Kth Largest Element in an Array | Heap | DSA Interview Problem
In this video, we solve the Kth Largest Element in an Array problem using multiple optimal approaches, Heap (Priority Queue).
This is one of the most frequently asked DSA interview questions in FAANG and top product-based companies, testing your understanding of selection algorithms, heaps, and partition logic.
🚀 What you’ll learn in this video:
Brute force vs optimized approaches
Heap (Min Heap / Max Heap) approach
Time & space complexity analysis
🎯 Interview Relevance:
Asked in Amazon, Google, Microsoft, Meta
Core problem for Arrays, Heaps, and Divide & Conquer
Important for SDE-I, SDE-II, and backend engineers
📌 If you’re preparing for coding interviews or competitive programming, this problem is mandatory practice.
📘 DSA Sheet Link:
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Playlist : • DSA in Java || Beginner to Advance
Code :https://github.com/maheshahirwar/dsa-...
⏱️ Timestamps:
00:00 - Introduction
00:11 - Problem Explained with Examples
02:31 - Optimized Approach using Priority Queue O(N log K)
05:52 - Code implementation using Priority Queue
07:42 - Conclusion
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