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Implementing own Hash Table with Open Addressing Linear Probing

Last Updated : 21 Feb, 2025
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In 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 found, insert k.
  • Search(k) - Keep probing until slot’s key doesn’t become equal to k or an empty slot is reached.
  • Delete(k) - Delete operation is interesting. If we simply delete a key, then search may fail. So slots of deleted keys are marked specially as “deleted”.

Here, to mark a node deleted we have used dummy node with key and value -1. 
Insert can insert an item in a deleted slot, but search doesn’t stop at a deleted slot.
The entire process ensures that for any key, we get an integer position within the size of the Hash Table to insert the corresponding value. 
So the process is simple, user gives a (key, value) pair set as input and based on the value generated by hash function an index is generated to where the value corresponding to the particular key is stored. So whenever we need to fetch a value corresponding to a key that is just O(1).
 

Implementation:

CPP
#include <bits/stdc++.h> using namespace std;  // template for generic type template <typename K, typename V>  // Hashnode class class HashNode { public:     V value;     K key;      // Constructor of hashnode     HashNode(K key, V value)     {         this->value = value;         this->key = key;     } };  // template for generic type template <typename K, typename V>  // Our own Hashmap class class HashMap {     // hash element array     HashNode<K, V>** arr;     int capacity;     // current size     int size;     // dummy node     HashNode<K, V>* dummy;  public:     HashMap()     {         // Initial capacity of hash array         capacity = 20;         size = 0;         arr = new HashNode<K, V>*[capacity];          // Initialise all elements of array as NULL         for (int i = 0; i < capacity; i++)             arr[i] = NULL;          // dummy node with value and key -1         dummy = new HashNode<K, V>(-1, -1);     }     // This implements hash function to find index     // for a key     int hashCode(K key) { return key % capacity; }      // Function to add key value pair     void insertNode(K key, V value)     {         HashNode<K, V>* temp             = new HashNode<K, V>(key, value);          // Apply hash function to find index for given key         int hashIndex = hashCode(key);          // find next free space         while (arr[hashIndex] != NULL                && arr[hashIndex]->key != key                && arr[hashIndex]->key != -1) {             hashIndex++;             hashIndex %= capacity;         }          // if new node to be inserted         // increase the current size         if (arr[hashIndex] == NULL             || arr[hashIndex]->key == -1)             size++;         arr[hashIndex] = temp;     }      // Function to delete a key value pair     V deleteNode(int key)     {         // Apply hash function         // to find index for given key         int hashIndex = hashCode(key);          // finding the node with given key         while (arr[hashIndex] != NULL) {             // if node found             if (arr[hashIndex]->key == key) {                 HashNode<K, V>* temp = arr[hashIndex];                  // Insert dummy node here for further use                 arr[hashIndex] = dummy;                  // Reduce size                 size--;                 return temp->value;             }             hashIndex++;             hashIndex %= capacity;         }          // If not found return null         return NULL;     }      // Function to search the value for a given key     V get(int key)     {         // Apply hash function to find index for given key         int hashIndex = hashCode(key);         int counter = 0;          // finding the node with given key         while (arr[hashIndex]                != NULL) { // int counter =0; // BUG!              if (counter++                 > capacity) // to avoid infinite loop                 return NULL;              // if node found return its value             if (arr[hashIndex]->key == key)                 return arr[hashIndex]->value;             hashIndex++;             hashIndex %= capacity;         }          // If not found return null         return NULL;     }      // Return current size     int sizeofMap() { return size; }      // Return true if size is 0     bool isEmpty() { return size == 0; }      // Function to display the stored key value pairs     void display()     {         for (int i = 0; i < capacity; i++) {             if (arr[i] != NULL && arr[i]->key != -1)                 cout << "key = " << arr[i]->key                      << "  value = " << arr[i]->value                      << endl;         }     } };  // Driver method to test map class int main() {     HashMap<int, int>* h = new HashMap<int, int>;     h->insertNode(1, 1);     h->insertNode(2, 2);     h->insertNode(2, 3);     h->display();     cout << h->sizeofMap() << endl;     cout << h->deleteNode(2) << endl;     cout << h->sizeofMap() << endl;     cout << h->isEmpty() << endl;     cout << h->get(2);      return 0; } 
Java
