K Closest Points to Origin — The Heap Insight скачать в хорошем качестве

K Closest Points to Origin — The Heap Insight

In this video, we solve the K Closest Points to Origin problem and focus on the intuition behind using a Heap. Instead of jumping to code, we understand: Why a heap is the right data structure Why we keep the heap size limited to k How distance comparison works without square roots How to explain this clearly in interviews This video follows the Clarity Before Code approach — understanding logic before coding. 00:00 Problem Overview 01:05 Brute Force Approach 02:20 Key Insight 07:30 Heap-Based Solution 11:15 Time & Space Complexity 🧠 Topics covered: Distance calculation Min Heap vs Max Heap Dry run Time & Space Complexity Language: C++