How do you solve Merge Similar Items on LeetCode?

Merge Similar Items (LeetCode #2363) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n) time complexity and O(n) space complexity. Key insight: Using a hash map allows for efficient aggregation of weights.

What is the brute force solution for Merge Similar Items?

The brute force approach for Merge Similar Items is Brute Force, with O(n²) time complexity and O(1) space complexity. In the brute force approach, we will iterate through both arrays and for each item in the first array, we will check if it exists in the second array. If it does, we will sum their weights. This method is straightforward but inefficient. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve Merge Similar Items?

Merge Similar Items uses the following concepts: Array, Hash Table, Sorting, Ordered Set. The recommended patterns to study are: Hash Map, Array.

What are the interview tips for Merge Similar Items?

Always consider the data structures that can optimize your solution. Explain your thought process clearly during the interview. Practice similar problems to get familiar with patterns.

What are common mistakes when solving Merge Similar Items?

Not using a hash map for aggregation, leading to inefficient solutions. Forgetting to sort the final output.

#2363

Merge Similar Items

Easy

ArrayHash TableSortingOrdered SetHash MapArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n)
Space	O(1)	O(n)

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Intuition

Time O(n)Space O(n)

Using a hash map allows us to efficiently aggregate weights by value from both arrays in a single pass. This reduces the time complexity significantly compared to the brute force method.

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Algorithm

5 steps

1Step 1: Initialize a hash map to store the weights.
2Step 2: Iterate through items1 and add weights to the map using values as keys.
3Step 3: Repeat for items2, updating the weights in the map.
4Step 4: Convert the map to a list and sort it by value.
5Step 5: Return the sorted list.

solution.py10 lines

1def mergeSimilarItems(items1, items2):
2    from collections import defaultdict
3    weights = defaultdict(int)
4    for value, weight in items1:
5        weights[value] += weight
6    for value, weight in items2:
7        weights[value] += weight
8    return sorted(weights.items())
9
10print(mergeSimilarItems([[1,1],[4,5],[3,8]], [[3,1],[1,5]]))

ℹ

Complexity note: The time complexity is O(n) because we make a single pass through both arrays to populate the hash map. The space complexity is O(n) due to the storage of weights in the hash map.

1Using a hash map allows for efficient aggregation of weights.
2Sorting the final result ensures the output is in the correct order.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.