Sliding Window Maximum
Last updated: March 3, 2025
Quick Overview
Find the maximum element in each sliding window of size k. Tests monotonic deque technique for optimal performance.
ByteDance
March 3, 202512
4
2,081 solved
Find the maximum element in each sliding window of size k. Tests monotonic deque technique for optimal performance.
Monotonic deque problems are medium priority at ByteDance but appear in senior rounds. Tests understanding of advanced data structure techniques.
What the Interviewer Expects
- Implement using a monotonic decreasing deque
- Achieve O(n) time complexity
- Handle window boundary management correctly
- Explain why the deque maintains the decreasing invariant
- Discuss applications in stream processing
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
- How would you handle this for a stream with unknown length?
- What if you need both min and max in each window?
- How would you parallelize this for a distributed stream?
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Practice DSA ProblemsSample Answer
Implementation
```python from collections import deque def max_sliding_window(nums, k): dq = deque() # stores indices, front is always the max result = [] ...
Why It Works
The deque maintains indices in decreasing order of their values. When a new element enters, all smaller elements at the back are removed (they can nev...
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