Smallest subarray with k distinct numbers Last Updated : 28 Feb, 2025 Comments Improve Suggest changes Like Article Like Report We are given an array consisting of n integers and an integer k. We need to find the smallest subarray [l, r] (both l and r are inclusive) such that there are exactly k different numbers. If no such subarray exists, print -1 and If multiple subarrays meet the criteria, return the one with the smallest starting index.Examples:Input: arr[] = { 1, 1, 2, 2, 3, 3, 4, 5} k = 3Output: 5 7Explanation: K Different numbers are present in range of [5,7] with the minimum range.Input: arr[] = { 1, 2, 2, 3} k = 2Output: 0 1Explanation: K Different numbers are present in range of [0,2] , with the minimum length and index.Input: arr[] = {1, 1, 2, 1, 2} k = 3Output: Invalid kExplanation: K Different Number is not present the array.Table of Content[Naive Approach] Generate all the Subarrays - O(n^2) Time and O(n) Space[Expected Approach] Sliding Window Approach - O(n) Time and O(k) Space[Naive Approach] Generate all the Subarrays - O(n^2) Time and O(n) SpaceWe use nested for loops to generate all possible subarrays. For each subarray, we check if it contains exactly k distinct numbers. If it does, we compare its length with the current minimum and update l and r accordingly. If not find any subarray that contain k distinct numbers return -1. C++ #include <bits/stdc++.h> using namespace std; // Prints the minimum range that contains exactly // k distinct numbers. void minRange(vector<int> &arr, int n, int k) { // Starting and ending index of resultant subarray int start = 0, end = n; // Selecting each element as the start index for // subarray for (int i = 0; i < n; i++) { // Initialize a set to store all distinct elements unordered_set<int> set; // Selecting the end index for subarray int j; for (j = i; j < n; j++) { set.insert(arr[j]); /* If set contains exactly k elements, then check subarray[i, j] is smaller in size than the current resultant subarray */ if (set.size() == k) { if (j - i < end - start) { start = i; end = j; } // There are already k distinct elements // now, no need to consider further elements break; } } // If there are no k distinct elements // left in the array starting from index i we will // break if (j == n) { break; } } // If no window found then print -1 if (start == 0 && end == n) cout << -1; else cout << start << " " << end; } // Driver code for above function. int main() { vector<int> arr = { 1, 2, 3, 4, 5 }; int n = arr.size(); int k = 3; minRange(arr, n, k); return 0; } Java import java.util.*; import java.util.ArrayList; import java.util.HashSet; class GFG { // Prints the minimum range // that contains exactly k // distinct numbers. static void minRange(int arr[], int n, int k) { // start -> start index of resultant subarray // end -> end index of resultant subarray int start = 0; int end = n; // Selecting each element as the start index for // subarray for (int i = 0; i < n; i++) { // Initialize a set to store all distinct // elements HashSet<Integer> set = new HashSet<Integer>(); // Selecting the end index for subarray int j; for (j = i; j < n; j++) { set.add(arr[j]); /* If set contains exactly k elements,then check subarray[i, j] is smaller in size than the current resultant subarray */ if (set.size() == k) { if (j - i < end - start) { start = i; end = j; } // There are already 'k' distinct // elements now, no need to consider // further elements break; } } // If there are no k distinct elements left // in the array starting from index i we will break if (j == n) break; } // If no window found then print -1 if (start == 0 && end == n) System.out.println(-1); else System.out.println(start + " " + end); } // Driver code public static void main(String args[]) { int arr[] = { 1, 2, 3, 4, 5 }; int n = arr.length; int k = 3; minRange(arr, n, k); } } Python # Prints the minimum range that contains # exactly k distinct numbers. def minRange(arr, n, k): l = 0 r = n # Consider every element as # starting point. for i in range(n): # Find the smallest window starting # with arr[i] and containing exactly # k distinct elements. s = [] for j in range(i, n) : s.append(arr[j]) if (len(s) == k): if ((j - i) < (r - l)) : r = j l = i break # There are less than k distinct # elements now, so no need to continue. if (j == n): break # If there was no window with k distinct # elements (k is greater than total # distinct elements) if (l == 0 and r == n): print(-1) else: print(l, r) # Driver code if __name__ == "__main__": arr = [ 1, 2, 3, 4, 5 ] n = len(arr) k = 3 minRange(arr, n, k) C# using System; using System.Collections.Generic; public class GFG { // Prints the minimum range // that contains exactly k // distinct numbers. public static void minRange(int[] arr, int n, int k) { int l = 0, r = n; // Consider every element // as starting point. for (int i = 0; i < n; i++) { // Find the smallest window // starting with arr[i] and // containing exactly k // distinct elements. ISet<int> s = new HashSet<int>(); int j; for (j = i; j < n; j++) { s.Add(arr[j]); if (s.Count == k) { if ((j - i) < (r - l)) { r = j; l = i; } break; } } // There are less than k // distinct elements now, // so no need to continue. if (j == n) { break; } } // If there was no window // with k distinct elements // (k is greater than total // distinct elements) if (l == 0 && r == n) { Console.WriteLine(-1); } else { Console.WriteLine(l + " " + r); } } // Driver code public static void Main(string[] args) { int[] arr = new int[] {1, 2, 3, 4, 5}; int n = arr.Length; int k = 3; minRange(arr, n, k); } } JavaScript // Prints the minimum range // that contains exactly k // distinct numbers. function minRange(arr, n, k) { let l = 0, r = n; // Consider every element // as starting point. for (let i = 0; i < n; i++) { // Find the smallest window // starting with arr[i] and // containing exactly k // distinct elements. let s = new Set(); let j; for (j = i; j < n; j++) { s.add(arr[j]); if (s.size == k) { if ((j - i) < (r - l)) { r = j; l = i; } break; } } // There are less than k // distinct elements now, // so no need to continue. if (j == n) break; } // If there was no window // with k distinct elements // (k is greater than total // distinct elements) if (l == 0 && r == n) console.log(-1); else console.log(l + " " + r); } // Driver code let arr = [ 1, 2, 3, 4, 5 ]; let n = arr.length; let k = 3; minRange(arr, n, k); Output0 2[Expected Approach] Sliding Window Approach - O(n) Time and O(k) SpaceWe can solve this problem efficiently using the Sliding Window technique with a map (hash table) to track the count of distinct numbers in the current window. We expand the window by moving the right pointer (r) until we have at least k distinct elements. If the number of distinct elements is greater than or equal to k, we attempt to shrink the window from the left (l) while maintaining the condition. Whenever we find a valid window, we check if it is the smallest possible and update our result accordingly. C++ #include <bits/stdc++.h> using namespace std; // prints the minimum range that contains exactly // k distinct numbers. void minRange(vector<int> arr, int n, int k) { /* start = starting index of resultant subarray end = ending index of resultant subarray */ int start = 0, end = n; unordered_map<int, int> map; /* i = starting index of the window (on left side) j = ending index of the window (on right side) */ int i = 0, j = 0; while (j < n) { // Add the current element to the map map[arr[j]]++; j++; // Nothing to do when having less element if (map.size() < k) continue; /* If map contains exactly k elements, consider subarray[i, j - 1] keep removing left most elements */ while (map.size() == k) { // as considering the (j-1)th and i-th index int windowLen = (j - 1) - i + 1; int subArrayLen = end - start + 1; if (subArrayLen > windowLen) { start = i; end = j - 1; } // Remove elements from left // If freq == 1 then totally erase if (map[arr[i]] == 1) map.erase(arr[i]); // decrease freq by 1 else map[arr[i]]--; // move the starting index of window i++; } } if (start == 0 && end == n) cout << -1 << endl; else cout << start << " " << end << endl; } // Driver code for above function. int main() { vector<int> arr = { 1, 1, 2, 2, 3, 3, 4, 5 }; int n = arr.size(); int k = 3; minRange(arr, n, k); return 0; } Java import java.util.