Implementing own Hash Table with Open Addressing Linear Probing
Prerequisite – Hashing Introduction, Implementing our Own Hash Table with Separate Chaining in Java
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; } |
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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