Maximum Sum of Distinct Subarrays With Length K | Khandani Template |Leetcode 2461 |codestorywithMIK
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This is the 31st Video of our Playlist "Sliding Window : Popular Interview Problems" by codestorywithMIK
In this video we will try to solve a classic Sliding Window Problem : Maximum Sum of Distinct Subarrays With Length K | Khandani Template | Leetcode 2461 | codestorywithMIK
I will explain the intuition so easily that you will never forget and start seeing this as cakewalk EASYYY.
We will do live coding after explanation and see if we are able to pass all the test cases.
Also, please note that my Github solution link below contains both C++ as well as JAVA code.
Problem Name : Maximum Sum of Distinct Subarrays With Length K | Khandani Template | Leetcode 2461 | codestorywithMIK
Company Tags : Capgemini
My solutions on Github(C++ & JAVA) - https://github.com/MAZHARMIK/Interview_DS_Algo/blob/master/Sliding Window/Maximum Sum of Distinct Subarrays With Length K.cpp
Leetcode Link : https://leetcode.com/problems/maximum-sum-of-distinct-subarrays-with-length-k
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Summary :
The solution uses the sliding window technique combined with a HashSet to find the maximum sum of a subarray of size k while ensuring that all elements in the subarray are unique.
Two Pointers:
Use two pointers i (start) and j (end) to define the current window.
HashSet for Uniqueness:
Maintain a HashSet to track unique elements in the current window.
Window Expansion:
Incrementally add nums[j] to the current window.
If nums[j] already exists in the HashSet, shrink the window from the left (i++) until the duplicate is removed.
Window Size Check:
When the window size equals k, calculate the sum and update the maximum result.
Then shrink the window from the left to explore other possibilities.
Sliding Mechanism:
Keep sliding the window until j traverses the entire array.
This approach ensures an O(n) time complexity due to the efficient sliding of the window and HashSet operations.
✨ Timelines✨
00:00 - Introduction
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