Question

703. Kth Largest Element in a Stream

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Description

Design a class to find the kth largest element in a stream. Note that it is the kth largest element in the sorted order, not the kth distinct element.

Implement KthLargest class:

• KthLargest(int k, int[] nums) Initializes the object with the integer k and the stream of integers nums.
• int add(int val) Appends the integer val to the stream and returns the element representing the kth largest element in the stream.

 

Example 1:

Input
["KthLargest", "add", "add", "add", "add", "add"]
[[3, [4, 5, 8, 2]], [3], [5], [10], [9], [4]]
Output
[null, 4, 5, 5, 8, 8]

Explanation
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

 

Constraints:

• 1 <= k <= 104
• 0 <= nums.length <= 104
• -104 <= nums[i] <= 104
• -104 <= val <= 104
• At most 104 calls will be made to add.
• It is guaranteed that there will be at least k elements in the array when you search for the kth element.

Solutions

Solution 1

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)

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);
 */

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);
 */

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);
 */

/**
 * @param {number} k
 * @param {number[]} nums
 */
var KthLargest = function (k, nums) {
  this.k = k;
  this.heap = new MinHeap();
  for (let num of nums) {
    this.add(num);
  }
};

/**
 * @param {number} val
 * @return {number}
 */
KthLargest.prototype.add = function (val) {
  this.heap.offer(val);
  if (this.heap.size() > this.k) {
    this.heap.poll();
  }
  return this.heap.peek();
};

class MinHeap {
  constructor(data = []) {
    this.data = data;
    this.comparator = (a, b) => a - b;
    this.heapify();
  }

  heapify() {
    if (this.size() < 2) return;
    for (let i = 1; i < this.size(); i++) {
      this.bubbleUp(i);
    }
  }

  peek() {
    if (this.size() === 0) return null;
    return this.data[0];
  }

  offer(value) {
    this.data.push(value);
    this.bubbleUp(this.size() - 1);
  }

  poll() {
    if (this.size() === 0) {
      return null;
    }
    const result = this.data[0];
    const last = this.data.pop();
    if (this.size() !== 0) {
      this.data[0] = last;
      this.bubbleDown(0);
    }
    return result;
  }

  bubbleUp(index) {
    while (index > 0) {
      const parentIndex = (index - 1) >> 1;
      if (this.comparator(this.data[index], this.data[parentIndex]) < 0) {
        this.swap(index, parentIndex);
        index = parentIndex;
      } else {
        break;
      }
    }
  }

  bubbleDown(index) {
    const lastIndex = this.size() - 1;
    while (true) {
      const leftIndex = index * 2 + 1;
      const rightIndex = index * 2 + 2;
      let findIndex = index;
      if (
        leftIndex <= lastIndex &&
        this.comparator(this.data[leftIndex], this.data[findIndex]) < 0
      ) {
        findIndex = leftIndex;
      }
      if (
        rightIndex <= lastIndex &&
        this.comparator(this.data[rightIndex], this.data[findIndex]) < 0
      ) {
        findIndex = rightIndex;
      }
      if (index !== findIndex) {
        this.swap(index, findIndex);
        index = findIndex;
      } else {
        break;
      }
    }
  }

  swap(index1, index2) {
    [this.data[index1], this.data[index2]] = [this.data[index2], this.data[index1]];
  }

  size() {
    return this.data.length;
  }
}

/**
 * Your KthLargest object will be instantiated and called as such:
 * var obj = new KthLargest(k, nums)
 * var param_1 = obj.add(val)
 */