我正在使用下面剪切文件中的样本数据评估频率。
我注意到，对于无序列表，求值只需要不到一秒钟的时间就可以返回结果。然而，对于向量，求值几乎需要整整一分钟！
我考虑了几个因素：

• 数据大小
• 数据本身

经过几次实验，我发现如果我取出倒数第二个数据（-6），性能几乎相同，两个数据的结果都在不到一秒的时间内返回！

但是，如果包含-6，则向量求值花费的时间太长！

我试着改变数字，如-5、-4等，实际上性能相当不错！

出于某种原因，文件中最后一个数据/数字（+125503）之前只有-6似乎影响了矢量性能......这是怎么回事？

**注意：**当然，我也尝试过分别运行它们，方法是注解掉无序列表逻辑，然后注解掉向量逻辑，行为相同
代码：

#include <algorithm>
#include <unordered_set>
#include <fstream>
#include <iostream>
#include <vector>

using namespace std;

vector<int> scanFile(ifstream &file) {
    vector<int> scannedFile;
    string str;
    
    while (getline(file, str)) {
        scannedFile.push_back(stoi(str));
    }
    
    return scannedFile;
}

int main() {
    ifstream inputFile;
    vector<int> fileInfo;
    string str = "";
    
    inputFile.open("file.txt");
    
    fileInfo = scanFile(inputFile);
    inputFile.close();
  
    int Occurrences = 0;
    unordered_set<int> unordrdList; //results are immediate, even with -6!
    bool found = false;
    
    unordrdList.insert(Occurrences);
    
    while (!found) {
        for (int n : fileInfo) {
          Occurrences += n;
          found = unordrdList.find(Occurrences) != unordrdList.end();
          
          unordrdList.insert(Occurrences);
          
          if (found) {
            cout << "Using Unordered_Set: The 2nd showing #: " << to_string(Occurrences) << endl;
            break;
          }
        }
    }
    
    int Occurrnce = 0;
    vector<int> vectr; //result takes too long with -6 present in the file before 2nd to last line!
    bool found2 = false;
    
    vectr.push_back(Occurrnce);
    
    while (!found2) {
        for (int n : fileInfo) {
          Occurrnce += n;
          found2 = find(vectr.begin(), vectr.end(), Occurrnce) != vectr.end();
          
          vectr.push_back(Occurrnce);
          
          if (found2) {
            cout << "Using Vector: The 2nd showing #: " << to_string(Occurrnce) << endl;
            break;
          }
        }
    }
}

