亚洲在线久爱草,狠狠天天香蕉网,天天搞日日干久草,伊人亚洲日本欧美

為了賬號安全,請及時綁定郵箱和手機立即綁定

【LEETCODE】模擬面試-215. Kth Largest Element in an Array

图:新生大学

https://leetcode.com/problems/kth-largest-element-in-an-array/

Find the kth largest element in an unsorted array.
Note that it is the kth largest element in the sorted order, not the kth distinct element.
For example,Given [3,2,1,5,6,4]
and k = 2, return 5.
**Note: **You may assume k is always valid, 1 ≤ k ≤ array's length.

**input: **an unsorted array, an integer k
output: return an integer, which is the kth largest in the given array, including duplicates
corner: when the array is null, or its length is less than k, there is no such element

The primitive idea is to sort the array, and count the kth element, if we use merge sort, it will take O(n logn), plus O(k) to count.

Or we can optimize that we just sort the largest k elements, ignoring the remain n-k elements. It will raise the Heap structure, since it's fast to find the largest element.

So, we scan from left to right in the array, first put k elements into a heap to heapify. Time is O(k)
This heap is a minHeap where its top is the smallest.
Every time we scan an element in the array, we compare it with the top of the heap.
If it's smaller than or equal to top, we keep moving on.
If it's larger than top, we pop the top, and put it in the top, and main the heap to be a minHeap. Time is O(logk)
After we scanned all the elements in the array, we just need to pop the top, which is the right largest one. Need to compare n - k times.

Finally, time complexity is O((n - k)logk + k)
space is O(k)

public class Solution {    public int findKthLargest(int[] nums, int k){    if ( nums == null || nums.length < k ){        return Integer.MIN_VALUE;
    }    
    //method: maintain a min heap with size k
    PriorityQueue<Integer> minHeap = new PriorityQueue<Integer>(k, new MyComparator());    
    //1.add first k elements
    for ( int i = 0; i < k; i++ ){
        minHeap.offer(nums[i]);
    }    
    //2.compare remain elements, add
    for ( int i = k; i < nums.length; i++ ){        if ( nums[i] > minHeap.peek() ){
            minHeap.poll();
            minHeap.offer(nums[i]);
        }
    }    
    return minHeap.poll();
    
}class MyComparator implements Comparator<Integer>{    @Override
    public int compare(Integer o1, Integer o2){        if ( o1.equals(o2) ){            return 0;
        }else{            //from small to large, minHeap
            return o1 - o2;
        }
    }
}


點擊查看更多內容
TA 點贊

若覺得本文不錯,就分享一下吧!

評論

作者其他優質文章

正在加載中
  • 推薦
  • 評論
  • 收藏
  • 共同學習,寫下你的評論
感謝您的支持,我會繼續努力的~
掃碼打賞,你說多少就多少
贊賞金額會直接到老師賬戶
支付方式
打開微信掃一掃,即可進行掃碼打賞哦
今天注冊有機會得

100積分直接送

付費專欄免費學

大額優惠券免費領

立即參與 放棄機會
微信客服

購課補貼
聯系客服咨詢優惠詳情

幫助反饋 APP下載

慕課網APP
您的移動學習伙伴

公眾號

掃描二維碼
關注慕課網微信公眾號

舉報

0/150
提交
取消