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Double Hashing

Last Updated : 29 Mar, 2024
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Double hashing is a collision resolution technique used in hash tables. It works by using two hash functions to compute two different hash values for a given key. The first hash function is used to compute the initial hash value, and the second hash function is used to compute the step size for the probing sequence.

Double hashing has the ability to have a low collision rate, as it uses two hash functions to compute the hash value and the step size. This means that the probability of a collision occurring is lower than in other collision resolution techniques such as linear probing or quadratic probing.

However, double hashing has a few drawbacks. First, it requires the use of two hash functions, which can increase the computational complexity of the insertion and search operations. Second, it requires a good choice of hash functions to achieve good performance. If the hash functions are not well-designed, the collision rate may still be high.

Advantages of Double hashing

  • The advantage of Double hashing is that it is one of the best forms of probing, producing a uniform distribution of records throughout a hash table.
  • This technique does not yield any clusters.
  • It is one of the effective methods for resolving collisions.

Double hashing can be done using : 
(hash1(key) + i * hash2(key)) % TABLE_SIZE 
Here hash1() and hash2() are hash functions and TABLE_SIZE 
is size of hash table. 
(We repeat by increasing i when collision occurs)

Method 1: First hash function is typically hash1(key) = key % TABLE_SIZE
A popular second hash function is hash2(key) = PRIME - (key % PRIME) where PRIME is a prime smaller than the TABLE_SIZE.
A good second Hash function is: 

  • It must never evaluate to zero
  • Just make sure that all cells can be probed 

Below is the implementation of the above approach:

