Problem Description
You are given an integer array nums
and an integer k
. Find the maximum subarray sum of all the subarrays of nums
that meet the following conditions:
- The length of the subarray is
k
, and - All the elements of the subarray are distinct.
Return the maximum subarray sum of all the subarrays that meet the conditions. If no subarray meets the conditions, return 0
.
A subarray is a contiguous non-empty sequence of elements within an array.
Example 1:
Input: nums = [1,5,4,2,9,9,9], k = 3 Output: 15 Explanation: The subarrays of nums with length 3 are: - [1,5,4] which meets the requirements and has a sum of 10. - [5,4,2] which meets the requirements and has a sum of 11. - [4,2,9] which meets the requirements and has a sum of 15. - [2,9,9] which does not meet the requirements because the element 9 is repeated. - [9,9,9] which does not meet the requirements because the element 9 is repeated. We return 15 because it is the maximum subarray sum of all the subarrays that meet the conditions
Example 2:
Input: nums = [4,4,4], k = 3 Output: 0 Explanation: The subarrays of nums with length 3 are: - [4,4,4] which does not meet the requirements because the element 4 is repeated. We return 0 because no subarrays meet the conditions.
Constraints:
1 <= k <= nums.length <= 105
1 <= nums[i] <= 105
Difficulty: Medium
Tags: array, hash table, sliding window
Rating: 98.13%
Solution Complexity
- Time Complexity: O(?)
- Space Complexity: O(?)
Could not extract solution code for analysis.
Solution
Here’s my Python solution to this problem:
class Solution:
def maximumSubarraySum(self, nums: List[int], k: int) -> int:
o = 0
last_i = {}
s = 0
l = 0
for r in range(0, len(nums)):
s += nums[r]
i = last_i.get(nums[r], -1)
last_i[nums[r]] = r
while l <= i or r-l+1 > k:
s -= nums[l]
l += 1
if r - l + 1 == k:
o = max(o, s)
return o