Duplicate within K Distance in an Array
Last Updated :
23 Jul, 2025
Given an integer array arr[] and an integer k, determine whether there exist two indices i and j such that arr[i] == arr[j] and |i - j| ≤ k. If such a pair exists, return 'Yes', otherwise return 'No'.
Examples:
Input: k = 3, arr[] = [1, 2, 3, 4, 1, 2, 3, 4]
Output: No
Explanation: Each element in the given array arr[] appears twice and the distance between every element and its duplicate is 4.
Input: k = 3, arr[] = [1, 2, 3, 1, 4, 5]
Output: Yes
Explanation: 1 is present at index 0 and 3.
Input: k = 3, arr[] = [1, 2, 3, 4, 5]
Output: No
Explanation: There is no duplicate element in arr[].
[Naive Approach] - O(n * k) Time and O(1) Space
The idea is to run two loops. The outer loop picks every index i as a starting index, and the inner loop compares all elements which are within k distance of i, i.e. i + k.
Below is given the implementation:
C++
#include <bits/stdc++.h>
using namespace std;
bool checkDuplicatesWithinK(vector<int> &arr, int k)
{
int n = arr.size();
// Traverse for every element
for (int i = 0; i < n; i++) {
// Traverse next k elements
for (int c = 1; c <= k && (i + c) < n; c++) {
int j = i + c;
// If we find one more occurrence
// within k
if (arr[i] == arr[j])
return true;
}
}
return false;
}
// Driver method to test above method
int main()
{
vector<int> arr = {10, 5, 3, 4, 3, 5, 6};
if (checkDuplicatesWithinK(arr, 3))
cout << "Yes";
else
cout << "No";
return 0;
}
#include <stdio.h>
int checkDuplicatesWithinK(int arr[], int n, int k)
{
// Traverse for every element
for (int i = 0; i < n; i++) {
// Traverse next k elements
for (int c = 1; c <= k && (i + c) < n; c++) {
int j = i + c;
// If we find one more occurrence within k
if (arr[i] == arr[j])
return 1;
}
}
return 0;
}
// Driver method to test above method
int main()
{
int arr[] = {10, 5, 3, 4, 3, 5, 6};
int n = sizeof(arr) / sizeof(arr[0]);
printf("%s\n", checkDuplicatesWithinK(arr, n, 3) ? "Yes" : "No");
return 0;
}
import java.util.Arrays;
class GfG {
static boolean checkDuplicatesWithinK(int[] arr, int k) {
int n = arr.length;
// Traverse for every element
for (int i = 0; i < n; i++) {
// Traverse next k elements
for (int c = 1; c <= k && (i + c) < n; c++) {
int j = i + c;
// If we find one more occurrence within k
if (arr[i] == arr[j])
return true;
}
}
return false;
}
public static void main(String[] args) {
int[] arr = {10, 5, 3, 4, 3, 5, 6};
System.out.println(checkDuplicatesWithinK(arr, 3) ? "Yes" : "No");
}
}
def check_duplicates_within_k(arr, k):
n = len(arr)
# Traverse for every element
for i in range(n):
# Traverse next k elements
for c in range(1, k + 1):
j = i + c
# If we find one more occurrence within k
if j < n and arr[i] == arr[j]:
return True
return False
# Driver method to test above method
arr = [10, 5, 3, 4, 3, 5, 6]
print("Yes" if check_duplicates_within_k(arr, 3) else "No")
using System;
class GfG
{
static bool CheckDuplicatesWithinK(int[] arr, int k)
{
int n = arr.Length;
// Traverse for every element
for (int i = 0; i < n; i++)
{
// Traverse next k elements
for (int c = 1; c <= k && (i + c) < n; c++)
{
int j = i + c;
// If we find one more occurrence within k
if (arr[i] == arr[j])
return true;
}
}
return false;
}
public static void Main()
{
int[] arr = { 10, 5, 3, 4, 3, 5, 6 };
Console.WriteLine(CheckDuplicatesWithinK(arr, 3) ? "Yes" : "No");
}
}
function checkDuplicatesWithinK(arr, k) {
const n = arr.length;
// Traverse for every element
for (let i = 0; i < n; i++) {
// Traverse next k elements
for (let c = 1; c <= k && (i + c) < n; c++) {
const j = i + c;
// If we find one more occurrence within k
if (arr[i] === arr[j]) {
return true;
}
}
}
return false;
}
// Driver method to test above method
const arr = [10, 5, 3, 4, 3, 5, 6];
console.log(checkDuplicatesWithinK(arr, 3) ? "Yes" : "No");
Time Complexity: O(n * k), for each element of the array arr[], we are iterating up to next k elements.