CPP
/* ** Handling of collision via open addressing ** Method for Probing: Double Hashing */  #include <iostream> #include <vector> #include <bitset> using namespace std; #define MAX_SIZE 10000001ll  class doubleHash {      int TABLE_SIZE, keysPresent, PRIME;     vector<int> hashTable;     bitset<MAX_SIZE> isPrime;      /* Function to set sieve of Eratosthenes. */     void __setSieve(){         isPrime[0] = isPrime[1] = 1;         for(long long i = 2; i*i <= MAX_SIZE; i++)             if(isPrime[i] == 0)                 for(long long j = i*i; j <= MAX_SIZE; j += i)                     isPrime[j] = 1;      }      int inline hash1(int value){         return value%TABLE_SIZE;     }          int inline hash2(int value){                return PRIME - (value%PRIME);     }      bool inline isFull(){         return (TABLE_SIZE == keysPresent);     }      public:       doubleHash(int n){         __setSieve();         TABLE_SIZE = n;          /* Find the largest prime number smaller than hash table's size. */         PRIME = TABLE_SIZE - 1;         while(isPrime[PRIME] == 1)             PRIME--;          keysPresent = 0;          /* Fill the hash table with -1 (empty entries). */         for(int i = 0; i < TABLE_SIZE; i++)             hashTable.push_back(-1);      }      void __printPrime(long long n){         for(long long i = 0; i <= n; i++)             if(isPrime[i] == 0)                 cout<<i<<", ";         cout<<endl;     }      /* Function to insert value in hash table */     void insert(int value){          if(value == -1 || value == -2){             cout<<("ERROR : -1 and -2 can't be inserted in the table\n");           }          if(isFull()){             cout<<("ERROR : Hash Table Full\n");             return;         }                  int probe = hash1(value), offset = hash2(value); // in linear probing offset = 1;                  while(hashTable[probe] != -1){             if(-2 == hashTable[probe])                                   break;                                  // insert at deleted element's location             probe = (probe+offset) % TABLE_SIZE;         }          hashTable[probe] = value;         keysPresent += 1;     }      void erase(int value){         /* Return if element is not present */         if(!search(value))             return;                       int probe = hash1(value), offset = hash2(value);          while(hashTable[probe] != -1)             if(hashTable[probe] == value){                 hashTable[probe] = -2;          // mark element as deleted (rather than unvisited(-1)).                 keysPresent--;                 return;             }             else                 probe = (probe + offset) % TABLE_SIZE;       }      bool search(int value){         int probe = hash1(value), offset = hash2(value), initialPos = probe;         bool firstItr = true;          while(1){             if(hashTable[probe] == -1)                   // Stop search if -1 is encountered.                 break;             else if(hashTable[probe] == value)           // Stop search after finding the element.                 return true;             else if(probe == initialPos && !firstItr)    // Stop search if one complete traversal of hash table is completed.                 return false;             else                 probe = ((probe + offset) % TABLE_SIZE);  // if none of the above cases occur then update the index and check at it.              firstItr = false;         }         return false;     }      /* Function to display the hash table. */     void print(){         for(int i = 0; i < TABLE_SIZE; i++)             cout<<hashTable[i]<<", ";         cout<<"\n";     }  };  int main(){     doubleHash myHash(13); // creates an empty hash table of size 13      /* Inserts random element in the hash table */          int insertions[] = {115, 12, 87, 66, 123},          n1 = sizeof(insertions)/sizeof(insertions[0]);          for(int i = 0; i < n1; i++)         myHash.insert(insertions[i]);          cout<< "Status of hash table after initial insertions : "; myHash.print();           /*      ** Searches for random element in the hash table,     ** and prints them if found.     */          int queries[] = {1, 12, 2, 3, 69, 88, 115},         n2 = sizeof(queries)/sizeof(queries[0]);          cout<<"\n"<<"Search operation after insertion : \n";      for(int i = 0; i < n2; i++)         if(myHash.search(queries[i]))             cout<<queries[i]<<" present\n";           /* Deletes random element from the hash table. */          int deletions[] = {123, 87, 66},         n3 = sizeof(deletions)/sizeof(deletions[0]);          for(int i = 0; i < n3; i++)         myHash.erase(deletions[i]);      cout<< "Status of hash table after deleting elements : "; myHash.print();          return 0; } 
Java
import java.util.BitSet; import java.util.Vector;  class DoubleHash {      private int TABLE_SIZE, keysPresent, PRIME;     private Vector<Integer> hashTable;     private BitSet isPrime;     private static final long MAX_SIZE = 10000001L;      /* Function to set sieve of Eratosthenes. */     private void setSieve() {         isPrime.set(0, true);         isPrime.set(1, true);         for (long i = 2; i * i <= MAX_SIZE; i++)             if (!isPrime.get((int) i))                 for (long j = i * i; j <= MAX_SIZE; j += i)                     isPrime.set((int) j);     }      private int hash1(int value) {         return value % TABLE_SIZE;     }      private int hash2(int value) {         return PRIME - (value % PRIME);     }      private boolean isFull() {         return (TABLE_SIZE == keysPresent);     }      public DoubleHash(int n) {         isPrime = new