Sliding Window Median
<p>The <strong>median</strong> is the middle value in an ordered integer list. If the size of the list is even, there is no middle value. So the median is the mean of the two middle values.</p>

<ul>
	<li>For examples, if <code>arr = [2,<u>3</u>,4]</code>, the median is <code>3</code>.</li>
	<li>For examples, if <code>arr = [1,<u>2,3</u>,4]</code>, the median is <code>(2 + 3) / 2 = 2.5</code>.</li>
</ul>

<p>You are given an integer array <code>nums</code> and an integer <code>k</code>. There is a sliding window of size <code>k</code> which is moving from the very left of the array to the very right. You can only see the <code>k</code> numbers in the window. Each time the sliding window moves right by one position.</p>

<p>Return <em>the median array for each window in the original array</em>. Answers within <code>10<sup>-5</sup></code> of the actual value will be accepted.</p>

<p>&nbsp;</p>
<p><strong class="example">Example 1:</strong></p>

<pre>
<strong>Input:</strong> nums = [1,3,-1,-3,5,3,6,7], k = 3
<strong>Output:</strong> [1.00000,-1.00000,-1.00000,3.00000,5.00000,6.00000]
<strong>Explanation:</strong> 
Window position                Median
---------------                -----
[<strong>1  3  -1</strong>] -3  5  3  6  7        1
 1 [<strong>3  -1  -3</strong>] 5  3  6  7       -1
 1  3 [<strong>-1  -3  5</strong>] 3  6  7       -1
 1  3  -1 [<strong>-3  5  3</strong>] 6  7        3
 1  3  -1  -3 [<strong>5  3  6</strong>] 7        5
 1  3  -1  -3  5 [<strong>3  6  7</strong>]       6
</pre>

<p><strong class="example">Example 2:</strong></p>

<pre>
<strong>Input:</strong> nums = [1,2,3,4,2,3,1,4,2], k = 3
<strong>Output:</strong> [2.00000,3.00000,3.00000,3.00000,2.00000,3.00000,2.00000]
</pre>

<p>&nbsp;</p>
<p><strong>Constraints:</strong></p>

<ul>
	<li><code>1 &lt;= k &lt;= nums.length &lt;= 10<sup>5</sup></code></li>
	<li><code>-2<sup>31</sup> &lt;= nums[i] &lt;= 2<sup>31</sup> - 1</code></li>
</ul>
Array; Hash Table; Sliding Window; Heap (Priority Queue)
class MedianFinder {
    private PriorityQueue<Integer> small = new PriorityQueue<>(Comparator.reverseOrder());
    private PriorityQueue<Integer> large = new PriorityQueue<>();
    private Map<Integer, Integer> delayed = new HashMap<>();
    private int smallSize;
    private int largeSize;
    private int k;

    public MedianFinder(int k) {
        this.k = k;
    }

    public void addNum(int num) {
        if (small.isEmpty() || num <= small.peek()) {
            small.offer(num);
            ++smallSize;
        } else {
            large.offer(num);
            ++largeSize;
        }
        rebalance();
    }

    public double findMedian() {
        return (k & 1) == 1 ? small.peek() : ((double) small.peek() + large.peek()) / 2;
    }

    public void removeNum(int num) {
        delayed.merge(num, 1, Integer::sum);
        if (num <= small.peek()) {
            --smallSize;
            if (num == small.peek()) {
                prune(small);
            }
        } else {
            --largeSize;
            if (num == large.peek()) {
                prune(large);
            }
        }
        rebalance();
    }

    private void prune(PriorityQueue<Integer> pq) {
        while (!pq.isEmpty() && delayed.containsKey(pq.peek())) {
            if (delayed.merge(pq.peek(), -1, Integer::sum) == 0) {
                delayed.remove(pq.peek());
            }
            pq.poll();
        }
    }

    private void rebalance() {
        if (smallSize > largeSize + 1) {
            large.offer(small.poll());
            --smallSize;
            ++largeSize;
            prune(small);
        } else if (smallSize < largeSize) {
            small.offer(large.poll());
            --largeSize;
            ++smallSize;
            prune(large);
        }
    }
}

class Solution {
    public double[] medianSlidingWindow(int[] nums, int k) {
        MedianFinder finder = new MedianFinder(k);
        for (int i = 0; i < k; ++i) {
            finder.addNum(nums[i]);
        }
        int n = nums.length;
        double[] ans = new double[n - k + 1];
        ans[0] = finder.findMedian();
        for (int i = k; i < n; ++i) {
            finder.addNum(nums[i]);
            finder.removeNum(nums[i - k]);
            ans[i - k + 1] = finder.findMedian();
        }
        return ans;
    }
}