给定一个初始数组A []和一个最终数组B []，它们的大小均为N，其中包含范围为[1，N]的整数，其中A []表示元素插入的顺序，而B []表示元素的插入顺序。将其删除后，任务是查找位于比其在A []中的相应位置早的索引处的B []中的元素数。
例子：
Input: A[ ] = {1, 2, 4, 3}, B[ ] = {2, 3, 4, 1}
Output: 3
Explanation:
The element 2 was inserted after 1, but removed before 1.
The element 3 was inserted after 4, but removed before 4.
The element 4 was inserted after 1, but removed before 1.
Hence, total 3 elements have moved ahead.
Input: A[ ] = {1, 2, 3, 4} B[ ] = {1, 2, 4, 3}
Output: 1
Explanation:
The element 4 was inserted after 3, but removed before 3.
Hence, only 1 element has moved ahead.
天真的方法：解决此问题的最简单方法是将B []中每个元素的位置与A []中其他每个元素的位置进行比较，并检查是否将其插入到A []中的元素之后，然后将其删除。 B [] 。如果是，则增加计数。最后，打印总数。
时间复杂度： O(N 2 )
辅助空间： O(1)
高效方法：解决此问题的更好方法是维护一个队列并将B []的元素插入此队列，并将所有元素插入无序集合。无序集合用于有效检查特定元素是否已处理。从队列中遍历A []和pop元素，直到当前元素A [i]出现在队列的顶部，还不断增加计数并标记出现在队列顶部的元素为已处理。最后，总数将给出B []中已向前移动的元素数。
请按照以下步骤解决问题：
- 维护一个Queue和无序集，并在两者中存储数组B []的值。
- 现在，遍历数组A [] 。
- 如果当前元素不存在于无序集中，则意味着它已被删除。
- 初始化变量计数。如果在队列中未找到第i个元素，请从队列中删除A [i]之前队列中存在的所有元素，并且无序集合将继续增加count 。
- 从队列和无序集中删除A [i] 。
- 最后，打印总数。
下面是上述方法的实现：
C++
// C++ Program to implement
// the above appraoch
#include
using namespace std;
// Function returns maximum number
// of required elements
int maximumCount(int A[], int B[], int n)
{
queue q;
unordered_set s;
// Insert the elements of array B
// in the queue and set
for (int i = 0; i < n; i++) {
s.insert(B[i]);
q.push(B[i]);
}
// Stores the answer
int count = 0;
for (int i = 0; i < n; i++) {
// If A[i] is already processed
if (s.find(A[i]) == s.end())
continue;
// Until we find A[i] in the queue
while (!q.empty() && q.front() != A[i]) {
// Remove elements from the queue
s.erase(q.front());
q.pop();
// Increment the count
count++;
}
// Remove the current element A[i]
// from the queue and set.
if (A[i] == q.front()) {
q.pop();
s.erase(A[i]);
}
if (q.empty())
break;
}
// Return total count
cout << count << endl;
}
// Driver Code
int main()
{
int N = 4;
int A[] = { 1, 2, 3, 4 };
int B[] = { 1, 2, 4, 3 };
maximumCount(A, B, N);
return 0;
} Java
// Java program to implement
// the above appraoch
import java.util.*;
class GFG{
// Function returns maximum number
// of required elements
static void maximumCount(int A[], int B[], int n)
{
Queue q = new LinkedList<>();
HashSet s = new HashSet<>();
// Insert the elements of array B
// in the queue and set
for(int i = 0; i < n; i++)
{
s.add(B[i]);
q.add(B[i]);
}
// Stores the answer
int count = 0;
for(int i = 0; i < n; i++)
{
// If A[i] is already processed
if (!s.contains(A[i]))
continue;
// Until we find A[i] in the queue
while (!q.isEmpty() && q.peek() != A[i])
{
// Remove elements from the queue
s.remove(q.peek());
q.remove();
// Increment the count
count++;
}
// Remove the current element A[i]
// from the queue and set.
if (A[i] == q.peek())
{
q.remove();
s.remove(A[i]);
}
if (q.isEmpty())
break;
}
// Return total count
System.out.print(count + "\n");
}
// Driver Code
public static void main(String[] args)
{
int N = 4;
int A[] = { 1, 2, 3, 4 };
int B[] = { 1, 2, 4, 3 };
maximumCount(A, B, N);
}
}
// This code is contributed by princi singh Python3
# Python3 Program to implement
# the above appraoch
import queue
# Function returns maximum number
# of required elements
def maximumCount(A, B, n):
q = queue.Queue()
s = set()
# Insert the elements of
# array B in the queue
# and set
for i in range(n):
s.add(B[i])
q.put(B[i])
# Stores the answer
count = 0
for i in range(n):
# If A[i] is already
# processed
if (A[i] not in s):
continue
# Until we find A[i]
# in the queue
while (q.qsize() > 0 and
q.queue[0] != A[i]):
# Remove elements from
# the queue
s.remove(q.queue[0]);
q.get()
# Increment the count
count += 1
# Remove the current element A[i]
# from the queue and set.
if (A[i] == q.queue[0]):
q.get()
s.remove(A[i])
if (q.qsize() == 0):
break
# Return total count
print(count)
# Driver code
N = 4
A = [1, 2, 3, 4]
B = [1, 2, 4, 3]
maximumCount(A, B, N)
# This code is contributed by divyeshrabadiya07C#
// C# program to implement
// the above appraoch
using System;
using System.Collections.Generic;
class GFG{
// Function returns maximum number
// of required elements
static void maximumCount(int []A, int []B, int n)
{
Queue q = new Queue();
HashSet s = new HashSet();
// Insert the elements of array B
// in the queue and set
for(int i = 0; i < n; i++)
{
s.Add(B[i]);
q.Enqueue(B[i]);
}
// Stores the answer
int count = 0;
for(int i = 0; i < n; i++)
{
// If A[i] is already processed
if (!s.Contains(A[i]))
continue;
// Until we find A[i] in the queue
while (q.Count != 0 && q.Peek() != A[i])
{
// Remove elements from the queue
s.Remove(q.Peek());
q.Dequeue();
// Increment the count
count++;
}
// Remove the current element A[i]
// from the queue and set.
if (A[i] == q.Peek())
{
q.Dequeue();
s.Remove(A[i]);
}
if (q.Count == 0)
break;
}
// Return total count
Console.Write(count + "\n");
}
// Driver Code
public static void Main(String[] args)
{
int N = 4;
int []A = { 1, 2, 3, 4 };
int []B = { 1, 2, 4, 3 };
maximumCount(A, B, N);
}
}
// This code is contributed by princi singh 输出：
1
时间复杂度： O(N)
辅助空间： O(N)