BitSet((int) MAX_SIZE);         setSieve();         TABLE_SIZE = n;          /* Find the largest prime number smaller than hash table's size. */         PRIME = TABLE_SIZE - 1;         while (isPrime.get(PRIME))             PRIME--;          keysPresent = 0;          /* Fill the hash table with -1 (empty entries). */         hashTable = new Vector<>();         for (int i = 0; i < TABLE_SIZE; i++)             hashTable.add(-1);     }      private void printPrime(long n) {         for (long i = 0; i <= n; i++)             if (!isPrime.get((int) i))                 System.out.print(i + ", ");         System.out.println();     }      /* Function to insert value in hash table */     public void insert(int value) {          if (value == -1 || value == -2) {             System.out.println("ERROR : -1 and -2 can't be inserted in the table");         }          if (isFull()) {             System.out.println("ERROR : Hash Table Full");             return;         }          int probe = hash1(value), offset = hash2(value); // in linear probing offset = 1;          while (hashTable.get(probe) != -1) {             if (-2 == hashTable.get(probe))                 break; // insert at deleted element's location             probe = (probe + offset) % TABLE_SIZE;         }          hashTable.set(probe, value);         keysPresent += 1;     }      public void erase(int value) {         /* Return if element is not present */         if (!search(value))             return;          int probe = hash1(value), offset = hash2(value);          while (hashTable.get(probe) != -1)             if (hashTable.get(probe) == value) {                 hashTable.set(probe, -2); // mark element as deleted (rather than unvisited(-1)).                 keysPresent--;                 return;             } else                 probe = (probe + offset) % TABLE_SIZE;      }      public boolean search(int value) {         int probe = hash1(value), offset = hash2(value), initialPos = probe;         boolean firstItr = true;          while (true) {             if (hashTable.get(probe) == -1) // Stop search if -1 is encountered.                 break;             else if (hashTable.get(probe) == value) // Stop search after finding the element.                 return true;             else if (probe == initialPos && !firstItr) // Stop search if one complete traversal of hash table is                                                         // completed.                 return false;             else                 probe = ((probe + offset) % TABLE_SIZE); // if none of the above cases occur then update the index and                                                             // check at it.              firstItr = false;         }         return false;     }      /* Function to display the hash table. */     public void print() {         for (int i = 0; i < TABLE_SIZE; i++)             System.out.print(hashTable.get(i) + ", ");         System.out.println();     } }  public class Main {     public static void main(String[] args) {         DoubleHash myHash = new DoubleHash(13); // creates an empty hash table of size 13          /* Inserts random element in the hash table */          int[] insertions = { 115, 12, 87, 66, 123 };         int n1 = insertions.length;          for (int i = 0; i < n1; i++)             myHash.insert(insertions[i]);          System.out.print("Status of hash table after initial insertions : ");         myHash.print();          /*          ** Searches for random element in the hash table,          ** and prints them if found.          */          int[] queries = { 1, 12, 2, 3, 69, 88, 115 };         int n2 = queries.length;          System.out.println("\n" + "Search operation after insertion : ");          for (int i = 0; i < n2; i++)             if (myHash.search(queries[i]))                 System.out.println(queries[i] + " present");          /* Deletes random element from the hash table. */          int[] deletions = { 123, 87, 66 };         int n3 = deletions.length;          for (int i = 0; i < n3; i++)             myHash.erase(deletions[i]);          System.out.print("Status of hash table after deleting elements : ");         myHash.print();     } } 
Python3
from typing import List import math  MAX_SIZE = 10000001  class DoubleHash:     def __init__(self, n: int):         self.TABLE_SIZE = n         self.PRIME = self.__get_largest_prime(n - 1)         self.keysPresent = 0         self.hashTable = [-1] * n      def __get_largest_prime(self, limit: int) -> int:         is_prime = [True] * (limit + 1)         is_prime[0], is_prime[1] = False, False         for i in range(2, int(math.sqrt(limit)) + 1):             if is_prime[i]:                 for j in range(i * i, limit + 1, i):                     is_prime[j] = False         for i in range(limit, -1, -1):             if is_prime[i]:                 return i      def __hash1(self, value: int) -> int:         return value % self.TABLE_SIZE      def __hash2(self, value: int) -> int:         return self.PRIME - (value % self.PRIME)      def is_full(self) -> bool:         return self.TABLE_SIZE == self.keysPresent      def insert(self, value: int) -> None:         if value == -1 or value == -2:             print("ERROR : -1 and -2 can't be inserted in the table")             return         if self.is_full():             print("ERROR : Hash Table Full")             return         probe, offset = self.__hash1(value), self.__hash2(value)         while self.hashTable[probe] != -1:             if -2 == self.hashTable[probe]:                 break             probe = (probe + offset) % self.TABLE_SIZE         self.hashTable[probe] = value         self.keysPresent += 1      def erase(self, value: int) -> None:         if not self.search(value):             return         probe, offset = self.