// Our own HashNode class class HashNode {     int key;     int value;      public HashNode(int key, int value)     {         this.key = key;         this.value = value;     } }  // Our own Hashmap class class HashMap {     // hash element array     int capacity;     int size;     HashNode[] arr;     // dummy node     HashNode dummy;      public HashMap()     {         this.capacity = 20;         this.size = 0;         this.arr = new HashNode[this.capacity];         // initialize with dummy node         this.dummy = new HashNode(-1, -1);     }      // This implements hash function to find index for a key     public int hashCode(int key)     {         return key % this.capacity;     }      // Function to add key value pair     public void insertNode(int key, int value)     {         HashNode temp = new HashNode(key, value);         // Apply hash function to find index for given key         int hashIndex = hashCode(key);         // find next free space         while (this.arr[hashIndex] != null                && this.arr[hashIndex].key != key                && this.arr[hashIndex].key != -1) {             hashIndex++;             hashIndex %= this.capacity;         }         // if new node to be inserted, increase the current         // size         if (this.arr[hashIndex] == null             || this.arr[hashIndex].key == -1) {             this.size++;         }         this.arr[hashIndex] = temp;     }      // Function to delete a key value pair     public int deleteNode(int key)     {         // Apply hash function to find index for given key         int hashIndex = hashCode(key);         // finding the node with given key         while (this.arr[hashIndex] != null) {             // if node found             if (this.arr[hashIndex].key == key) {                 HashNode temp = this.arr[hashIndex];                 // Insert dummy node here for further use                 this.arr[hashIndex] = this.dummy;                 // Reduce size                 this.size--;                 return temp.value;             }             hashIndex++;             hashIndex %= this.capacity;         }         // If not found return -1         return -1;     }      // Function to search the value for a given key     public int get(int key)     {         // Apply hash function to find index for given key         int hashIndex = hashCode(key);         int counter = 0;         // finding the node with given key         while (this.arr[hashIndex] != null) {             // If counter is greater than capacity to avoid             // infinite loop             if (counter > this.capacity) {                 return -1;             }             // if node found return its value             if (this.arr[hashIndex].key == key) {                 return this.arr[hashIndex].value;             }             hashIndex++;             hashIndex %= this.capacity;             counter++;         }         // If not found return 0         return 0;     }      // Return current size     public int sizeofMap() { return this.size; }      // Return true if size is 0     public boolean isEmpty() { return this.size == 0; }      // Function to display the stored key value pairs     public void display()     {         for (int i = 0; i < this.capacity; i++) {             if (this.arr[i] != null                 && this.arr[i].key != -1) {                 System.out.println(                     "key = " + this.arr[i].key                     + " value = " + this.arr[i].value);             }         }     } }  public class Main {     public static void main(String[] args)     {         HashMap h = new HashMap();         h.insertNode(1, 1);         h.insertNode(2, 2);         h.insertNode(2, 3);         h.display();         System.out.println(h.sizeofMap());         System.out.println(h.deleteNode(2));         System.out.println(h.sizeofMap());         System.out.println(h.isEmpty());         System.out.println(h.get(2));     } } 
Python
# Our own Hashnode class class HashNode:     def __init__(self, key, value):         self.key = key         self.value = value  # Our own Hashmap class   class HashMap:     # hash element array     def __init__(self):         self.capacity = 20         self.size = 0         self.arr = [None] * self.capacity         # dummy node         self.dummy = HashNode(-1, -1)      # This implements hash function to find index for a key     def hashCode(self, key):         return key % self.capacity      # Function to add key value pair     def insertNode(self, key, value):         temp = HashNode(key, value)         # Apply hash function to find index for given key         hashIndex = self.hashCode(key)         # find next free space         while self.arr[hashIndex] is not None and self.arr[hashIndex].key != key and self.arr[hashIndex].key != -1:             hashIndex += 1             hashIndex %= self.capacity         # if new node to be inserted, increase the current size         if self.arr[hashIndex] is None or self.arr[hashIndex].key == -1:             self.size += 1         self.arr[hashIndex] = temp      # Function to delete a key value pair     def deleteNode(self, key):         # Apply hash function to find index for given key         hashIndex = self.hashCode(key)         # finding the node with given key         while self.arr[hashIndex] is not None:             # if node found             if self.arr[hashIndex].key == key:                 temp = self.arr[hashIndex]                 # Insert dummy node here for further use                 self.arr[hashIndex] = self.dummy                 # Reduce size                 self.size -= 1                 return temp.value             hashIndex += 1             hashIndex %= self.capacity         # If not found return None         return None      # Function to search the value for a given key     def get(self, key):         # Apply hash function to find index for given key         hashIndex = self.hashCode(key)         counter = 0         # finding the node with given key         while self.arr[hashIndex] is not None:             # If counter is greater than capacity to avoid infinite loop             if counter > self.capacity:                 return None             # if node found return its value             if self.arr[hashIndex].key == key:                 return self.arr[hashIndex].value             hashIndex += 1             hashIndex %= self.capacity             counter += 1         # If not found return None         return 0      # Return current size     def sizeofMap(self):         return self.size      # Return true if size is 0     def isEmpty(self):         return self.size == 0      # Function to display the stored key value pairs     def display(self):         for i in range(self.capacity):             if self.arr[i] is not None and self.arr[i].key != -1:                 print("key = ", self.arr[i].key,                       " value = ", self.arr[i].value)   # Driver method to test map class if __name__ == "__main__":     h = HashMap()     h.insertNode(1, 1)     h.insertNode(2, 2)     h.insertNode(2, 3)     h.display()     print(h.sizeofMap())     print(h.deleteNode(2))     print(h.sizeofMap())     print(h.isEmpty())     print(h.get(2)) 
C#
using System;  class HashNode {     public int key;     public int value;     public HashNode next;      public HashNode(int key, int value)     {         this.key = key;         this.value = value;         next = null;     } }  class HashMap {     private HashNode[] table;     private int capacity;     private int size;      public HashMap(int capacity)     {         this.capacity = capacity;         table = new HashNode[capacity];         size = 0;     }      // hash function to find index for a given key     private int HashCode(int key) { return key % capacity; }      // function to add key value pair     public void InsertNode(int key, int value)     {         int hashIndex = HashCode(key);         HashNode newNode = new HashNode(key, value);          // if the key already exists, update the value         if (table[hashIndex] != null) {             HashNode current = table[hashIndex];              while (current != null) {                 if (current.key == key) {                     current.value = value;                     return;                 }                 current = current.next;             }         }          // if the key is new, add a new node to the table         newNode.next = table[hashIndex];         table[hashIndex] = newNode;         size++;     }      // function to delete a key value pair     public int ? DeleteNode(int key)     {         int hashIndex = HashCode(key);          if (table[hashIndex] != null) {             HashNode current = table[hashIndex];             HashNode previous = null;              while (current != null) {                 if (current.key == key) {                     if (previous == null) {                         table[hashIndex] = current.next;                     }                     else {                         previous.next = current.next;                     }                     size--;                     return current.value;                 }                 previous = current;                 current = current.next;             }         }          return null;     }      // function to get the value for a given key     public int ? Get(int key)     {         int hashIndex = HashCode(key);          if (table[hashIndex] != null) {             HashNode current = table[hashIndex];              while (current != null) {                 if (current.key == key) {                     return current.value;                 }                 current = current.next;             }         }          return 0;     }      // function to get the number of key value pairs in the     // hashmap     public int Size() { return size; }      // function to check if the hashmap is empty     public bool IsEmpty() { return size == 0; }      // function to display the key value pairs in the     // hashmap     public void Display()     {         for (int i = 0; i < capacity; i++) {             if (table[i] != null) {                 HashNode current = table[i];                  while (current != null) {                     Console.WriteLine("key = " + current.key                                       + " value = "                                       + current.value);                     current = current.next;                 }             }         }     } }  class Program {     static void Main(string[] args)     {         HashMap h = new HashMap(20);          h.InsertNode(1, 1);         h.InsertNode(2, 2);         h.InsertNode(2, 3);          h.Display();          Console.WriteLine(h.Size());         Console.WriteLine(h.DeleteNode(2));         Console.WriteLine(h.Size());         Console.WriteLine(h.IsEmpty());         Console.WriteLine(h.Get(2));     } } 
