Heaps and Priority Queues

Lesson Overview

Welcome to our exploration of the intriguing worlds of heaps and priority queues . These are powerful data structures used extensively across a range of applications, from job scheduling systems to modeling the stock market. Heaps can efficiently solve problems involving intervals, nth largest elements, and even sorting. In Kotlin, we primarily use the PriorityQueue class from the java.util package to work with heaps .

Quick Overview & Motivation

O(\log n)

What's Next: Practice!

Let's plunge into the exercises, trusting that the best way to learn is by doing. As we solve various problems, you'll build a solid understanding of how these powerful tools can be employed to simplify complex tasks. This will not only prepare you for your interviews but also cultivate a mindset for problem-solving. Welcome aboard!

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import java.util.PriorityQueue fun findKLargest(nums: IntArray, k: Int): List<Int> { // Use a Min-Heap to keep track of the k largest elements seen so far. val minHeap = PriorityQueue<Int>() for (num in nums) { minHeap.add(num) // If the heap exceeds size k, remove the smallest element. // This keeps only the largest k elements in the heap. if (minHeap.size > k) { minHeap.poll() } } // Convert to a list and sort descending for the final result return minHeap.toList().sortedDescending() } fun main() { val nums = intArrayOf(3, 2, 1, 5, 6, 4) val k = 2 println(findKLargest(nums, k)) // Output: [6, 5] }