Count distinct elements from a range of a sorted sequence from a given frequency array
Last Updated :
23 Jul, 2025
Given two integers L and R and an array arr[] consisting of N positive integers( 1-based indexing ) such that the frequency of ith element of a sorted sequence, say A[], is arr[i]. The task is to find the number of distinct elements from the range [L, R] in the sequence A[].
Examples:
Input: arr[] = {3, 6, 7, 1, 8}, L = 3, R = 7
Output: 2
Explanation: From the given frequency array, the sorted array will be {1, 1, 1, 2, 2, 2, 2, 2, 2, 3, 3, 3, ....}. Now, the number of distinct elements from the range [3, 7] is 2( = {1, 2}).
Input: arr[] = {1, 2, 3, 4}, L = 3, R = 4
Output: 2
Naive Approach: The simplest approach to solve the given problem is to construct the sorted sequence from the given array arr[] using the given frequencies and then traverse the constructed array over the range [L, R] to count the number of distinct elements.
Code-
C++
// C++ program for the above approach
#include<bits/stdc++.h>
using namespace std;
// Function to count the number of
// distinct elements over the range
// [L, R] in the sorted sequence
void countDistinct(vector<int> arr,
int L, int R)
{
vector<int> vec;
for(int i=0;i<arr.size();i++){
int temp=arr[i];
for(int j=0;j<temp;j++){
vec.push_back(i+1);
}
}
int curr=INT_MIN;
int count=0;
for(int i=L-1;i<R;i++){
if(curr!=vec[i]){
count++;
curr=vec[i];
}
}
cout<<count<<endl;
}
// Driver Code
int main()
{
vector<int> arr{ 3, 6, 7, 1, 8 };
int L = 3;
int R = 7;
countDistinct(arr, L, R);
}
import java.util.*;
class GFG {
// Function to count the number of
// distinct elements over the range
// [L, R] in the sorted sequence
static void countDistinct(ArrayList<Integer> arr, int L,
int R)
{
ArrayList<Integer> vec = new ArrayList<Integer>();
for (int i = 0; i < arr.size(); i++) {
int temp = arr.get(i);
for (int j = 0; j < temp; j++) {
vec.add(i + 1);
}
}
int curr = Integer.MIN_VALUE;
int count = 0;
for (int i = L - 1; i < R; i++) {
if (curr != vec.get(i)) {
count++;
curr = vec.get(i);
}
}
System.out.println(count);
}
// Driver Code
public static void main(String[] args)
{
ArrayList<Integer> arr = new ArrayList<Integer>(
Arrays.asList(3, 6, 7, 1, 8));
int L = 3;
int R = 7;
countDistinct(arr, L, R);
}
}
# Python program for the above approach
def countDistinct(arr, L, R):
# create a new vector
vec = []
for i in range(len(arr)):
temp = arr[i]
for j in range(temp):
vec.append(i+1)
curr = float('-inf')
count = 0
for i in range(L-1, R):
if curr != vec[i]:
count += 1
curr = vec[i]
print(count)
# Driver Code
if __name__ == '__main__':
arr = [3, 6, 7, 1, 8]
L = 3
R = 7
countDistinct(arr, L, R)
using System;
using System.Collections.Generic;
class GFG
{
// Function to count the number of distinct elements over the range
// [L, R] in the sorted sequence
static void CountDistinct(List<int> arr, int L, int R)
{
List<int> vec = new List<int>();
// Create a sorted sequence with occurrences of elements from the input array
foreach (int temp in arr)
{
for (int j = 0; j < temp; j++)
{
vec.Add(arr.IndexOf(temp) + 1);
}
}
int curr = int.MinValue;
int count = 0;
// Count the number of distinct elements in the range [L, R]
for (int i = L - 1; i < R; i++)
{
if (curr != vec[i])
{
count++;
curr = vec[i];
}
}
Console.WriteLine(count);
}
// Driver Code
static void Main()
{
List<int> arr = new List<int> { 3, 6, 7, 1, 8 };
int L = 3;
int R = 7;
CountDistinct(arr, L, R);
}
}
// Function to count the number of
// distinct elements over the range
// [L, R] in the sorted sequence
function countDistinct(arr, L, R) {
// creating sorted sequence
let vec = [];
for (let i = 0; i < arr.length; i++) {
let temp = arr[i];
for (let j = 0; j < temp; j++) {
vec.push(i + 1);
}
}
// Counting distinct elements
let curr = Number.MIN_SAFE_INTEGER;
let count = 0;
for (let i = L - 1; i < R; i++) {
if (curr !== vec[i]) {
count++;
curr = vec[i];
}
}
console.log(count);
}
// test case
let arr = [3, 6, 7, 1, 8];
let L = 3;
let R = 7;
countDistinct(arr, L, R);
Time Complexity: O(S + R - L)
Auxiliary Space: O(S), where S is the sum of the array elements.