JavaScript
// template for generic type class HashNode {   constructor(key, value) {     this.key = key;     this.value = value;   } }  // template for generic type class HashMap {   constructor() {     this.capacity = 20;     this.size = 0;     this.arr = new Array(this.capacity);      // Initialise all elements of array as NULL     for (let i = 0; i < this.capacity; i++) {       this.arr[i] = null;     }      // dummy node with value and key -1     this.dummy = new HashNode(-1, -1);   }    // This implements hash function to find index for a key   hashCode(key) {     return key % this.capacity;   }    // Function to add key value pair   insertNode(key, value) {     const temp = new HashNode(key, value);      // Apply hash function to find index for given key     let hashIndex = this.hashCode(key);      // find next free space     while (       this.arr[hashIndex] !== null &&       this.arr[hashIndex].key !== key &&       this.arr[hashIndex].key !== -1     ) {       hashIndex++;       hashIndex %= this.capacity;     }      // if new node to be inserted     // increase the current size     if (       this.arr[hashIndex] === null ||       this.arr[hashIndex].key === -1     ) {       this.size++;     }     this.arr[hashIndex] = temp;   }    // Function to delete a key value pair   deleteNode(key) {     // Apply hash function to find index for given key     let hashIndex = this.hashCode(key);      // finding the node with given key     while (this.arr[hashIndex] !== null) {       // if node found       if (this.arr[hashIndex].key === key) {         const temp = this.arr[hashIndex];          // Insert dummy node here for further use         this.arr[hashIndex] = this.dummy;          // Reduce size         this.size--;         return temp.value;       }       hashIndex++;       hashIndex %= this.capacity;     }      // If not found return null     return null;   }    // Function to search the value for a given key   get(key) {     // Apply hash function to find index for given key     let hashIndex = this.hashCode(key);     let counter = 0;      // finding the node with given key     while (this.arr[hashIndex] !== null) {       if (counter++ > this.capacity) {         // to avoid infinite loop         return 0;       }        // if node found return its value       if (this.arr[hashIndex].key === key) {         return this.arr[hashIndex].value;       }       hashIndex++;       hashIndex %= this.capacity;     }      // If not found return null     return 0;   }    // Return current size   sizeofMap() {     return this.size;   }    // Return true if size is 0   isEmpty() {     return this.size === 0;   }    // Function to display the stored key value pairs   display() {     for (let i = 0; i < this.capacity; i++) {       if (this.arr[i] !== null && this.arr[i].key !== -1) {         console.log(`key = ${this.arr[i].key} value = ${this.arr[i].value}`);       }     }   } }  // Driver method to test map class const h = new HashMap(); h.insertNode(1,1); h.insertNode(2,2); h.insertNode(2,3); h.display(); console.log(h.sizeofMap()); console.log(h.deleteNode(2)); console.log(h.sizeofMap()); console.log(h.isEmpty()); console.log(h.get(2)); 

Output
key = 1  value = 1 key = 2  value = 3 2 3 1 0 0

Complexity analysis for Insertion:

  • Time Complexity:
    • Best Case: O(1)
    • Worst Case: O(N). This happens when all elements have collided and we need to insert the last element by checking free space one by one.
    • Average Case: O(1) for good hash function, O(N) for bad hash function
  • Auxiliary Space: O(1)

Complexity analysis for Deletion:

  • Time Complexity:
    • Best Case: O(1)
    • Worst Case: O(N)
    • Average Case: O(1) for good hash function; O(N) for bad hash function
  • Auxiliary Space: O(1) 

Complexity analysis for Searching:

  • Time Complexity:
    • Best Case: O(1)
    • Worst Case: O(N)
    • Average Case: O(1) for good hash function; O(N) for bad hash function
  • Auxiliary Space: O(1) for search operation



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Maximum possible difference of two subsets of an array

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  • Hash
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    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 Hashing

    Find Itinerary from a given list of tickets
    Given 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 Manager
    Given 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 K
    Given 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 subsequence
    Given 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 K
    Given 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 time
    Design 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 Numbers
    Given 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 Java
    All 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 Probing
    In 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 array
    Given 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 function
    We 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 numbers
    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 smalle
    14 min read
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