文本文件：

-5
-2
+1
+14
+7
+5
-14
-4
-5
-12
+7
-5
+17
+5
-13
-12
+15
+22
-5
-6
-12
+20
+4
+2
+17
-1
+18
-7
-1
-17
+11
-12
-5
-2
+9
+2
-6
-17
-1
+2
-3
+15
+19
+9
-8
+13
+1
+11
+16
+3
-16
-7
-15
-15
+12
+16
+18
+1
-9
+16
-9
-19
+17
+1
-15
+13
-9
-8
-1
+7
+17
+13
+15
-17
-3
+12
-10
+5
+4
-16
+15
+3
+19
+1
-2
+19
-16
-11
+4
-10
-8
+13
+13
+19
-6
-19
+1
-4
+18
+15
+16
-18
+12
+3
-9
+8
+3
-9
+11
+4
+8
+1
+6
-10
-3
+15
+16
+15
+12
-14
+4
-14
-7
-3
+14
+4
+3
-6
-7
+11
-2
-18
+17
-3
+14
+18
+6
+8
+18
-13
-7
+17
-18
-10
-15
+13
-16
+5
-10
+15
-8
-4
+14
+13
-10
-14
+7
+5
+13
-4
+12
+3
+14
-7
+6
+12
+17
-18
+3
-6
-3
-14
-1
+13
+19
+3
+9
+4
+11
+12
+3
+1
+14
+7
-17
+12
+11
+6
-7
+4
-11
-1
+6
-19
-10
-16
-2
-19
+7
+9
-3
+5
+12
+15
+8
+11
+1
+8
+15
-9
-9
-8
-10
-3
-16
+7
-17
+9
-5
+16
-15
-4
+15
-5
-25
-6
+1
+4
+17
+19
-13
+17
+7
+19
+2
+4
+10
+16
-9
+19
+13
+3
-10
+9
+5
+1
+18
-11
-14
-4
-5
-13
-7
-12
+2
+3
+6
-16
-1
+13
-10
-4
-1
-3
+9
+22
+4
-18
+17
+11
-21
-17
-18
-8
+12
+6
+15
+12
+10
-7
+18
+10
-8
-10
-18
+11
-17
+25
+15
-9
-19
+38
-3
-6
-23
+34
-25
-5
-12
+25
+14
+17
+30
+3
+9
-8
+16
+21
+21
+4
-12
+23
-13
+9
+3
+6
+13
+15
+6
-7
+15
+12
-10
+13
+12
-7
+13
+4
-9
+18
-10
+5
+8
-7
+2
-14
-12
-1
-6
-16
-18
-3
+1
+12
-6
+15
-17
+15
+13
+6
-15
+26
+1
-21
-3
-21
-4
+14
-1
-19
-11
+13
-10
-14
+2
-17
-23
+25
-16
+8
-30
+17
-44
+13
-19
+5
-9
-12
+10
+14
+17
+24
-15
+7
-61
-103
-18
+21
-22
-6
-9
-6
-9
-7
-15
-17
+4
-1
+10
+8
+14
-4
+15
-16
-6
-16
-15
-12
+15
+10
-15
+3
+15
-10
-17
+3
-5
-12
+4
+3
-37
-7
+14
-18
-8
+6
-11
+14
+30
+7
+23
+39
-12
+11
-8
+11
-1
+56
-28
-12
+7
+34
+47
+21
+88
+61
+18
+10
-99
-287
+26
-858
-209
-61255
+2
-7
-8
+12
+18
+17
-14
-2
+14
+4
+3
+3
-15
+21
+3
+20
+1
+3
-1
-25
-2
+7
-9
+17
-19
-6
-13
+2
-4
-3
-14
-8
+12
-20
+17
-40
+11
+3
-20
-16
-18
-3
-6
-10
+4
+20
-12
-3
+11
+16
-2
+4
-9
+28
-12
+5
+17
-13
+35
+25
+2
+35
-17
-8
+31
+3
-39
-46
+3
-96
-18
-14
-14
-12
+9
+15
+3
+18
-8
+1
-2
-15
+13
+14
-13
-3
+7
-11
-15
-17
-12
-15
-17
+9
+7
-10
-8
-3
+9
+16
+3
+15
-14
-5
-9
+1
-3
+10
+3
-18
-21
-11
+2
-17
-17
-7
-11
+8
+11
-2
-7
-1
-19
-2
-16
+1
+5
+11
+18
+5
+17
+2
-5
-2
+19
-4
+12
+2
+20
-13
-20
-12
+10
+4
+14
-1
+12
+13
-10
-13
-8
-1
+14
+16
+6
+10
+18
+19
+14
-1
+6
-13
-9
+10
-20
+1
+1
-12
+6
+7
-15
-13
-2
+14
-19
-5
-10
-17
+15
-5
+8
+20
+9
+14
-6
+4
-3
+19
+18
-14
-3
-8
+4
+16
+7
-3
-5
+19
-2
+12
+19
+12
-10
-17
-40
+1
-11
+19
-27
-9
+45
-27
+31
+1
-25
+41
+58
-5
-39
-112
+1
-8
-3
-6
-15
-3
-9
+13
+13
-24
+3
-4
+13
-19
-21
+16
-20
-10
-15
-16
-1
-13
-12
-17
+16
+17
+16
-2
-9
-1
-19
+8
+5
-18
+17
-19
-19
-12
+14
-18
-12
+10
+9
-13
-8
+19
+16
+13
-5
+2
+16
-15
+17
+9
+10
+2
-5
+20
+16
-8
-4
+16
+6
-7
-2
-11
+18
+11
-1
+2
+5
+3
+40
-38
+22
-11
-15
-27
+7
-25
+4
-11
-15
-12
+15
-20
-13
+9
-13
+7
-5
+10
+18
+24
+8
+15
-6
-10
-10
-1
-4
-3
-17
+7
-15
+20
-19
-18
-14
-4
-26
-22
-5
+17
+6
+13
+9
+7
+28
-11
-8
+57
-23
-37
-11
-43
+3
-14
+3
-14
+13
-15
+6
-23
+8
+12
-8
+15
+16
+2
-9
-14
+18
+19
-1
-43
-2
-3
-13
+5
-6
-13
-20
+15
+13
-12
+3
+2
+3
+11
+7
-17
-8
-13
+18
-17
-2
-13
+5
+3
+1
-11
+20
+4
+2
-1
-19
-8
-19
+1
-6
-12
+8
-6
-5
+1
+6
+9
-12
+13
+10
-14
+20
-11
+9
+9
-3
-18
+9
-5
+9
+2
-9
-19
-4
-10
+7
-8
+68
+30
+2
-9
+12
-65
+15
-26
-9
-15
-67
-38
-36
-37
-7
+18
-20
-44
+35
-70
-85
+14
+18
-499
+209
-61690
-5
+15
-4
+3
+5
+6
+15
+16
+3
-4
+12
-14
-7
-9
-15
+2
-1
-11
-21
-8
-2
-15
+19
+7
-10
-19
-3
-14
+4
+9
+13
-16
-14
+2
+10
-19
+6
+16
+11
+7
-14
-9
-21
-7
-12
+2
+12
-6
+125503