如何处理C++大数据开发中的数据查询效率?

#include <unordered_map>
#include <iostream>

int main() {
    std::unordered_map<int, std::string> data;
    data.insert({1, "John"});
    data.insert({2, "Amy"});
    
    // 查询键为2的数据
    auto it = data.find(2);
    if (it != data.end()) {
        std::cout << it->second << std::endl;
    }
    
    return 0;
}

#include <map>
#include <iostream>

int main() {
    std::map<int, std::string> data;
    data.insert({1, "John"});
    data.insert({2, "Amy"});
    
    // 查询键为2的数据
    auto it = data.find(2);
    if (it != data.end()) {
        std::cout << it->second << std::endl;
    }
    
    return 0;
}

#include <algorithm>
#include <iostream>
#include <vector>

int main() {
    std::vector<int> data = {1, 3, 5, 7, 9};
    
    int target = 5;
    int low = 0;
    int high = data.size() - 1;
    
    while (low <= high) {
        int mid = low + (high - low) / 2;
        if (data[mid] == target) {
            std::cout << "找到目标数据：" << data[mid] << std::endl;
            break;
        } else if (data[mid] < target) {
            low = mid + 1;
        } else {
            high = mid - 1;
        }
    }
    
    return 0;
}

#include <iostream>
#include <vector>
#include <omp.h>

int main() {
    std::vector<int> data = {1, 2, 3, 4, 5};
    int target = 3;
  
    #pragma omp parallel for
    for (int i = 0; i < data.size(); i++) {
        if (data[i] == target) {
            std::cout << "找到目标数据：" << data[i] << std::endl;
        }
    }

    return 0;
}