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
// 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)
Feeling lost in the world of random DSA topics, wasting time without progress? It’s time for a change! Join our DSA course, where we’ll guide you on an exciting journey to master DSA efficiently and on schedule.
Ready to dive in? Explore our Free Demo Content and join our DSA course, trusted by over 100,000 neveropen!
Ready to dive in? Explore our Free Demo Content and join our DSA course, trusted by over 100,000 neveropen!
