Top K Elements This is a great example of using a min-heap (PriorityQueue) with a HashMap to solve the “Top K Frequent Elements” problem — a popular interview question. Let’s make it memorable by breaking it down into a story and then walking line by line. 🧠The Concept Story — “Finding the Noisy Guests” Imagine you’re throwing a party 🥳, and guests keep talking (numbers appear multiple times). You want to find the top K noisiest guests — i.e., the ones who talk the most (appear most frequently). You have two helpers: The Secretary (HashMap) — keeps count of how many times each guest talks. The Gatekeeper (PriorityQueue / Min-Heap) — only allows the top K noisiest guests inside the “VIP room”. 🧩 Code Walkthrough (in human language) Step 1: Count how often each number appears Map < Integer , Integer > numFrequencyMap = new HashMap < > ( ) ; for ( int n : arr ) numFrequencyMap . put ( n , numFrequencyMap . getOrDefault ( n , 0 ) + 1 ) ; Think of num...