LeetCode 325: Maximum Size Subarray Sum Equals k
LeetCode 325 Solution Explanation
Explanation:
To solve this problem, we can use a hashmap to store the cumulative sum up to each index. We iterate through the array keeping track of the cumulative sum and store it in the hashmap along with its index. At each index, we check if the current sum minus the target k exists in the hashmap. If it does, we update the maximum length of the subarray. We return the maximum length of the subarray that sums to k.
Algorithm:
- Initialize a hashmap to store cumulative sums and their corresponding indices.
- Initialize variables
maxLento store the maximum length of the subarray andsumto store the cumulative sum. - Iterate through the array:
- Update
sumwith the current element. - If
sum - kis present in the hashmap, updatemaxLenif necessary. - If
sumis not present in the hashmap, store it with its index.
- Update
- Return
maxLen.
Time Complexity: O(n) - We iterate through the array once. Space Complexity: O(n) - We use a hashmap to store cumulative sums.
:
LeetCode 325 Solutions in Java, C++, Python
class Solution {
public int maxSubArrayLen(int[] nums, int k) {
Map<Integer, Integer> map = new HashMap<>();
int maxLen = 0;
int sum = 0;
for (int i = 0; i < nums.length; i++) {
sum += nums[i];
if (sum == k) {
maxLen = i + 1;
} else if (map.containsKey(sum - k)) {
maxLen = Math.max(maxLen, i - map.get(sum - k));
}
if (!map.containsKey(sum)) {
map.put(sum, i);
}
}
return maxLen;
}
}Interactive Code Editor for LeetCode 325
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