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剑指 Offer II 059. 数据流的第 K 大数值

题目描述

设计一个找到数据流中第 k 大元素的类(class)。注意是排序后的第 k 大元素,不是第 k 个不同的元素。

请实现 KthLargest 类:

  • KthLargest(int k, int[] nums) 使用整数 k 和整数流 nums 初始化对象。
  • int add(int val)val 插入数据流 nums 后,返回当前数据流中第 k 大的元素。

 

示例:

输入:
["KthLargest", "add", "add", "add", "add", "add"]
[[3, [4, 5, 8, 2]], [3], [5], [10], [9], [4]]
输出:
[null, 4, 5, 5, 8, 8]

解释:
KthLargest kthLargest = new KthLargest(3, [4, 5, 8, 2]);
kthLargest.add(3);   // return 4
kthLargest.add(5);   // return 5
kthLargest.add(10);  // return 5
kthLargest.add(9);   // return 8
kthLargest.add(4);   // return 8

 

提示:

  • 1 <= k <= 104
  • 0 <= nums.length <= 104
  • -104 <= nums[i] <= 104
  • -104 <= val <= 104
  • 最多调用 add 方法 104
  • 题目数据保证,在查找第 k 大元素时,数组中至少有 k 个元素

 

注意:本题与主站 703 题相同: https://leetcode.cn/problems/kth-largest-element-in-a-stream/

解法

方法一

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class KthLargest:
    def __init__(self, k: int, nums: List[int]):
        self.q = []
        self.size = k
        for num in nums:
            self.add(num)

    def add(self, val: int) -> int:
        heappush(self.q, val)
        if len(self.q) > self.size:
            heappop(self.q)
        return self.q[0]


# Your KthLargest object will be instantiated and called as such:
# obj = KthLargest(k, nums)
# param_1 = obj.add(val)
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class KthLargest {
    private PriorityQueue<Integer> q;
    private int size;

    public KthLargest(int k, int[] nums) {
        q = new PriorityQueue<>(k);
        size = k;
        for (int num : nums) {
            add(num);
        }
    }

    public int add(int val) {
        q.offer(val);
        if (q.size() > size) {
            q.poll();
        }
        return q.peek();
    }
}

/**
 * Your KthLargest object will be instantiated and called as such:
 * KthLargest obj = new KthLargest(k, nums);
 * int param_1 = obj.add(val);
 */
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class KthLargest {
public:
    priority_queue<int, vector<int>, greater<int>> q;
    int size;

    KthLargest(int k, vector<int>& nums) {
        size = k;
        for (int num : nums) add(num);
    }

    int add(int val) {
        q.push(val);
        if (q.size() > size) q.pop();
        return q.top();
    }
};

/**
 * Your KthLargest object will be instantiated and called as such:
 * KthLargest* obj = new KthLargest(k, nums);
 * int param_1 = obj->add(val);
 */
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type KthLargest struct {
    h *IntHeap
    k int
}

func Constructor(k int, nums []int) KthLargest {
    h := &IntHeap{}
    heap.Init(h)
    for _, v := range nums {
        heap.Push(h, v)
    }

    for h.Len() > k {
        heap.Pop(h)
    }

    return KthLargest{
        h: h,
        k: k,
    }
}

func (this *KthLargest) Add(val int) int {
    heap.Push(this.h, val)
    for this.h.Len() > this.k {
        heap.Pop(this.h)
    }

    return this.h.Top()
}

func connectSticks(sticks []int) int {
    h := IntHeap(sticks)
    heap.Init(&h)
    res := 0
    for h.Len() > 1 {
        val := heap.Pop(&h).(int)
        val += heap.Pop(&h).(int)
        res += val
        heap.Push(&h, val)
    }
    return res
}

type IntHeap []int

func (h IntHeap) Len() int           { return len(h) }
func (h IntHeap) Less(i, j int) bool { return h[i] < h[j] }
func (h IntHeap) Swap(i, j int)      { h[i], h[j] = h[j], h[i] }
func (h *IntHeap) Push(x any) {
    *h = append(*h, x.(int))
}
func (h *IntHeap) Pop() any {
    old := *h
    n := len(old)
    x := old[n-1]
    *h = old[0 : n-1]
    return x
}

func (h *IntHeap) Top() int {
    if (*h).Len() == 0 {
        return 0
    }

    return (*h)[0]
}

/**
 * Your KthLargest object will be instantiated and called as such:
 * obj := Constructor(k, nums);
 * param_1 := obj.Add(val);
 */

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