Radix Sort – Data Structures and Algorithms Tutorials
Last Updated :
16 Feb, 2024
Radix Sort is a linear sorting algorithm that sorts elements by processing them digit by digit. It is an efficient sorting algorithm for integers or strings with fixed-size keys.Â
Rather than comparing elements directly, Radix Sort distributes the elements into buckets based on each digit’s value. By repeatedly sorting the elements by their significant digits, from the least significant to the most significant, Radix Sort achieves the final sorted order.
Radix Sort Algorithm
The key idea behind Radix Sort is to exploit the concept of place value. It assumes that sorting numbers digit by digit will eventually result in a fully sorted list. Radix Sort can be performed using different variations, such as Least Significant Digit (LSD) Radix Sort or Most Significant Digit (MSD) Radix Sort.
How does Radix Sort Algorithm work?
To perform radix sort on the array [170, 45, 75, 90, 802, 24, 2, 66], we follow these steps:
How does Radix Sort Algorithm work | Step 1
Step 1: Find the largest element in the array, which is 802. It has three digits, so we will iterate three times, once for each significant place.
Step 2: Sort the elements based on the unit place digits (X=0). We use a stable sorting technique, such as counting sort, to sort the digits at each significant place.
Sorting based on the unit place:
- Perform counting sort on the array based on the unit place digits.
- The sorted array based on the unit place is [170, 90, 802, 2, 24, 45, 75, 66].
How does Radix Sort Algorithm work | Step 2
Step 3: Sort the elements based on the tens place digits.
Sorting based on the tens place:
- Perform counting sort on the array based on the tens place digits.
- The sorted array based on the tens place is [802, 2, 24, 45, 66, 170, 75, 90].
How does Radix Sort Algorithm work | Step 3
Step 4: Sort the elements based on the hundreds place digits.
Sorting based on the hundreds place:
- Perform counting sort on the array based on the hundreds place digits.
- The sorted array based on the hundreds place is [2, 24, 45, 66, 75, 90, 170, 802].
How does Radix Sort Algorithm work | Step 4
Step 5: The array is now sorted in ascending order.
The final sorted array using radix sort is [2, 24, 45, 66, 75, 90, 170, 802].
How does Radix Sort Algorithm work | Step 5
Below is the implementation for the above illustrations:
C++
#include <iostream>
using namespace std;
int getMax( int arr[], int n)
{
int mx = arr[0];
for ( int i = 1; i < n; i++)
if (arr[i] > mx)
mx = arr[i];
return mx;
}
void countSort( int arr[], int n, int exp )
{
int output[n];
int i, count[10] = { 0 };
for (i = 0; i < n; i++)
count[(arr[i] / exp ) % 10]++;
for (i = 1; i < 10; i++)
count[i] += count[i - 1];
for (i = n - 1; i >= 0; i--) {
output[count[(arr[i] / exp ) % 10] - 1] = arr[i];
count[(arr[i] / exp ) % 10]--;
}
for (i = 0; i < n; i++)
arr[i] = output[i];
}
void radixsort( int arr[], int n)
{
int m = getMax(arr, n);
for ( int exp = 1; m / exp > 0; exp *= 10)
countSort(arr, n, exp );
}
void print( int arr[], int n)
{
for ( int i = 0; i < n; i++)
cout << arr[i] << " " ;
}
int main()
{
int arr[] = { 543, 986, 217, 765, 329 };
int n = sizeof (arr) / sizeof (arr[0]);
radixsort(arr, n);
print(arr, n);
return 0;
}
|
Java
import java.io.*;
import java.util.*;
class Radix {
static int getMax( int arr[], int n)
{
int mx = arr[ 0 ];
for ( int i = 1 ; i < n; i++)
if (arr[i] > mx)
mx = arr[i];
return mx;
}
static void countSort( int arr[], int n, int exp)
{
int output[] = new int [n];
int i;
int count[] = new int [ 10 ];
Arrays.fill(count, 0 );
for (i = 0 ; i < n; i++)
count[(arr[i] / exp) % 10 ]++;
for (i = 1 ; i < 10 ; i++)
count[i] += count[i - 1 ];
for (i = n - 1 ; i >= 0 ; i--) {
output[count[(arr[i] / exp) % 10 ] - 1 ] = arr[i];
count[(arr[i] / exp) % 10 ]--;
}
for (i = 0 ; i < n; i++)
arr[i] = output[i];
}
static void radixsort( int arr[], int n)
{
int m = getMax(arr, n);
for ( int exp = 1 ; m / exp > 0 ; exp *= 10 )
countSort(arr, n, exp);
}
static void print( int arr[], int n)
{
for ( int i = 0 ; i < n; i++)
System.out.print(arr[i] + " " );
}
public static void main(String[] args)
{
int arr[] = { 170 , 45 , 75 , 90 , 802 , 24 , 2 , 66 };
int n = arr.length;
radixsort(arr, n);
print(arr, n);
}
}
|
Python3
def countingSort(arr, exp1):
n = len (arr)
output = [ 0 ] * (n)
count = [ 0 ] * ( 10 )
for i in range ( 0 , n):
index = arr[i] / / exp1
count[index % 10 ] + = 1
for i in range ( 1 , 10 ):
count[i] + = count[i - 1 ]
i = n - 1
while i > = 0 :
index = arr[i] / / exp1
output[count[index % 10 ] - 1 ] = arr[i]
count[index % 10 ] - = 1
i - = 1
i = 0
for i in range ( 0 , len (arr)):
arr[i] = output[i]
def radixSort(arr):
max1 = max (arr)
exp = 1
while max1 / exp > = 1 :
countingSort(arr, exp)
exp * = 10
arr = [ 170 , 45 , 75 , 90 , 802 , 24 , 2 , 66 ]
radixSort(arr)
for i in range ( len (arr)):
print (arr[i], end = " " )
|
C#