*; class GFG { // Prints the minimum range that contains exactly // k distinct numbers. static void minRange(int arr[], int n, int k) { /* start = starting index of resultant subarray end = ending index of resultant subarray */ int start = 0, end = n; HashMap<Integer, Integer> map = new HashMap<>(); /* i = starting index of the window (on left side) j = ending index of the window (on right side) */ int i = 0, j = 0; while (j < n) { // Add the current element to the map map.put(arr[j], map.getOrDefault(arr[j], 0) + 1); j++; // Nothing to do when having less element if (map.size() < k) continue; /* If map contains exactly k elements, consider subarray[i, j - 1] keep removing left most elements */ while (map.size() == k) { // as considering the (j-1)th and i-th index int windowLen = (j - 1) - i + 1; int subArrayLen = end - start + 1; if (windowLen < subArrayLen) { start = i; end = j - 1; } // Remove elements from left // If freq == 1 then totally erase if (map.get(arr[i]) == 1) map.remove(arr[i]); // decrease freq by 1 else map.put(arr[i], map.get(arr[i]) - 1); // move the starting index of window i++; } } if (start == 0 && end == n) System.out.println(-1); else System.out.println(start + " " + end); } // Driver code public static void main(String[] args) { int arr[] = { 1, 1, 2, 2, 3, 3, 4, 5 }; int n = arr.length; int k = 3; minRange(arr, n, k); } } Python from collections import defaultdict # Prints the minimum range that contains # exactly k distinct numbers. def minRange(arr, n, k): # Initially left and right side is -1 # and -1, number of distinct elements # are zero and range is n. l, r = 0, n i = 0 j = -1 # Initialize right side hm = defaultdict(lambda:0) while i < n: while j < n: # increment right side. j += 1 # if number of distinct elements less than k. if len(hm) < k and j < n: hm[arr[j]] += 1 # if distinct elements are equal to k # and length is less than previous length. if len(hm) == k and ((r - l) >= (j - i)): l, r = i, j break # if number of distinct elements less # than k, then break. if len(hm) < k: break # if distinct elements equals to k then # try to increment left side. while len(hm) == k: if hm[arr[i]] == 1: del(hm[arr[i]]) else: hm[arr[i]] -= 1 # increment left side. i += 1 # it is same as explained in above loop. if len(hm) == k and (r - l) >= (j - i): l, r = i, j if hm[arr[i]] == 1: del(hm[arr[i]]) else: hm[arr[i]] -= 1 i += 1 if l == 0 and r == n: print(-1) else: print(l, r) # Driver code for above function. if __name__ == "__main__": arr = [1, 1, 2, 2, 3, 3, 4, 5] n = len(arr) k = 3 minRange(arr, n, k) C# using System; using System.Collections.Generic; class GFG{ // Prints the minimum // range that contains exactly // k distinct numbers. static void minRange(int []arr, int n, int k) { // Initially left and // right side is -1 and -1, // number of distinct // elements are zero and // range is n. int l = 0, r = n; // Initialize right side int j = -1; Dictionary<int, int> hm = new Dictionary<int, int>(); for(int i = 0; i < n; i++) { while (j < n) { // Increment right side. j++; // If number of distinct elements less // than k. if (j < n && hm.Count < k) if(hm.ContainsKey(arr[j])) hm[arr[j]] = hm[arr[j]] + 1; else hm.Add(arr[j], 1); // If distinct elements are equal to k // and length is less than previous length. if (hm.Count == k && ((r - l) >= (j - i))) { l = i; r = j; break; } } // If number of distinct elements less // than k, then break. if (hm.Count < k) break; // If distinct elements equals to k then // try to increment left side. while (hm.Count == k) { if (hm.ContainsKey(arr[i]) && hm[arr[i]] == 1) hm.Remove(arr[i]); else { if(hm.ContainsKey(arr[i])) hm[arr[i]] = hm[arr[i]] - 1; } // Increment left side. i++; // It is same as explained in above loop. if (hm.Count == k && (r - l) >= (j - i)) { l = i; r = j; } } if (hm.ContainsKey(arr[i]) && hm[arr[i]] == 1) hm.Remove(arr[i]); else if(hm.ContainsKey(arr[i])) hm[arr[i]] = hm[arr[i]] - 1; } if (l == 0 && r == n) Console.WriteLine(-1); else Console.WriteLine(l + " " + r); } // Driver code public static void Main(String[] args) { int []arr = {1, 1, 2, 2, 3, 3, 4, 5}; int n = arr.Length; int k = 3; minRange(arr, n, k); } } JavaScript function minRange(arr, n, k) { // Initially left and right side is -1 and -1, // number of distinct elements are zero and // range is n. let l = 0, r = n; // Initialize right side