Efficient Approach: The above approach can be optimized by using the Binary Search and the prefix sum technique to find the number of distinct elements over the range [L, R]. Follow the steps below to solve the given problem:
- Initialize an auxiliary array, say prefix[] that stores the prefix sum of the given array elements.
- Find the prefix sum of the given array and stored it in the array prefix[].
- By using binary search, find the first index at which the value in prefix[] is at least L, say left.
- By using binary search, find the first index at which the value in prefix[] is at least R, say right.
- After completing the above steps, print the value of (right - left + 1) as the result.
Below is the implementation of the above approach:
C++
// C++ program for the above approach
#include<bits/stdc++.h>
using namespace std;
// Function to find the first index
// with value is at least element
int binarysearch(int array[], int right,
int element)
{
// Update the value of left
int left = 1;
// Update the value of right
// Binary search for the element
while (left <= right)
{
// Find the middle element
int mid = (left + right / 2);
if (array[mid] == element)
{
return mid;
}
// Check if the value lies
// between the elements at
// index mid - 1 and mid
if (mid - 1 > 0 && array[mid] > element &&
array[mid - 1] < element)
{
return mid;
}
// Check in the right subarray
else if (array[mid] < element)
{
// Update the value
// of left
left = mid + 1;
}
// Check in left subarray
else
{
// Update the value of
// right
right = mid - 1;
}
}
return 1;
}
// Function to count the number of
// distinct elements over the range
// [L, R] in the sorted sequence
void countDistinct(vector<int> arr,
int L, int R)
{
// Stores the count of distinct
// elements
int count = 0;
// Create the prefix sum array
int pref[arr.size() + 1];
for(int i = 1; i <= arr.size(); ++i)
{
// Update the value of count
count += arr[i - 1];
// Update the value of pref[i]
pref[i] = count;
}
// Calculating the first index
// of L and R using binary search
int left = binarysearch(pref, arr.size() + 1, L);
int right = binarysearch(pref, arr.size() + 1, R);
// Print the resultant count
cout << right - left + 1;
}
// Driver Code
int main()
{
vector<int> arr{ 3, 6, 7, 1, 8 };
int L = 3;
int R = 7;
countDistinct(arr, L, R);
}
// This code is contributed by ipg2016107
// Java program for the above approach
import java.io.*;
import java.util.*;
class GFG {
// Function to find the first index
// with value is at least element
static int binarysearch(int array[],
int element)
{
// Update the value of left
int left = 1;
// Update the value of right
int right = array.length - 1;
// Binary search for the element
while (left <= right) {
// Find the middle element
int mid = (int)(left + right / 2);
if (array[mid] == element) {
return mid;
}
// Check if the value lies
// between the elements at
// index mid - 1 and mid
if (mid - 1 > 0
&& array[mid] > element
&& array[mid - 1] < element) {
return mid;
}
// Check in the right subarray
else if (array[mid] < element) {
// Update the value
// of left
left = mid + 1;
}
// Check in left subarray
else {
// Update the value of
// right
right = mid - 1;
}
}
return 1;
}
// Function to count the number of
// distinct elements over the range
// [L, R] in the sorted sequence
static void countDistinct(int arr[],
int L, int R)
{
// Stores the count of distinct
// elements
int count = 0;
// Create the prefix sum array
int pref[] = new int[arr.length + 1];
for (int i = 1; i <= arr.length; ++i) {
// Update the value of count
count += arr[i - 1];
// Update the value of pref[i]
pref[i] = count;
}
// Calculating the first index
// of L and R using binary search
int left = binarysearch(pref, L);
int right = binarysearch(pref, R);
// Print the resultant count
System.out.println(
(right - left) + 1);
}
// Driver Code
public static void main(String[] args)
{
int arr[] = { 3, 6, 7, 1, 8 };
int L = 3;
int R = 7;
countDistinct(arr, L, R);
}
}
# Python3 program for the above approach
# Function to find the first index
# with value is at least element
def binarysearch(array, right,
element):
# Update the value of left
left = 1
# Update the value of right
# Binary search for the element
while (left <= right):
# Find the middle element
mid = (left + right // 2)
if (array[mid] == element):
return mid
