23. Sliding Window Maximum
hardAsked at RedisFind the max of every window of size k as it slides across an array; Redis uses it to probe deque/monotonic intuition that mirrors LPUSH/RPOP patterns on Redis Lists.
By Alex Chen, Founder, InterviewChamp.AI · Last verified
Problem
Given an integer array nums and a window size k, return an array of the maximum value within every contiguous window. Must run in O(n).
Constraints
1 <= k <= nums.length <= 10^5-10^4 <= nums[i] <= 10^4
Examples
Example 1
nums=[1,3,-1,-3,5,3,6,7], k=3[3,3,5,5,6,7]Example 2
nums=[1], k=1[1]Approaches
1. Recompute max per window
Slide the window and call Math.max on each.
- Time
- O(n*k)
- Space
- O(1)
for (let i = 0; i + k <= nums.length; i++)
out.push(Math.max(...nums.slice(i, i + k)));Tradeoff:
2. Monotonic deque
Maintain a deque of indices whose values are strictly decreasing. Pop from the back while the new element is bigger; pop from the front when it falls out of the window. The front is always the window max. This mirrors how Redis Lists drive backpressure via LPUSH + LPOP.
- Time
- O(n)
- Space
- O(k)
function maxSlidingWindow(nums, k) {
const dq = []; // indices
const out = [];
for (let i = 0; i < nums.length; i++) {
while (dq.length && dq[0] <= i - k) dq.shift();
while (dq.length && nums[dq[dq.length - 1]] < nums[i]) dq.pop();
dq.push(i);
if (i >= k - 1) out.push(nums[dq[0]]);
}
return out;
}Tradeoff:
Redis-specific tips
Redis interviewers like the monotonic-deque framing because that's how Redis Streams XREAD windowing throttles back-pressure; cite quicklist's deque-like ends as a side reference.
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