Implementing Counting Sort using map in C++
Last Updated :
23 May, 2023
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Counting Sort is one of the best sorting algorithms which can sort in O(n) time complexity but the disadvantage with the counting sort is it’s space complexity, for a small collection of values, it will also require a huge amount of unused space. So, we need two things to overcome this:
- A data structure which occupies the space for input elements only and not for all the elements other than inputs.
- The stored elements must be in sorted order because if it’s unsorted then storing them will be of no use.
So Map in C++ satisfies both the condition. Thus we can achieve this through a map.
Examples:
Input: arr[] = {1, 4, 3, 5, 1}
Output: 1 1 3 4 5
Input: arr[] = {1, -1, -3, 8, -3}
Output: -3 -3 -1 1 8
Below is the implementation of Counting Sort using map in C++:
- CPP
CPP
// C++ implementation of the approach #include <bits/stdc++.h> using namespace std; // Function to sort the array using counting sort void countingSort(vector< int > arr, int n) { // Map to store the frequency // of the array elements map< int , int > freqMap; for ( auto i = arr.begin(); i != arr.end(); i++) { freqMap[*i]++; } int i = 0; // For every element of the map for ( auto it : freqMap) { // Value of the element int val = it.first; // Its frequency int freq = it.second; for ( int j = 0; j < freq; j++) arr[i++] = val; } // Print the sorted array for ( auto i = arr.begin(); i != arr.end(); i++) { cout << *i << " " ; } } // Driver code int main() { vector< int > arr = { 1, 4, 3, 5, 1 }; int n = arr.size(); countingSort(arr, n); return 0; } |
Output:
1 1 3 4 5
Time Complexity: O(n log(n))
Auxiliary Space: O(n)