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)
将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
次 - 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
//leetcode submit region begin(Prohibit modification and deletion)
class KthLargest {
private PriorityQueue<Integer> pq;
private int k;
public KthLargest(int k, int[] nums) {
pq = new PriorityQueue<>(new Comparator<Integer>(){
@Override
public int compare(Integer o1, Integer o2) {
return o1.compareTo(o2);
}
});
this.k = k;
for (int num : nums) {
add(num);
}
}
public int add(int val) {
pq.add(val);
if (pq.size() > this.k) {
pq.poll();
}
return pq.peek();
}
}
/**
* Your KthLargest object will be instantiated and called as such:
* KthLargest obj = new KthLargest(k, nums);
* int param_1 = obj.add(val);
*/
//leetcode submit region end(Prohibit modification and deletion)