Hashing is a technique used for storing , searching and removing elements in almost constant time. Hashing is done with help of a hash function that generates index for a given input, then this index can be used to search the elements, store an element, or remove that element from that index.
A hash function is a function that is used to map the data elements to their position in the data structure used. For example if we use an array to store the integer elements then the hash function will generate position for each element so that searching, storing and removing operation on the array can be done in constant time that is independent of the number of elements in the array. For better look at the example below.
now we face a problem if for 2 numbers same position is generated example consider elements 1 and 14
1 % 13 = 1
14 % 13 = 1
so when we get 1 we store it at the first position, but when we get 14 we see that the position 1 is already taken, this is a case of collision.
Inorder to resolve collision we employ various collision resolving methods here we use linear probing to resolve collision.
In Linear Probing we look for the next immediate empty position and store the element, so as in the above example as the position 1 is already filled we see if position 2 is empty if yes then we store 14 at 2nd position else we check 3rd position. if in any case we reach end of the table we start again from the top and check for an empty position.
To know more about hash functions and how to select hash function click Here.
To know more about Linear Probing and its performance as compared to other collision resolving methods click Here.
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A hash function is a function that is used to map the data elements to their position in the data structure used. For example if we use an array to store the integer elements then the hash function will generate position for each element so that searching, storing and removing operation on the array can be done in constant time that is independent of the number of elements in the array. For better look at the example below.
now we face a problem if for 2 numbers same position is generated example consider elements 1 and 14
1 % 13 = 1
14 % 13 = 1
so when we get 1 we store it at the first position, but when we get 14 we see that the position 1 is already taken, this is a case of collision.
Inorder to resolve collision we employ various collision resolving methods here we use linear probing to resolve collision.
In Linear Probing we look for the next immediate empty position and store the element, so as in the above example as the position 1 is already filled we see if position 2 is empty if yes then we store 14 at 2nd position else we check 3rd position. if in any case we reach end of the table we start again from the top and check for an empty position.
To know more about hash functions and how to select hash function click Here.
To know more about Linear Probing and its performance as compared to other collision resolving methods click Here.
C++ Program
Sample input and output to check the program
You might also be interested in
Hashing using Quadratic Probing
Find Trailing number of zeros in factorial of a number.
Check if a number is a Fibonacci number or not
Find Factorial of a number
Find Square root using Babylonian method
Bubble sort Algorithm
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