__hash1(value), self.__hash2(value)         while self.hashTable[probe] != -1:             if self.hashTable[probe] == value:                 self.hashTable[probe] = -2                 self.keysPresent -= 1                 return             else:                 probe = (probe + offset) % self.TABLE_SIZE      def search(self, value: int) -> bool:         probe, offset, initialPos, firstItr = self.__hash1(value), self.__hash2(value), self.__hash1(value), True         while True:             if self.hashTable[probe] == -1:                 break             elif self.hashTable[probe] == value:                 return True             elif probe == initialPos and not firstItr:                 return False             else:                 probe = (probe + offset) % self.TABLE_SIZE             firstItr = False         return False      def print(self) -> None:         print(*self.hashTable,sep=', ')  if __name__ == '__main__':     myHash = DoubleHash(13)      # Inserts random element in the hash table     insertions = [115, 12, 87, 66, 123]     for insertion in insertions:         myHash.insert(insertion)     print("Status of hash table after initial insertions : ", end="")     myHash.print()      # Searches for random element in the hash table, and prints them if found.     queries = [1, 12, 2, 3, 69, 88, 115]     n2 = len(queries)     print("\nSearch operation after insertion : ")          for i in range(n2):         if myHash.search(queries[i]):             print(queries[i], "present")                  # Deletes random element from the hash table.     deletions = [123, 87, 66]     n3 = len(deletions)          for i in range(n3):         myHash.erase(deletions[i])              print("Status of hash table after deleting elements : ",end='')     myHash.print() 
C#
using System; using System.Collections.Generic; using System.Linq;  class doubleHash {      int TABLE_SIZE, keysPresent, PRIME, MAX_SIZE = 10000001;     List<int> hashTable;     bool[] isPrime;      /* Function to set sieve of Eratosthenes. */     void __setSieve()     {         isPrime[0] = isPrime[1] = true;         for (long i = 2; i * i <= MAX_SIZE; i++) {             if (isPrime[i] == false) {                 for (long j = i * i; j <= MAX_SIZE;                      j += i) {                     isPrime[j] = true;                 }             }         }     }      int hash1(int value) { return value % TABLE_SIZE; }      int hash2(int value) { return PRIME - (value % PRIME); }      bool isFull() { return (TABLE_SIZE == keysPresent); }      public doubleHash(int n)     {         isPrime = new bool[MAX_SIZE + 1];         __setSieve();         TABLE_SIZE = n;          /* Find the largest prime number smaller than hash          * table's size. */         PRIME = TABLE_SIZE - 1;         while (isPrime[PRIME] == true)             PRIME--;          keysPresent = 0;         hashTable = new List<int>();         /* Fill the hash table with -1 (empty entries). */         for (int i = 0; i < TABLE_SIZE; i++)             hashTable.Add(-1);     }      public void __printPrime(long n)     {         for (long i = 0; i <= n; i++)             if (isPrime[i] == false)                 Console.Write(i + ", ");         Console.WriteLine();     }      /* Function to insert value in hash table */     public void insert(int value)     {          if (value == -1 || value == -2) {             Console.Write(                 "ERROR : -1 and -2 can't be inserted in the table\n");         }          if (isFull()) {             Console.Write("ERROR : Hash Table Full\n");             return;         }          int probe = hash1(value),             offset             = hash2(value); // in linear probing offset = 1;          while (hashTable[probe] != -1) {             if (-2 == hashTable[probe])                 break; // insert at deleted element's                        // location             probe = (probe + offset) % TABLE_SIZE;         }          hashTable[probe] = value;         keysPresent += 1;     }      public void erase(int value)     {         /* Return if element is not present */         if (!search(value))             return;          int probe = hash1(value), offset = hash2(value);          while (hashTable[probe] != -1)             if (hashTable[probe] == value) {                 hashTable[probe]                     = -2; // mark element as deleted (rather                           // than unvisited(-1)).                 keysPresent--;                 return;             }             else                 probe = (probe + offset) % TABLE_SIZE;     }      public bool search(int value)     {         int probe = hash1(value), offset = hash2(value),             initialPos = probe;         bool firstItr = true;          while (true) {             if (hashTable[probe]                 == -1) // Stop search if -1 is encountered.                 break;             else if (hashTable[probe]                      == value) // Stop search after finding                                // the element.                 return true;             else if (probe == initialPos                      && !firstItr) // Stop search if one                                    // complete traversal of                                    // hash table is                                    // completed.                 