Kth Largest Element in an Array

// C — nth_element approach (quickselect)
int compare(const void* a, const void* b) { return *(int*)b - *(int*)a; }
int findKthLargest(int* nums, int n, int k) {
    qsort(nums, n, sizeof(int), compare);
    return nums[k-1];
}

// C++ — nth_element O(n) average
int findKthLargest(vector<int>& nums, int k) {
    nth_element(nums.begin(), nums.begin() + k - 1, nums.end(), greater<int>());
    return nums[k-1];
}
// Or min-heap:
int findKthLargestHeap(vector<int>& nums, int k) {
    priority_queue<int, vector<int>, greater<int>> minH;
    for (int n : nums) {
        minH.push(n);
        if ((int)minH.size() > k) minH.pop();
    }
    return minH.top();
}

// Java — min-heap
public int findKthLargest(int[] nums, int k) {
    PriorityQueue<Integer> minH = new PriorityQueue<>();
    for (int n : nums) {
        minH.offer(n);
        if (minH.size() > k) minH.poll();
    }
    return minH.peek();
}

// JavaScript — sort descending
function findKthLargest(nums, k) {
    nums.sort((a, b) => b - a);
    return nums[k - 1];
}

# Python — heapq.nlargest
import heapq

def findKthLargest(nums, k):
    return heapq.nlargest(k, nums)[-1]

# Or min-heap:
def findKthLargestHeap(nums, k):
    heap = nums[:k]
    heapq.heapify(heap)
    for n in nums[k:]:
        if n > heap[0]:
            heapq.heapreplace(heap, n)
    return heap[0]