2204. Find Subsequence Of Length K With The Largest Sum¶

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2204. Find Subsequence of Length K With the Largest Sum

Easy

You are given an integer array nums and an integer k. You want to find a subsequence of nums of length k that has the largest sum.

Return any such subsequence as an integer array of length k.

A subsequence is an array that can be derived from another array by deleting some or no elements without changing the order of the remaining elements.

Example 1:

Input: nums = [2,1,3,3], k = 2
Output: [3,3]
Explanation:
The subsequence has the largest sum of 3 + 3 = 6.

Example 2:

Input: nums = [-1,-2,3,4], k = 3
Output: [-1,3,4]
Explanation: 
The subsequence has the largest sum of -1 + 3 + 4 = 6.

Example 3:

Input: nums = [3,4,3,3], k = 2
Output: [3,4]
Explanation:
The subsequence has the largest sum of 3 + 4 = 7. 
Another possible subsequence is [4, 3].

Constraints:

• 1 <= nums.length <= 1000
• -105 <= nums[i] <= 105
• 1 <= k <= nums.length

Solution¶

class Solution {
    static class custom_sort implements Comparator<Integer> {
        @Override
        public int compare(Integer first, Integer second) {
            return Integer.compare(second, first);
        }
    }
    public int[] maxSubsequence(int[] nums, int k) {
        int n = nums.length;
        PriorityQueue<Integer> pq = new PriorityQueue<>(new custom_sort());
        for(int i = 0; i < n; i++) 
            pq.offer(nums[i]);
        int res[] = new int[k];
        int p = 0;
        HashMap<Integer, Integer> map = new HashMap<>();
        while(k > 0) {
            int ele = pq.poll();
            map.put(ele, map.getOrDefault(ele, 0) + 1);
            k--;
        }
        for(int i = 0; i < n; i++) {
            if(map.containsKey(nums[i])) {
                res[p++] = nums[i];
                map.put(nums[i] , map.getOrDefault(nums[i] , 0) - 1);
                if(map.get(nums[i]) == 0) 
                    map.remove(nums[i]);
            }
        }
        return res;
    }
}

Complexity Analysis¶

• Time Complexity: O(?)
• Space Complexity: O(?)

Approach¶

Detailed explanation of the approach will be added here