# Check if the value lies
# between the elements at
# index mid - 1 and mid
if (mid - 1 > 0 and array[mid] > element and
array[mid - 1] < element):
return mid
# Check in the right subarray
elif (array[mid] < element):
# Update the value
# of left
left = mid + 1
# Check in left subarray
else:
# Update the value of
# right
right = mid - 1
return 1
# Function to count the number of
# distinct elements over the range
# [L, R] in the sorted sequence
def countDistinct(arr, L, R):
# Stores the count of distinct
# elements
count = 0
# Create the prefix sum array
pref = [0] * (len(arr) + 1)
for i in range(1, len(arr) + 1):
# Update the value of count
count += arr[i - 1]
# Update the value of pref[i]
pref[i] = count
# Calculating the first index
# of L and R using binary search
left = binarysearch(pref, len(arr) + 1, L)
right = binarysearch(pref, len(arr) + 1, R)
# Print the resultant count
print(right - left + 1)
# Driver Code
if __name__ == "__main__":
arr = [ 3, 6, 7, 1, 8 ]
L = 3
R = 7
countDistinct(arr, L, R)
# This code is contributed by ukasp
// C# program for the above approach
using System;
using System.Collections.Generic;
class GFG{
// Function to find the first index
// with value is at least element
static int binarysearch(int []array, int right,
int element)
{
// Update the value of left
int left = 1;
// Update the value of right
// Binary search for the element
while (left <= right)
{
// Find the middle element
int mid = (left + right / 2);
if (array[mid] == element)
{
return mid;
}
// Check if the value lies
// between the elements at
// index mid - 1 and mid
if (mid - 1 > 0 && array[mid] > element &&
array[mid - 1] < element)
{
return mid;
}
// Check in the right subarray
else if (array[mid] < element)
{
// Update the value
// of left
left = mid + 1;
}
// Check in left subarray
else
{
// Update the value of
// right
right = mid - 1;
}
}
return 1;
}
// Function to count the number of
// distinct elements over the range
// [L, R] in the sorted sequence
static void countDistinct(List<int> arr,
int L, int R)
{
// Stores the count of distinct
// elements
int count = 0;
// Create the prefix sum array
int []pref = new int[arr.Count + 1];
for(int i = 1; i <= arr.Count; ++i)
{
// Update the value of count
count += arr[i - 1];
// Update the value of pref[i]
pref[i] = count;
}
// Calculating the first index
// of L and R using binary search
int left = binarysearch(pref, arr.Count + 1, L);
int right = binarysearch(pref, arr.Count + 1, R);
// Print the resultant count
Console.Write(right - left + 1);
}
// Driver Code
public static void Main()
{
List<int> arr = new List<int>(){ 3, 6, 7, 1, 8 };
int L = 3;
int R = 7;
countDistinct(arr, L, R);
}
}
// This code is contributed by SURENDRA_GANGWAR
<script>
// Javascript program for the above approach
// Function to find the first index
// with value is at least element
function binarysearch(array, right, element)
{
// Update the value of left
let left = 1;
// Update the value of right
// Binary search for the element
while (left <= right)
{
// Find the middle element
let mid = Math.floor((left + right / 2));
if (array[mid] == element)
{
return mid;
}
// Check if the value lies
// between the elements at
// index mid - 1 and mid
if (mid - 1 > 0 && array[mid] > element &&
array[mid - 1] < element)
{
return mid;
}
// Check in the right subarray
else if (array[mid] < element)
{
// Update the value
// of left
left = mid + 1;
}
// Check in left subarray
else
{
// Update the value of
// right
right = mid - 1;
}
}
return 1;
}
// Function to count the number of
// distinct elements over the range
// [L, R] in the sorted sequence
function countDistinct(arr, L, R)
{
// Stores the count of distinct
// elements
let count = 0;
// Create the prefix sum array
let pref = Array.from(
{length: arr.length + 1}, (_, i) => 0);
for(let i = 1; i <= arr.length; ++i)
{
// Update the value of count
count += arr[i - 1];
// Update the value of pref[i]
pref[i] = count;
}
// Calculating the first index
// of L and R using binary search
let left = binarysearch(pref, arr.length + 1, L);
let right = binarysearch(pref, arr.length + 1, R);
// Print the resultant count
document.write((right - left) + 1);
}
// Driver Code
let arr = [ 3, 6, 7, 1, 8 ];
let L = 3;
let R = 7;
countDistinct(arr, L, R);
// This code is contributed by susmitakundugoaldanga
</script>
Time Complexity: O(log(N))
Auxiliary Space: O(N)
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