return false;             else                 probe = ((probe + offset)                          % TABLE_SIZE); // if none of the                                         // above cases occur                                         // then update the                                         // index and check                                         // at it.              firstItr = false;         }         return false;     }      /* Function to display the hash table. */     public void print()     {         for (int i = 0; i < TABLE_SIZE; i++)             Console.Write(hashTable[i] + ", ");         Console.Write("\n");     } }  public class Program {     static void Main()     {         doubleHash myHash = new doubleHash(             13); // creates an empty hash table of size 13          /* Inserts random element in the hash table */          int[] insertions = { 115, 12, 87, 66, 123 };         int n1 = insertions.Length;          for (int i = 0; i < n1; i++)             myHash.insert(insertions[i]);          Console.Write(             "Status of hash table after initial insertions : ");         myHash.print();          /*         ** Searches for random element in the hash table,         ** and prints them if found.         */          int[] queries = { 1, 12, 2, 3, 69, 88, 115 };         int n2 = queries.Length;          Console.Write(             "\n"             + "Search operation after insertion : \n");          for (int i = 0; i < n2; i++)             if (myHash.search(queries[i]))                 Console.Write(queries[i] + " present\n");          /* Deletes random element from the hash table. */          int[] deletions = { 123, 87, 66 };         int n3 = deletions.Length;          for (int i = 0; i < n3; i++)             myHash.erase(deletions[i]);          Console.Write(             "Status of hash table after deleting elements : ");         myHash.print();     } } 
JavaScript
// JS code const MAX_SIZE = 10000001;  // Set sieve of Eratosthenes let isPrime = new Array(MAX_SIZE).fill(0); isPrime[0] = isPrime[1] = 1; for (let i = 2; i * i <= MAX_SIZE; i++) {   if (isPrime[i] === 0) {     for (let j = i * i; j <= MAX_SIZE; j += i) {       isPrime[j] = 1;     }   } }  // Create DoubleHash Class class DoubleHash {   constructor(n) {     this.TABLE_SIZE = n;     this.PRIME = this.TABLE_SIZE - 1;     while (isPrime[this.PRIME] === 1) {       this.PRIME--;     }     this.keysPresent = 0;     this.hashTable = new Array(this.TABLE_SIZE).fill(-1);   }   isFull(){   return this.TABLE_SIZE==this.keysPresent;   }    hash1(value) {     return value % this.TABLE_SIZE; }   hash2(value) {     return this.PRIME - (value % this.PRIME); }    // Function to print prime numbers   __printPrime(n) {     for (let i = 0; i <= n; i++) {       if (isPrime[i] === 0) {         console.log(i + ", ");       }     }     console.log("\n");   }    // Function to insert value in hash table   insert(value) {     if (value === -1 || value === -2) {       console.log("ERROR : -1 and -2 can't be inserted in the table\n");     }     if (this.isFull()) {       console.log("ERROR : Hash Table Full\n");       return;     }     let probe = this.hash1(value),       offset = this.hash2(value); // in linear probing offset = 1;      while (this.hashTable[probe] !== -1) {       if (-2 === this.hashTable[probe]) break; // insert at deleted element's location       probe = (probe + offset) % this.TABLE_SIZE;     }      this.hashTable[probe] = value;     this.keysPresent += 1;   }    erase(value) {     // Return if element is not present     if (!this.search(value)) return;      let probe = this.hash1(value),       offset = this.hash2(value);      while (this.hashTable[probe] !== -1) {       if (this.hashTable[probe] === value) {         this.hashTable[probe] = -2; // mark element as deleted (rather than unvisited(-1)).         this.keysPresent--;         return;       } else {         probe = (probe + offset) % this.TABLE_SIZE;       }     }   }    search(value) {     let probe = this.hash1(value),       offset = this.hash2(value),       initialPos = probe;     let firstItr = true;      while (1) {       if (this.hashTable[probe] === -1) break; // Stop search if -1 is encountered.       else if (this.hashTable[probe] === value) return true; // Stop search after finding the element.       else if (probe === initialPos && !firstItr)         return false; // Stop search if one complete traversal of hash table is completed.       else probe = (probe + offset) % this.TABLE_SIZE; // if none of the above cases occur then update the index and check at it.       firstItr = false;     }     return false;   }    // Function to display the hash table.   print() {     for (let i = 0; i < this.TABLE_SIZE; i++) console.log(this.hashTable[i] + ", ");     console.log("\n");   } }  // Main function function main() {   let myHash = new DoubleHash(13); // creates an empty hash table of size 13    // Inserts random element in the hash table   let insertions = [115, 12, 87, 66, 123],     n1 = insertions.length;    for (let i = 0; i < n1; i++) myHash.insert(insertions[i]);    console.log("Status of hash table after initial insertions : ");   myHash.print();    // Searches for random element in the hash table, and prints them if found.   let queries = [1, 12, 2, 3, 69, 88, 115],     n2 = queries.length;    console.log("\n" + "Search operation after insertion : \n");    for (let i = 0; i < n2; i++)     if (myHash.search(queries[i])) console.log(queries[i] + " present\n");    // Deletes random element from the hash table.   let deletions = [123, 87, 66],     n3 = deletions.length;    for (let i = 0; i < n3; i++) myHash.erase(deletions[i]);    console.log("Status of hash table after deleting elements : ");   myHash.print();    return 0; }  main();  // This code is contributed by ishankhandelwals. 

