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Largest Subarray Length K

Easy
25%
Updated 8/1/2025

Asked by 1 Company

Largest Subarray Length K

1. What is this problem about?

The Largest Subarray Length K coding problem involves finding the lexicographically largest subarray of a fixed length k from a given array of distinct integers. A subarray is "lexicographically larger" than another if, at the first position where they differ, the first subarray has a larger element.

2. Why is this asked in interviews?

Google frequently uses this problem to test a candidate's ability to simplify complex-sounding requirements. While "lexicographical comparison" might sound like it requires comparing all possible subarrays, the "fixed length K" constraint allows for a much simpler greedy observation. It evaluates your ability to find the most efficient starting position for the subarray.

3. Algorithmic pattern used

This utilizes the Array and Greedy interview pattern. Because all subarrays have the same length k, the lexicographical order is determined entirely by the elements from left to right. To make the subarray as large as possible, we simply need to find the largest possible first element. The range of possible starting indices is from 0 to n - k. We scan this range and pick the index with the maximum value.

4. Example explanation

Array: [1, 4, 5, 2, 3], k = 3. Possible starting indices (where a subarray of length 3 can start):

  • Index 0: [1, 4, 5]
  • Index 1: [4, 5, 2]
  • Index 2: [5, 2, 3] Scanning the starting elements: 1, 4, and 5. 5 is the largest. Resulting subarray: [5, 2, 3].

5. Common mistakes candidates make

A common mistake is trying to compare entire subarrays, which leads to O(N * K) complexity. Another error is not correctly identifying the range of valid starting indices, potentially leading to an "index out of bounds" error or a subarray shorter than k. Since the integers are distinct, the greedy approach is even simpler as there are no "ties" to break.

6. Interview preparation tip

In "Array, Greedy interview pattern" problems, always look for the most "influential" element. For lexicographical problems, the first element is always the most influential. If you can maximize the first element, you've already made the best possible greedy choice.

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