator who made the i-th video
ids[i] - the unique identifier of the i-th video
views[i] - the number of views the i-th video has received

Your Goal: Find the creator(s) with the highest total popularity (sum of all their video views) and identify their most popular video.

Special Rules:

If multiple creators tie for highest popularity, include all of them
If a creator has multiple videos with the same highest view count, choose the one with the lexicographically smallest video ID
Different videos can share the same ID (they're still considered separate videos)

Return a 2D array where each row contains [creator_name, most_popular_video_id] for each top creator.

Input & Output

example_1.py — Basic Case

$ Input: creators = ["alice","bob","alice","charlie"] ids = ["one","two","three","four"] views = [5,10,5,4]

› Output: [["alice","one"]]

💡 Note: Alice has total views of 5+5=10, Bob has 10 views, Charlie has 4 views. Alice has the highest total. Among Alice's videos, both have 5 views, but 'one' is lexicographically smaller than 'three'.

example_2.py — Multiple Winners

$ Input: creators = ["alice","alice","alice"] ids = ["a","b","c"] views = [1,2,2]

› Output: [["alice","b"]]

💡 Note: Alice is the only creator with total views of 5. Among her videos with max views (2), 'b' is lexicographically smaller than 'c'.

example_3.py — Tie Breaker

$ Input: creators = ["alice","bob","charlie"] ids = ["video1","video2","video3"] views = [10,10,10]

› Output: [["alice","video1"],["bob","video2"],["charlie","video3"]]

💡 Note: All creators have equal popularity (10 views each), so all are included in the result with their respective video IDs.

Constraints

n == creators.length == ids.length == views.length
1 ≤ n ≤ 10⁵
1 ≤ creators[i].length, ids[i].length ≤ 5
creators[i] and ids[i] consist of lowercase English letters only
0 ≤ views[i] ≤ 10⁵

Visualization

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Understanding the Visualization

Initialize Tracking

Set up data structures to monitor creator performance metrics

Process Video Stream

As each video data arrives, update the creator's total views and check if it's their new best video

Update Leaderboard

Track the highest total popularity and identify leading creators

Generate Report

Compile final results showing top creators and their most successful videos

Key Takeaway

🎯 Key Insight: By processing the video stream once and maintaining running statistics, we can efficiently identify the most successful creators and their top-performing content in linear time.

Asked in

G Google 45 a Amazon 38 f Meta 32 N Netflix 28

The optimal solution uses a one-pass hash table approach with O(n) time complexity. We maintain two hash maps: one tracking each creator's total views and another tracking their best video. During a single iteration through the input, we update both statistics simultaneously while keeping track of the maximum popularity seen so far. Finally, we collect all creators with maximum popularity and return their best videos.

Common Approaches

Approach	Time	Space	Notes
✓ One-Pass Hash Table (Optimal)	O(n)	O(k)	Build creator statistics and find winners in a single pass through the data
Brute Force (Multiple Passes)	O(n² × k)	O(k)	Calculate each creator's total views separately, then find maximum and best videos

One-Pass Hash Table (Optimal) — Algorithm Steps

Initialize hash maps for creator total views and their best video info
Iterate through all videos once, updating each creator's total views
For each video, check if it's the creator's new best video (higher views or lexicographically smaller ID)
Track the maximum popularity seen so far
Collect all creators with maximum popularity and return their best videos

Visualization

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Step-by-Step Walkthrough

Initialize Hash Maps

Create maps to track total views and best video for each creator

Process Each Video

Update creator stats and track maximum popularity in real-time

Collect Winners

Gather all creators with maximum popularity and their best videos

Code -

solution.c — C

#include <stdio.h>
#include <stdlib.h>
#include <string.h>

// C implementation would require complex hash table implementation
// This is a simplified structure showing the approach
struct CreatorStats {
    char* name;
    long long totalViews;
    int bestVideoIndex;
    int bestVideoViews;
};

char*** mostPopularCreator(char** creators, char** ids, int* views, int n, int* returnSize, int** returnColumnSizes) {
    // Complex C implementation would go here
    *returnSize = 0;
    return NULL;
}

int main() {
    // Parse input and call solution
    return 0;
}

Time & Space Complexity

Time Complexity

⏱️

O(n)

Single pass through n videos, with constant time hash map operations

✓ Linear Growth

Space Complexity

O(k)

Where k is the number of unique creators, for storing creator statistics

✓ Linear Space

95.0K Views

Medium Frequency

~15 min Avg. Time

2.8K Likes

Ln 1, Col 1

Smart Actions

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🎥 Most Popular Video Creator

Input & Output

Constraints

Visualization

Related Problems

Common Approaches

One-Pass Hash Table (Optimal) — Algorithm Steps

Visualization

Code -

Time & Space Complexity

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