Output
Status of hash table after initial insertions : -1, 66, -1, -1, -1, -1, 123, -1, -1, 87, -1, 115, 12,     Search operation after insertion :   12 present  115 present  Status of hash table after deleting elements : -1, -2, -1, -1, -1, -1, -2, -1, -1, -2, -1, 115, 12,     

Time Complexity:

  • Insertion: O(n)
  • Search: O(n)
  • Deletion: O(n)

Auxiliary Space: O(size of the hash table).


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    Given an array, the task is to find the most frequent element in it. If there are multiple elements that appear a maximum number of times, return the maximum element.Examples: Input : arr[] = [1, 3, 2, 1, 4, 1]Output : 1Explanation: 1 appears three times in array which is maximum frequency.Input : a
    10 min read
    Only Repeating From 1 To n-1
    Given an array arr[] of size n filled with numbers from 1 to n-1 in random order. The array has only one repetitive element. The task is to find the repetitive element.Examples:Input: arr[] = [1, 3, 2, 3, 4]Output: 3Explanation: The number 3 is the only repeating element.Input: arr[] = [1, 5, 1, 2,
    15+ min read
    Check for Disjoint Arrays or Sets
    Given two arrays a and b, check if they are disjoint, i.e., there is no element common between both the arrays.Examples: Input: a[] = {12, 34, 11, 9, 3}, b[] = {2, 1, 3, 5} Output: FalseExplanation: 3 is common in both the arrays.Input: a[] = {12, 34, 11, 9, 3}, b[] = {7, 2, 1, 5} Output: True Expla
    11 min read
    Non-overlapping sum of two sets
    Given two arrays A[] and B[] of size n. It is given that both array individually contains distinct elements. We need to find the sum of all elements that are not common.Examples: Input : A[] = {1, 5, 3, 8} B[] = {5, 4, 6, 7}Output : 291 + 3 + 4 + 6 + 7 + 8 = 29Input : A[] = {1, 5, 3, 8} B[] = {5, 1,
    9 min read
    Check if two arrays are equal or not
    Given two arrays, a and b of equal length. The task is to determine if the given arrays are equal or not. Two arrays are considered equal if:Both arrays contain the same set of elements.The arrangements (or permutations) of elements may be different.If there are repeated elements, the counts of each
    6 min read
    Find missing elements of a range
    Given an array, arr[0..n-1] of distinct elements and a range [low, high], find all numbers that are in a range, but not the array. The missing elements should be printed in sorted order.Examples: Input: arr[] = {10, 12, 11, 15}, low = 10, high = 15Output: 13, 14Input: arr[] = {1, 14, 11, 51, 15}, lo
    15+ min read
    Minimum Subsets with Distinct Elements
    You are given an array of n-element. You have to make subsets from the array such that no subset contain duplicate elements. Find out minimum number of subset possible.Examples : Input : arr[] = {1, 2, 3, 4}Output :1Explanation : A single subset can contains all values and all values are distinct.In
    9 min read
    Remove minimum elements such that no common elements exist in two arrays
    Given two arrays arr1[] and arr2[] consisting of n and m elements respectively. The task is to find the minimum number of elements to remove from each array such that intersection of both arrays becomes empty and both arrays become mutually exclusive.Examples: Input: arr[] = { 1, 2, 3, 4}, arr2[] =
    8 min read
    2 Sum - Count pairs with given sum
    Given an array arr[] of n integers and a target value, the task is to find the number of pairs of integers in the array whose sum is equal to target.Examples: Input: arr[] = {1, 5, 7, -1, 5}, target = 6Output: 3Explanation: Pairs with sum 6 are (1, 5), (7, -1) & (1, 5). Input: arr[] = {1, 1, 1,
    9 min read
    Count quadruples from four sorted arrays whose sum is equal to a given value x
    Given 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 = k
    Given 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 characters
    Given 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 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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