Auxiliary Space: O(1)
[Expected Approach] - Using HashSet - O(n) Time and O(k) Space
The idea is to use HashSet to store elements of the array arr[] and check if there is any duplicate present within a k distance. Also remove elements that are present at more than k distance from the current element. Following is a detailed algorithm.
- Create an empty HashSet.
- Traverse all elements from left to right. Let the current element be 'arr[i]'
- If the current element 'arr[i]' is present in a HashSet, then return true.
- Else add arr[i] to hash and remove arr[i-k] from hash if i >= k
Below is given the implementation:
C++
#include <bits/stdc++.h>
using namespace std;
// C++ program to Check if a given array contains duplicate
// elements within k distance from each other
bool checkDuplicatesWithinK(vector<int> &arr, int k) {
// Creates an empty hashset
unordered_set<int> s;
// Traverse the input array
for (int i = 0; i < arr.size(); i++) {
// If already present in hash, then we found
// a duplicate within k distance
if (s.find(arr[i]) != s.end())
return true;
// Add this item to hashset
s.insert(arr[i]);
// Remove the k+1 distant item
if (i >= k)
s.erase(arr[i - k]);
}
return false;
}
// Driver method to test above method
int main () {
vector<int> arr = {10, 5, 3, 4, 3, 5, 6};
if (checkDuplicatesWithinK(arr, 3))
cout << "Yes";
else
cout << "No";
}
/* Java program to Check if a given array contains duplicate
elements within k distance from each other */
import java.util.*;
class Main
{
static boolean checkDuplicatesWithinK(int arr[], int k)
{
// Creates an empty hashset
HashSet<Integer> set = new HashSet<>();
// Traverse the input array
for (int i=0; i<arr.length; i++)
{
// If already present n hash, then we found
// a duplicate within k distance
if (set.contains(arr[i]))
return true;
// Add this item to hashset
set.add(arr[i]);
// Remove the k+1 distant item
if (i >= k)
set.remove(arr[i-k]);
}
return false;
}
// Driver method to test above method
public static void main (String[] args)
{
int arr[] = {10, 5, 3, 4, 3, 5, 6};
if (checkDuplicatesWithinK(arr, 3))
System.out.println("Yes");
else
System.out.println("No");
}
}
# Python 3 program to Check if a given array
# contains duplicate elements within k distance
# from each other
def checkDuplicatesWithinK(arr, n, k):
# Creates an empty list
myset = set()
# Traverse the input array
for i in range(n):
# If already present n hash, then we
# found a duplicate within k distance
if arr[i] in myset:
return True
# Add this item to hashset
myset.add(arr[i])
# Remove the k+1 distant item
if (i >= k):
myset.remove(arr[i - k])
return False
# Driver Code
if __name__ == "__main__":
arr = [10, 5, 3, 4, 3, 5, 6]
n = len(arr)
if (checkDuplicatesWithinK(arr, n, 3)):
print("Yes")
else:
print("No")
/* C# program to Check if a given
array contains duplicate elements
within k distance from each other */
using System;
using System.Collections.Generic;
class GFG
{
static bool checkDuplicatesWithinK(int []arr, int k)
{
// Creates an empty hashset
HashSet<int> set = new HashSet<int>();
// Traverse the input array
for (int i = 0; i < arr.Length; i++)
{
// If already present n hash, then we found
// a duplicate within k distance
if (set.Contains(arr[i]))
return true;
// Add this item to hashset
set.Add(arr[i]);
// Remove the k+1 distant item
if (i >= k)
set.Remove(arr[i - k]);
}
return false;
}
// Driver code
public static void Main (String[] args)
{
int []arr = {10, 5, 3, 4, 3, 5, 6};
if (checkDuplicatesWithinK(arr, 3))
Console.WriteLine("Yes");
else
Console.WriteLine("No");
}
}
// JavaScript program to Check if a given array contains duplicate
// elements within k distance from each other
function checkDuplicatesWithinK(arr, k) {
// Creates an empty hashset
const s = new Set();
// Traverse the input array
for (let i = 0; i < arr.length; i++) {
// If already present in hash, then we found
// a duplicate within k distance
if (s.has(arr[i]))
return true;
// Add this item to hashset
s.add(arr[i]);
// Remove the k+1 distant item
if (i >= k)
s.delete(arr[i - k]);
}
return false;
}
// Driver method to test above method
const arr = [10, 5, 3, 4, 3, 5, 6];
if (checkDuplicatesWithinK(arr, 3))
console.log('Yes');
else
console.log('No');
Time Complexity: O(n), as we are iterating through elements only once.
Auxiliary Space: O(k), to store the k elements in HashSet.
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