Transform matrix to hash map
Last updated: October 1, 2025
Quick Overview
Given a 2D matrix, transform it into a hash map where the keys represent the unique elements of the matrix and the values are the counts of their occurrences. The output should be a hash map that accurately reflects the frequency of each element in the input matrix. Ensure that the solution efficiently handles large matrices and adheres to optimal time and space complexity.
Oracle
October 1, 20255
9
2,932 solved
Given a 2D matrix, transform it into a hash map where the keys represent the unique elements of the matrix and the values are the counts of their occurrences. The output should be a hash map that accurately reflects the frequency of each element in the input matrix. Ensure that the solution efficiently handles large matrices and adheres to optimal time and space complexity.
Coding interviews at Oracle focus on problem-solving approach as much as the final solution. The interviewer wants to see you break down the problem, consider edge cases, and optimize iteratively. Communication throughout the process is key.
What the Interviewer Expects
- Quickly identify the optimal approach and its theoretical basis
- Handle complex algorithm design with multiple interacting components
- Write concise, elegant code under time pressure
- Prove correctness of your approach and discuss alternative solutions
- Optimize beyond the obvious: discuss constant factor improvements
- Address follow-up variations and explain how the solution generalizes
Key Topics to Cover
How to Approach This
- Clarify input constraints and edge cases before writing code.
- Walk through your approach verbally and confirm with the interviewer before coding.
- Start with a brute force solution, then optimize. Mention time and space complexity.
- Test your solution with examples, including edge cases like empty input or duplicates.
- Consider common patterns: sliding window, two pointers, hash map, BFS/DFS, dynamic programming.
Possible Follow-up Questions
- Can you solve this iteratively instead of recursively (or vice versa)?
- What if the input doesn't fit in memory?
- Can you optimize the space complexity of your solution?
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Problem Analysis
To transform a 2D matrix into a hash map that counts the occurrences of each unique element, we can utilize a hash map (or dictionary in Python) where keys are the unique elements and values are their...
Approach
- Initialize an empty hash map (dictionary) to store the counts of each element.
- Iterate through each row of the matrix.
- For each element in the row, check if it exists in the hash map: ...
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