**Hashing**is the technique used for performing almost constant time search in case of insertion, deletion and find operation. Taking a very simple example of it, an array with its index as key is the example of hash table.

So each index (key) can be used for accessing the value in a constant search time. This mapping key must be simple to compute and must helping in identifying the associated value. Function which helps us in generating such kind of key-value mapping is known as

**Hash Function.**

**Hash Table a.k.a Hash Map**is a data structure which uses hash function to generate key corresponding to the associated value.

lets look at some sample hash function for strings

**Folding Method:-**

int h(String x, int D)

{

int i, sum;

for (sum=0, i=0; i<x.length(); i++)

sum+= (int)x.charAt(i);

return (sum%D);

}

**Cyclic Shift :-**

static long hashCode(String key, int D)

{

int h=0;

for (int i=0, i<key.length(); i++)

{

h = (h << 4) | ( h >> 27);

h += (int) key.charAt(i);

}

return h%D;

}

good link for hash function on string : click here

Coming to very important part of hashing , which is

**collision resolution**. Since its always not possible to design perfect hash function with minimal overhead which would generate unique key. To address this problem following are the two main collision resolving techniques :-
1) Open Hashing also known as separate chaining

2) Closed Hashing also known as open addressing

Lets understand the difference between them

**1) Open Hashing**:- In this strategy collision is resolved by keeping the conflicting element in a list. That is to keep all element in a list which generate same hash.

Open Hashing |

From above figure its clear that how collision get resolved by keeping a linked list.

**2) Closed Hashing**:- In this strategy collision is resolved by placing the conflicting element near to the slot generated by the hash function. Associated with closed hashing is a rehash strategy:

“If we try to place x in bucket h(x) and find it occupied, find alternative location h1(x), h2(x), etc. Try each in order, if none empty table is full,”

Lets take an example to understand it

HASH_TABLE_SIZE = 8

Input data :- a,b,c,d Hash for them H(a) = 0, H(b) = 3, H(c) = 7 and H(d) = 3

Now as 'c' and 'd' has same hash, where to insert 'd' then ?

Finding position using linear hashing :

h1(d) = (h(d)+1)%8 = 4%8 = 4

Adding 1 to hash function of h(d) we get new position 4, and slot 4 is currently non occupied. So entering d at position 4. In this way Closed hashing works.

*Disadvantage*of closed hashing is that it consumes more space as compared to open hashing

also it has less flexibility in accommodating for duplicate hash element.

Major

*advantage*of closed hashing is that it reduces the overhead of introducing new data structure and reduces cost of new memory allocation per new element insertion.
## 11 comments:

good job (y) THANKS :)

its good with precise informtion

good

thanks dear

you give very simple language to understand

once again thnx.......

This is the most difficult and confusing portion which I am trying from several days to learn. A big thanks to you for simplifying all the things in such a simple and easy way.

e signatures

Good

in example for closed hashing above 'c' is taken instead of 'd'.

Excellent info ............

what is data structure and its types

Good eexplanatin....bt can u give more explanation on other methods of hashing such as mid-square, multiplication and division....

very helpful information thanks

Very useful information but it will be even better if you provide questions to workout like Geeks for geeks.Try to update..

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