Learn how to efficiently find elements in a C++ std::vector using custom comparators, especially for large datasets. Implementing custom comparison logic can greatly enhance the performance of search operations and allow for tailored logic to meet specific requirements.
custom comparator, C++ std::vector, large datasets, find elements, search performance
#include <iostream>
#include <vector>
#include <algorithm>
struct CustomComparator {
bool operator()(const int& a, const int& b) const {
return a < b; // Define your custom comparison logic here
}
};
int main() {
std::vector<int> numbers = {5, 3, 8, 6, 2, 7, 4, 1};
// Sort the vector using custom comparator
std::sort(numbers.begin(), numbers.end(), CustomComparator());
// Finding an element using binary search with custom comparator
int target = 5;
bool found = std::binary_search(numbers.begin(), numbers.end(), target, CustomComparator());
if(found) {
std::cout << "Element " << target << " found in the vector!" << std::endl;
} else {
std::cout << "Element " << target << " not found in the vector." << std::endl;
}
return 0;
}
How do I avoid rehashing overhead with std::set in multithreaded code?
How do I find elements with custom comparators with std::set for embedded targets?
How do I erase elements while iterating with std::set for embedded targets?
How do I provide stable iteration order with std::unordered_map for large datasets?
How do I reserve capacity ahead of time with std::unordered_map for large datasets?
How do I erase elements while iterating with std::unordered_map in multithreaded code?
How do I provide stable iteration order with std::map for embedded targets?
How do I provide stable iteration order with std::map in multithreaded code?
How do I avoid rehashing overhead with std::map in performance-sensitive code?
How do I merge two containers efficiently with std::map for embedded targets?