Find the Kth Largest Integer in the Array

Find the Kth Largest Integer in the Array - Problem

Array String Divide and Conquer Sorting Heap (Priority Queue) Quickselect Medium

You are given an array of strings nums and an integer k. Each string in nums represents an integer without leading zeros.

Return the string that represents the kth largest integer in nums.

Note: Duplicate numbers should be counted distinctly. For example, if nums is ["1","2","2"], "2" is the first largest integer, "2" is the second-largest integer, and "1" is the third-largest integer.

Input & Output

Example 1 — Basic Case

$ Input: nums = ["3","6","7","10"], k = 4

› Output: "3"

💡 Note: Sorted in descending order: ["10","7","6","3"]. The 4th largest is "3".

Example 2 — With Duplicates

$ Input: nums = ["2","21","12","1"], k = 3

› Output: "2"

💡 Note: Sorted: ["21","12","2","1"]. The 3rd largest is "2".

Example 3 — Large Numbers

$ Input: nums = ["1","2","2"], k = 2

› Output: "2"

💡 Note: Sorted: ["2","2","1"]. Both "2"s are counted distinctly, so 2nd largest is "2".

Constraints

1 ≤ k ≤ nums.length ≤ 10⁴
1 ≤ nums[i].length ≤ 100
nums[i] consists of only digits
nums[i] will not have any leading zeros

Visualization

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Asked in

a Amazon 15 G Google 12 f Facebook 8 M Microsoft 6

The key insight is that string numbers can be compared directly using length and lexicographic order. For same-sign numbers, longer strings represent larger values, and for same-length strings, lexicographic comparison works. Best approach uses custom string comparator to sort efficiently. Time: O(n log n), Space: O(1)

Common Approaches

✓ Frequency Count

⏱️ Time: N/A Space: N/A

Custom String Comparator

⏱️ Time: O(n log n) Space: O(1)

Instead of converting to integers, use a custom comparator that compares string numbers directly. For same-sign numbers, longer strings are larger, and for same length, lexicographic comparison works.

Min Heap Approach

⏱️ Time: O(n log k) Space: O(k)

Maintain a min heap of size k. For each element, if heap size < k, add element. Otherwise, if current element is larger than heap's minimum, replace the minimum.

Sort All Elements

⏱️ Time: O(n log n) Space: O(n)

Convert all string numbers to integers for proper comparison, sort the entire array in descending order, then return the element at index k-1.

Algorithm Steps — Algorithm Steps

Code -

solution.c — C

Time & Space Complexity

Time Complexity

⏱️

⚡ Linearithmic

Space Complexity

✓ Linear Space

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Medium Frequency

~25 min Avg. Time

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Smart Actions

💡 Explanation

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