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_239.java
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_239.java
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package com.fishercoder.solutions;
import java.util.PriorityQueue;
/**
* 239. Sliding Window Maximum
*
* Given an array nums, there is a sliding window of size k which is moving from the very left of the array to the very right.
* You can only see the k numbers in the window. Each time the sliding window moves right by one position.
For example,
Given nums = [1,3,-1,-3,5,3,6,7], and k = 3.
Window position Max
--------------- -----
[1 3 -1] -3 5 3 6 7 3
1 [3 -1 -3] 5 3 6 7 3
1 3 [-1 -3 5] 3 6 7 5
1 3 -1 [-3 5 3] 6 7 5
1 3 -1 -3 [5 3 6] 7 6
1 3 -1 -3 5 [3 6 7] 7
Therefore, return the max sliding window as [3,3,5,5,6,7].
Note:
You may assume k is always valid, ie: 1 ≤ k ≤ input array's size for non-empty array.
Follow up:
Could you solve it in linear time?
Hint:
How about using a data structure such as deque (double-ended queue)?
The queue size need not be the same as the window’s size.
Remove redundant elements and the queue should store only elements that need to be considered.
*/
public class _239 {
public static class Solution1 {
public int[] maxSlidingWindow(int[] nums, int k) {
if (nums == null || nums.length == 0 || k == 0) {
return new int[0];
}
PriorityQueue<Integer> heap = new PriorityQueue<>((a, b) -> b - a);
int[] res = new int[nums.length - k + 1];
for (int i = 0; i < nums.length; i++) {
if (i < k) {
heap.offer(nums[i]);
if (i == k - 1) {
res[0] = heap.peek();
}
} else {
heap.remove(nums[i - k]);
heap.offer(nums[i]);
res[i - k + 1] = heap.peek();
}
}
return res;
}
}
}