Maximum Sum of Distinct Subarrays With Length K
Asked at Walmart
Problem
Given an integer array nums and an integer k, find the maximum sum of a subarray of length k where all elements are distinct. If no such subarray exists, return 0. A subarray is a contiguous non-empty sequence of elements within an array.
Asked At
| Company | Difficulty | |
|---|---|---|
| Walmart | MEDIUM | View all Walmart questions → |
How to Think About It
Brute force: check every subarray of length k, verify uniqueness with a set, and track the maximum sum.
Optimize by using a sliding window of fixed size k with a hash map to count element frequencies.
Expand the window by adding elements from the right; when window size exceeds k, remove the leftmost element.
When a duplicate is detected, shrink the window from the left until the duplicate is removed.
Maintain a running sum, add the new element on expansion, subtract the removed element on shrink, and update the max sum.
Optimal Approach
Use a sliding window of fixed size k with a hash map tracking element frequencies. As you expand the right pointer, add elements and their counts. When a duplicate is detected (count > 1), shrink from the left until the duplicate is removed. When the window reaches size k, update the maximum sum. This runs in O(n) time with O(k) space.
What Trips People Up in Real Interviews
Clarify whether elements must be strictly distinct or if the subarray itself must contain no duplicates.
Edge case: all elements in the array are the same — the answer is 0 since no subarray of length k has distinct elements.
Edge case: array length equals k — check if all k elements are distinct and return their sum.
Distinguish this from classic maximum sum subarray problems — the distinct constraint changes the approach entirely.
Watch for integer overflow if element values are large; use long for the running sum in production code.
Solution Code
def maximumSubarraySum(nums, k):
from collections import defaultdict
count = defaultdict(int)
curr_sum = 0
max_sum = 0
left = 0
for right in range(len(nums)):
count[nums[right]] += 1
curr_sum += nums[right]
if right - left + 1 > k:
count[nums[left]] -= 1
curr_sum -= nums[left]
if count[nums[left]] == 0:
del count[nums[left]]
left += 1
if right - left + 1 == k and len(count) == k:
max_sum = max(max_sum, curr_sum)
return max_sumFrequently Asked Questions
What is the Maximum Sum of Distinct Subarrays With Length K problem?
Given an integer array nums and an integer k, find the maximum sum of a subarray of length k where all elements are distinct. If no such subarray exists, return 0. A subarray is a contiguous non-empty sequence of elements within an array.
How do you solve Maximum Sum of Distinct Subarrays With Length K?
The optimal approach is described in detail above, including step-by-step walkthroughs, complexity analysis, and solution code in Python. Scroll up to the "Optimal Approach" section.
What companies ask Maximum Sum of Distinct Subarrays With Length K?
Maximum Sum of Distinct Subarrays With Length K is asked at Walmart. It is a medium difficulty problem.
What are common mistakes on Maximum Sum of Distinct Subarrays With Length K?
- Clarify whether elements must be strictly distinct or if the subarray itself must contain no duplicates.
- Edge case: all elements in the array are the same — the answer is 0 since no subarray of length k has distinct elements.
- Edge case: array length equals k — check if all k elements are distinct and return their sum.
- Distinguish this from classic maximum sum subarray problems — the distinct constraint changes the approach entirely.
- Watch for integer overflow if element values are large; use long for the running sum in production code.