let j = -1; let hm = new Map(); for (let i = 0; i < n; i++) { while (j < n) { // Increment right side. j++; // If number of distinct elements less // than k. if (j < n && hm.size < k) { if (hm.has(arr[j])) hm.set(arr[j], hm.get(arr[j]) + 1); else hm.set(arr[j], 1); } // If distinct elements are equal to k // and length is less than previous length. if (hm.size == k && ((r - l) >= (j - i))) { l = i; r = j; break; } } // If number of distinct elements less // than k, then break. if (hm.size < k) break; // If distinct elements equals to k then // try to increment left side. while (hm.size == k) { if (hm.has(arr[i]) && hm.get(arr[i]) == 1) hm.delete(arr[i]); else if (hm.has(arr[i])) hm.set(arr[i], hm.get(arr[i]) - 1); // Increment left side. i++; // It is same as explained in above loop. if (hm.size == k && (r - l) >= (j - i)) { l = i; r = j; } } if (hm.has(arr[i]) && hm.get(arr[i]) == 1) hm.delete(arr[i]); else if (hm.has(arr[i])) hm.set(arr[i], hm.get(arr[i]) - 1); } if (l == 0 && r == n) console.log(-1); else console.log(l + " " + r); } // Driver code let arr = [ 1, 1, 2, 2, 3, 3, 4, 5 ]; let n = arr.length; let k = 3; minRange(arr, n, k); Output5 7Related Problems:Count Distinct Elements In Every Window of Size K Find first negative integer in every k size window Maximum of all subarray of size K Maximum MEX of all subarray of size K Sum of minimum and maximum elements of all subarrays of given size K Comment More infoAdvertise with us R Rajdeep Mallick Improve Article Tags : Misc Hash DSA Arrays sliding-window cpp-unordered_map +2 More Practice Tags : ArraysHashMiscsliding-window Similar Reads Hashing in Data Structure Hashing is a technique used in data structures that efficiently stores and retrieves data in a way that allows for quick access. 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Input: arr[] = {1, 1, 1, 9 min read Count quadruples from four sorted arrays whose sum is equal to a given value xGiven four sorted arrays each of size n of distinct elements. Given a value x. The problem is to count all quadruples(group of four numbers) from all the four arrays whose sum is equal to x.Note: The quadruple has an element from each of the four arrays. Examples: Input : arr1 = {1, 4, 5, 6}, arr2 = 15+ min read Sort elements by frequency | Set 4 (Efficient approach using hash)Print the elements of an array in the decreasing frequency if 2 numbers have the same frequency then print the one which came first. Examples: Input : arr[] = {2, 5, 2, 8, 5, 6, 8, 8} Output : arr[] = {8, 8, 8, 2, 2, 5, 5, 6} Input : arr[] = {2, 5, 2, 6, -1, 9999999, 5, 8, 8, 8} Output : arr[] = {8, 12 min read Find all pairs (a, b) in an array such that a % b = kGiven an array with distinct elements, the task is to find the pairs in the array such that a % b = k, where k is a given integer. You may assume that a and b are in small range Examples : Input : arr[] = {2, 3, 5, 4, 7} k = 3Output : (7, 4), (3, 4), (3, 5), (3, 7)7 % 4 = 33 % 4 = 33 % 5 = 33 % 7 = 15 min read Group words with same set of charactersGiven a list of words with lower cases. Implement a function to find all Words that have the same unique character set. Example: Input: words[] = { "may", "student", "students", "dog", "studentssess", "god", "cat", "act", "tab", "bat", "flow", "wolf", "lambs", "amy", "yam", "balms", "looped", "poodl 8 min read k-th distinct (or non-repeating) element among unique elements in an array.Given an integer array arr[], print kth distinct element in this array. The given array may contain duplicates and the output should print the k-th element among all unique elements. If k is more than the number of distinct elements, print -1.Examples:Input: arr[] = {1, 2, 1, 3, 4, 2}, k = 2Output: 7 min read Intermediate problems on HashingFind Itinerary from a given list of ticketsGiven a list of tickets, find the itinerary in order using the given list.Note: It may be assumed that the input list of tickets is not cyclic and there is one ticket from every city except the final destination.Examples:Input: "Chennai" -> "Bangalore" "Bombay" -> "Delhi" "Goa" -> "Chennai" 11 min read Find number of Employees Under every ManagerGiven a 2d matrix of strings arr[][] of order n * 2, where each array