Given an integer array, nums, and an integer, k, determine and return the kth largest element in the array.
Note: The
kthlargest element is defined with respect to the array’s sorted order (descending), and does not necessarily correspond to thekthunique value.
Constraints:
1≤ k ≤ nums.length ≤103
−104≤ nums[i] ≤104
To find the kth largest element in an array, the main idea is to avoid sorting the entire array and instead focus only on the k largest elements encountered. As we scan through the array, we keep a collection that stores the k largest elements found so far. The smallest element in this collection is always the current candidate for the kth largest. A min heap is perfectly suited for this because it allows constant-time access to the smallest element while supporting efficient insertion and removal. The algorithm begins by inserting elements into the heap one by one; whenever the heap size exceeds k, the smallest element (the heap’s root) is removed, ...
Given an integer array, nums, and an integer, k, determine and return the kth largest element in the array.
Note: The
kthlargest element is defined with respect to the array’s sorted order (descending), and does not necessarily correspond to thekthunique value.
Constraints:
1≤ k ≤ nums.length ≤103
−104≤ nums[i] ≤104
To find the kth largest element in an array, the main idea is to avoid sorting the entire array and instead focus only on the k largest elements encountered. As we scan through the array, we keep a collection that stores the k largest elements found so far. The smallest element in this collection is always the current candidate for the kth largest. A min heap is perfectly suited for this because it allows constant-time access to the smallest element while supporting efficient insertion and removal. The algorithm begins by inserting elements into the heap one by one; whenever the heap size exceeds k, the smallest element (the heap’s root) is removed, ...