Day 13 | 239. Sliding Window Maximum | 347. Top K Frequent Elements

Day 1 | 704. Binary Search | 27. Remove Element | 35. Search Insert Position | 34. First and Last Position of Element in Sorted Array

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LeetCode 239. Sliding Window Maximum

Question Link

Solution:

class Solution {
    public int[] maxSlidingWindow(int[] nums, int k) {
        if(nums.length==1)
            return nums;
        int len = nums.length - k + 1;
        int[] res = new int[len];
        int idx = 0;
        MyQueue myQueue = new MyQueue();
        // Put the first k elements into the myQueue
        for(int i=0; i<k; i++)
            myQueue.add(nums[i]);
        res[idx++] = myQueue.peek();
        for(int i = k; i < nums.length; i++){
            myQueue.poll(nums[i-k]);        // remove the front element
            myQueue.add(nums[i]);           // add the following element
            res[idx++] = myQueue.peek();    // record the max value
        }
        return res;
    }
}

class MyQueue{
    Deque<Integer> deque = new LinkedList<>();

    // When removing the front element, we must judge whether the element to be removed is equal to the front element of the window.
    void poll(int val){
        if(!deque.isEmpty() && deque.peek() == val)
            deque.poll();
    }

    void add(int val){
        // If the element to add is larger than the entrance element, remove the entrance element.
        while(!deque.isEmpty() && deque.getLast() < val)
            deque.pollLast();
        deque.add(val);
    }

    int peek(){
        return deque.peek();
    }
}

Thoughts:

• When removing the front element, we must judge whether the element to be removed is equal to the front element of the window.
• If the element to add is larger than the entrance element, remove the entrance element.

LeetCode 347. Top K Frequent Elements

Question Link

Solution:

        // 1、Build hash map : character and how often it appears
        Map<Integer, Integer> map = new HashMap<>();
        for(int n : nums)
            map.put(n, map.getOrDefault(n, 0) + 1);
        
        // 2、Order the frequencies, the less frequent element first
        // diy a comparator
        Queue<Integer> heap = new PriorityQueue<>((n1,n2) -> map.get(n1) - map.get(n2));
        for(Integer key : map.keySet()){
            heap.add(key);
            if(heap.size() > k)
                heap.poll();
        }

        // 3. Build an output array, from small to large
        int[] top = new int[k];
        for(int i = k-1; i >= 0 ; i--)
            top[i] = heap.poll();
        return top;

Thought:

• 1、Build hash map : character and how often it appears
• 2、Order the frequencies by min-heap, the less frequent element first
• 3、 Build an output array, from small to large