Is Kth Largest Element in an Array easy or hard?

Kth Largest Element in an Array is generally classified as a medium difficulty problem. The heap solution is straightforward, but recognizing that Quickselect can reduce the complexity to average O(n) requires deeper algorithm knowledge.

How to solve Kth Largest Element in an Array in O(n)?

Use the Quickselect algorithm. Partition the array around a pivot and check the pivot's final index. Compare it with the target index n - k, then recursively search only the relevant partition. Because each step discards roughly half of the remaining elements on average, the expected running time becomes O(n).

Kth Largest Element in an Array Python or Java solution?

Python solutions typically use the heapq library to maintain a min-heap of size k, giving O(n log k) time complexity. Java implementations often use PriorityQueue for the same approach. Quickselect can also be implemented in both languages using in-place partitioning for average O(n) performance.

What is the best approach for Kth Largest Element in an Array?

Quickselect is generally considered the best approach because it finds the kth element in average O(n) time without sorting the entire array. It partitions the array similar to QuickSort and recursively searches only the side containing the target index. A min-heap approach is also popular in interviews because it is simpler and guarantees O(n log k) time.

Is Kth Largest Element in an Array asked at Google/Amazon/Meta?

Kth Largest Element in an Array is a common interview question at companies like Amazon, Google, Meta, and Microsoft. It tests knowledge of heaps, partitioning, and selection algorithms such as Quickselect. Variants also appear in streaming and top-k problems.

What data structure is used in Kth Largest Element in an Array?

The most common data structure used is a min-heap (priority queue). The heap keeps track of the top k largest elements while scanning the array. Quickselect solutions rely more on array partitioning rather than additional data structures.

What is the time complexity of Kth Largest Element in an Array?

Time complexity depends on the approach used. A min-heap solution runs in O(n log k) time with O(k) space. The Quickselect algorithm runs in average O(n) time and O(1) extra space, though the worst case can degrade to O(n²) if pivot selection is poor.

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215. Kth Largest Element in an Array

Medium

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215. Kth Largest Element in an Array

Medium68.8% Acceptance

Array Divide and Conquer Sorting Heap (Priority Queue)Quickselect

Given an integer array nums and an integer k, return the k^th largest element in the array.

Note that it is the k^th largest element in the sorted order, not the k^th distinct element.

Can you solve it without sorting?

Example 1:

Input: nums = [3,2,1,5,6,4], k = 2
Output: 5

Example 2:

Input: nums = [3,2,3,1,2,4,5,5,6], k = 4
Output: 4

Constraints:

1 <= k <= nums.length <= 10⁵
-10⁴ <= nums[i] <= 10⁴

Asked by 41 companies