#67 Medium Time O(n) Space O(1) Animated

Kth Largest Element in an Array

Find the kth largest element in an unsorted array.

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1 Predict
2 Trace
3 Explain
4 Implement

Pattern Priority queue for the next best choice

Keep only candidates that may become the next answer, ordered by the priority that matters.

Approach: Min-Heap

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Core Insight

Keep only candidates that may become the next answer, ordered by the priority that matters.

Common Pitfall

Push only meaningful candidates and remove stale entries before trusting the root.

Description

Find the kth largest element in an unsorted array.

Constraints

Time Complexity: O(n)
Space Complexity: O(1)

Solution — Min-Heap

TimeO(n) SpaceO(1)

Implementation Plan

Translate the invariant into these small, testable moves.

Choose the priority key.
Push initial candidates.
Pop the best valid candidate.
Add newly eligible candidates and repeat.

def findKthLargest(nums, k):
    # Min-Heap of size k
    heap = nums[:k]
    heapq.heapify(heap)
    
    for n in nums[k:]:
        if n > heap[0]:
            heapq.heappop(heap)
            heapq.heappush(heap, n)
            
    return heap[0]

K Closest Points to Origin

Task Scheduler

Kth Largest Element in an Array

Steps

Description

Constraints

Tags

Solution — Min-Heap