arr[i] contains two strings, where the first string arr[i][0] is the employee and arr[i][1] is his manager. The task is to find the count of the number of employees under each manager in the hierarchy and not just their direct rep 9 min read Longest Subarray With Sum Divisible By KGiven an arr[] containing n integers and a positive integer k, he problem is to find the longest subarray's length with the sum of the elements divisible by k.Examples:Input: arr[] = [2, 7, 6, 1, 4, 5], k = 3Output: 4Explanation: The subarray [7, 6, 1, 4] has sum = 18, which is divisible by 3.Input: 10 min read Longest Subarray with 0 Sum Given an array arr[] of size n, the task is to find the length of the longest subarray with sum equal to 0.Examples:Input: arr[] = {15, -2, 2, -8, 1, 7, 10, 23}Output: 5Explanation: The longest subarray with sum equals to 0 is {-2, 2, -8, 1, 7}Input: arr[] = {1, 2, 3}Output: 0Explanation: There is n 10 min read Longest Increasing consecutive subsequenceGiven N elements, write a program that prints the length of the longest increasing consecutive subsequence. Examples: Input : a[] = {3, 10, 3, 11, 4, 5, 6, 7, 8, 12} Output : 6 Explanation: 3, 4, 5, 6, 7, 8 is the longest increasing subsequence whose adjacent element differs by one. Input : a[] = {6 10 min read Count Distinct Elements In Every Window of Size KGiven an array arr[] of size n and an integer k, return the count of distinct numbers in all windows of size k. Examples: Input: arr[] = [1, 2, 1, 3, 4, 2, 3], k = 4Output: [3, 4, 4, 3]Explanation: First window is [1, 2, 1, 3], count of distinct numbers is 3. Second window is [2, 1, 3, 4] count of d 10 min read Design a data structure that supports insert, delete, search and getRandom in constant timeDesign a data structure that supports the following operations in O(1) time.insert(x): Inserts an item x to the data structure if not already present.remove(x): Removes item x from the data structure if present. search(x): Searches an item x in the data structure.getRandom(): Returns a random elemen 5 min read Subarray with Given Sum - Handles Negative NumbersGiven an unsorted array of integers, find a subarray that adds to a given number. If there is more than one subarray with the sum of the given number, print any of them.Examples: Input: arr[] = {1, 4, 20, 3, 10, 5}, sum = 33Output: Sum found between indexes 2 and 4Explanation: Sum of elements betwee 13 min read Implementing our Own Hash Table with Separate Chaining in JavaAll data structure has their own special characteristics, for example, a BST is used when quick searching of an element (in log(n)) is required. A heap or a priority queue is used when the minimum or maximum element needs to be fetched in constant time. Similarly, a hash table is used to fetch, add 10 min read Implementing own Hash Table with Open Addressing Linear ProbingIn Open Addressing, all elements are stored in the hash table itself. So at any point, size of table must be greater than or equal to total number of keys (Note that we can increase table size by copying old data if needed).Insert(k) - Keep probing until an empty slot is found. Once an empty slot is 13 min read Maximum possible difference of two subsets of an arrayGiven an array of n-integers. The array may contain repetitive elements but the highest frequency of any element must not exceed two. You have to make two subsets such that the difference of the sum of their elements is maximum and both of them jointly contain all elements of the given array along w 15+ min read Sorting using trivial hash functionWe have read about various sorting algorithms such as heap sort, bubble sort, merge sort and others. Here we will see how can we sort N elements using a hash array. But this algorithm has a limitation. We can sort only those N elements, where the value of elements is not large (typically not above 1 15+ min read Smallest subarray with k distinct numbersWe are given an array consisting of n integers and an integer k. We need to find the smallest subarray [l, r] (both l and r are inclusive) such that there are exactly k different numbers. If no such subarray exists, print -1 and If multiple subarrays meet the criteria, return the one with the smalle 14 min read Like