703. Kth Largest Element in a Stream #

Problem #

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) 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.

Problem Summary #

Design a class to find the kth largest element in a data stream. Note that it is the kth largest element after sorting, not the kth distinct element. Implement the KthLargest class:

KthLargest(int k, int[] nums) Initializes the object with the integer k and the integer stream nums.
int add(int val) Inserts val into the data stream nums, then returns the current kth largest element in the data stream.

Solution Approach #

After reading the problem, it is clear that this problem tests a min-heap. Build a min-heap of length K, and each time pop the heap top (the smallest element in the heap), maintaining the heap top as the Kth largest element.
Here is a concise way to write it. Normally, to build a pq priority queue, you need to create a new type yourself and then implement the five methods Len(), Less(), Swap(), Push(), and Pop(). The sort package has a ready-made min-heap, sort.IntSlice. You can reuse it and then implement Push() and Pop() yourself to use the min-heap, saving some code.

Code #

package leetcode

import (
	"container/heap"
	"sort"
)

type KthLargest struct {
	sort.IntSlice
	k int
}

func Constructor(k int, nums []int) KthLargest {
	kl := KthLargest{k: k}
	for _, val := range nums {
		kl.Add(val)
	}
	return kl
}

func (kl *KthLargest) Push(v interface{}) {
	kl.IntSlice = append(kl.IntSlice, v.(int))
}

func (kl *KthLargest) Pop() interface{} {
	a := kl.IntSlice
	v := a[len(a)-1]
	kl.IntSlice = a[:len(a)-1]
	return v
}

func (kl *KthLargest) Add(val int) int {
	heap.Push(kl, val)
	if kl.Len() > kl.k {
		heap.Pop(kl)
	}
	return kl.IntSlice[0]
}