Leetcode #2789: Largest Element in an Array after Merge Operations
In this guide, we solve Leetcode #2789 Largest Element in an Array after Merge Operations in Python and focus on the core idea that makes the solution efficient.
You will see the intuition, the step-by-step method, and a clean Python implementation you can use in interviews.
Problem Statement
You are given a 0-indexed array nums consisting of positive integers. You can do the following operation on the array any number of times: Choose an index i such that 0 <= i < nums.length - 1 and nums[i] <= nums[i + 1].
Quick Facts
- Difficulty: Medium
- Premium: No
- Tags: Greedy, Array
Intuition
A locally optimal choice leads to a globally optimal result for this structure.
That means we can commit to decisions as we scan without backtracking.
Approach
Sort or preprocess if needed, then repeatedly take the best available local choice.
Maintain the minimal state necessary to validate the greedy decision.
Steps:
- Sort or preprocess as needed.
- Iterate and pick the best local option.
- Track the current solution.
Example
Input: nums = [2,3,7,9,3]
Output: 21
Explanation: We can apply the following operations on the array:
- Choose i = 0. The resulting array will be nums = [5,7,9,3].
- Choose i = 1. The resulting array will be nums = [5,16,3].
- Choose i = 0. The resulting array will be nums = [21,3].
The largest element in the final array is 21. It can be shown that we cannot obtain a larger element.
Python Solution
class Solution:
def maxArrayValue(self, nums: List[int]) -> int:
for i in range(len(nums) - 2, -1, -1):
if nums[i] <= nums[i + 1]:
nums[i] += nums[i + 1]
return max(nums)
Complexity
The time complexity is , where is the length of the array. The space complexity is .
Edge Cases and Pitfalls
Watch for boundary values, empty inputs, and duplicate values where applicable. If the problem involves ordering or constraints, confirm the invariant is preserved at every step.
Summary
This Python solution focuses on the essential structure of the problem and keeps the implementation interview-friendly while meeting the constraints.