using System;
class GFG {
public static int getMax( int [] arr, int n)
{
int mx = arr[0];
for ( int i = 1; i < n; i++)
if (arr[i] > mx)
mx = arr[i];
return mx;
}
public static void countSort( int [] arr, int n, int exp)
{
int [] output = new int [n];
int i;
int [] count = new int [10];
for (i = 0; i < 10; i++)
count[i] = 0;
for (i = 0; i < n; i++)
count[(arr[i] / exp) % 10]++;
for (i = 1; i < 10; i++)
count[i] += count[i - 1];
for (i = n - 1; i >= 0; i--) {
output[count[(arr[i] / exp) % 10] - 1] = arr[i];
count[(arr[i] / exp) % 10]--;
}
for (i = 0; i < n; i++)
arr[i] = output[i];
}
public static void radixsort( int [] arr, int n)
{
int m = getMax(arr, n);
for ( int exp = 1; m / exp > 0; exp *= 10)
countSort(arr, n, exp);
}
public static void print( int [] arr, int n)
{
for ( int i = 0; i < n; i++)
Console.Write(arr[i] + " " );
}
public static void Main()
{
int [] arr = { 170, 45, 75, 90, 802, 24, 2, 66 };
int n = arr.Length;
radixsort(arr, n);
print(arr, n);
}
}
|
Javascript
<script>
function getMax(arr,n)
{
let mx = arr[0];
for (let i = 1; i < n; i++)
if (arr[i] > mx)
mx = arr[i];
return mx;
}
function countSort(arr,n,exp)
{
let output = new Array(n);
let i;
let count = new Array(10);
for (let i=0;i<10;i++)
count[i]=0;
for (i = 0; i < n; i++)
let x = Math.floor(arr[i] / exp) % 10;
count[x]++;
for (i = 1; i < 10; i++)
count[i] += count[i - 1];
for (i = n - 1; i >= 0; i--) {
output[count[x] - 1] = arr[i];
count[x]--;
}
for (i = 0; i < n; i++)
arr[i] = output[i];
}
function radixsort(arr,n)
{
let m = getMax(arr, n);
for (let exp = 1; Math.floor(m / exp) > 0; exp *= 10)
countSort(arr, n, exp);
}
function print(arr,n)
{
for (let i = 0; i < n; i++)
document.write(arr[i] + " " );
}
let arr=[170, 45, 75, 90, 802, 24, 2, 66];
let n = arr.length;
radixsort(arr, n);
print(arr, n);
</script>
|
PHP
<?php
function countSort(& $arr , $n , $exp )
{
$output = array_fill (0, $n , 0);
$count = array_fill (0, 10, 0);
for ( $i = 0; $i < $n ; $i ++)
$count [ ( $arr [ $i ] / $exp ) % 10 ]++;
for ( $i = 1; $i < 10; $i ++)
$count [ $i ] += $count [ $i - 1];
for ( $i = $n - 1; $i >= 0; $i --)
{
$output [ $count [ ( $arr [ $i ] /
$exp ) % 10 ] - 1] = $arr [ $i ];
$count [ ( $arr [ $i ] / $exp ) % 10 ]--;
}
for ( $i = 0; $i < $n ; $i ++)
$arr [ $i ] = $output [ $i ];
}
function radixsort(& $arr , $n )
{
$m = max( $arr );
for ( $exp = 1; $m / $exp > 0; $exp *= 10)
countSort( $arr , $n , $exp );
}
function PrintArray(& $arr , $n )
{
for ( $i = 0; $i < $n ; $i ++)
echo $arr [ $i ] . " " ;
}
$arr = array (170, 45, 75, 90, 802, 24, 2, 66);
$n = count ( $arr );
radixsort( $arr , $n );
PrintArray( $arr , $n );
?>
|
Output
217 329 543 765 986
Time Complexity:Â
- Radix sort is a non-comparative integer sorting algorithm that sorts data with integer keys by grouping the keys by the individual digits which share the same significant position and value. It has a time complexity of O(d * (n + b)), where d is the number of digits, n is the number of elements, and b is the base of the number system being used.
- In practical implementations, radix sort is often faster than other comparison-based sorting algorithms, such as quicksort or merge sort, for large datasets, especially when the keys have many digits. However, its time complexity grows linearly with the number of digits, and so it is not as efficient for small datasets.
Auxiliary Space:Â
- Radix sort also has a space complexity of O(n + b), where n is the number of elements and b is the base of the number system. This space complexity comes from the need to create buckets for each digit value and to copy the elements back to the original array after each digit has been sorted.
Frequently Asked Questions about RadixSort
Q1. Is Radix Sort preferable to Comparison based sorting algorithms like Quick-Sort?Â
If we have log2n bits for every digit, the running time of Radix appears to be better than Quick Sort for a wide range of input numbers. The constant factors hidden in asymptotic notation are higher for Radix Sort and Quick-Sort uses hardware caches more effectively. Also, Radix sort uses counting sort as a subroutine and counting sort takes extra space to sort numbers.
Q2. What if the elements are in the range from 1 to n2?
- The lower bound for the Comparison based sorting algorithm (Merge Sort, Heap Sort, Quick-Sort .. etc) is Ω(nLogn), i.e., they cannot do better than nLogn. Counting sort is a linear time sorting algorithm that sort in O(n+k) time when elements are in the range from 1 to k.
- We can’t use counting sort because counting sort will take O(n2) which is worse than comparison-based sorting algorithms. Can we sort such an array in linear time?Â
- Radix Sort is the answer. The idea of Radix Sort is to do digit-by-digit sorting starting from the least significant digit to the most significant digit. Radix sort uses counting sort as a subroutine to sort.
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