Description

Our Black Box represents a primitive database. It can save an integer array and has a special i variable. At the initial moment Black Box is empty and i equals 0. This Black Box processes a sequence of commands (transactions). There are two types of transactions:

ADD (x): put element x into Black Box; 
GET: increase i by 1 and give an i-minimum out of all integers containing in the Black Box. Keep in mind that i-minimum is a number located at i-th place after Black Box elements sorting by non- descending.

Let us examine a possible sequence of 11 transactions:

Example 1

N Transaction i Black Box contents after transaction Answer

(elements are arranged by non-descending)

1 ADD(3) 0 3

2 GET 1 3 3

3 ADD(1) 1 1, 3

4 GET 2 1, 3 3

5 ADD(-4) 2 -4, 1, 3

6 ADD(2) 2 -4, 1, 2, 3

7 ADD(8) 2 -4, 1, 2, 3, 8

8 ADD(-1000) 2 -1000, -4, 1, 2, 3, 8

9 GET 3 -1000, -4, 1, 2, 3, 8 1

10 GET 4 -1000, -4, 1, 2, 3, 8 2

11 ADD(2) 4 -1000, -4, 1, 2, 2, 3, 8

It is required to work out an efficient algorithm which treats a given sequence of transactions. The maximum number of ADD and GET transactions: 30000 of each type.

Let us describe the sequence of transactions by two integer arrays:

1. A(1), A(2), ..., A(M): a sequence of elements which are being included into Black Box. A values are integers not exceeding 2 000 000 000 by their absolute value, M <= 30000. For the Example we have A=(3, 1, -4, 2, 8, -1000, 2).

2. u(1), u(2), ..., u(N): a sequence setting a number of elements which are being included into Black Box at the moment of first, second, ... and N-transaction GET. For the Example we have u=(1, 2, 6, 6).

The Black Box algorithm supposes that natural number sequence u(1), u(2), ..., u(N) is sorted in non-descending order, N <= M and for each p (1 <= p <= N) an inequality p <= u(p) <= M is valid. It follows from the fact that for the p-element of our u sequence we perform a GET transaction giving p-minimum number from our A(1), A(2), ..., A(u(p)) sequence.

Input

Input contains (in given order): M, N, A(1), A(2), ..., A(M), u(1), u(2), ..., u(N). All numbers are divided by spaces and (or) carriage return characters.

Output

Write to the output Black Box answers sequence for a given sequence of transactions, one number each line.

Sample Input

7 4
3 1 -4 2 8 -1000 2
1 2 6 6

Sample Output

3
3
1
2

Source

题意:

给一系列数字,给出前k个数字中第i大的数字,i从1->m;

题解:

维护一个从大到小的优先队列和一个从小到大的,大顶堆中存放的是前i-1个数字的最小值,但是会时时更新,小顶堆中存放的是当前的最小值

此处记录一下改变优先队列的大小顺序的方法,

1,首先优先队列默认从大到小,大的在顶

2,从小到大。

priority_queue<int,vector<int>,greater<int> >//这样便是从小到大
priority_queue< int,vector<int>,less<int> > //大->小

3,如果是结构体

struct number1
{
int x;
bool operator < (const number1 &a) const//只有 < 这个符号
{
return x>a.x;//小值优先 //反之大值优先
}
};

  

  

//#include <bits/stdc++.h>
#include <cstdio>
#include <queue>
using namespace std;
const int MAXN=30010;
priority_queue<int>big;
priority_queue<int,vector<int>,greater<int> >mi; int a[MAXN],b[MAXN];
int main()
{
int n,m;
scanf("%d%d",&n,&m);
for (int i = 0; i <n ; ++i) {
scanf("%d",&a[i]);
}
int op;
int k=0;
for (int i = 0; i <m ; ++i) {
scanf("%d",&op);
while(k<op)
{
mi.push(a[k]);
if(!big.empty()&&mi.top()<big.top())//大顶堆维护前k-1的最小值,小顶堆维护当前除了前k-1个最小值的最小值。
{
int t;
t=big.top();
big.pop();
big.push(mi.top());
mi.pop();
mi.push(t);
}
k++;
}
printf("%d\n",mi.top());//需要把当前的最小值发放入到大顶堆中
big.push(mi.top());
mi.pop();
} return 0;
}

  

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