What Are the Types of Hashing in Data Structure?
Hashing is a fundamental concept in data structure that allows for efficient data retrieval. It is a technique used to map data to a fixed-size array, called a hash table, based on a predefined function called a hash function. The hash function takes an input and produces a unique output, which is used as the index for storing and retrieving data.
Types of Hashing
There are several types of hashing techniques commonly used in data structures. Let’s explore some of the most widely used ones:
1. Division Method
The division method is one of the simplest hashing techniques. It uses the remainder obtained after dividing the key by the size of the hash table as the index for storing data. In this method, the hash function is simply:
hash(key) = key % table_size
This method works well when the keys are uniformly distributed, but it can lead to clustering if there are many collisions (i.e., different keys mapping to the same index).
2. Multiplication Method
The multiplication method improves upon the division method by incorporating both multiplication and division operations. It multiplies the key with a constant value between 0 and 1 and extracts the fractional part of the result. The size of the hash table is then multiplied by this fractional part to obtain the final index:
hash(key) = floor(table_size * (key * constant % 1))
This method helps distribute keys more evenly across the hash table, reducing clustering and improving performance.
3. Folding Method
The folding method involves dividing or folding large keys into smaller parts and then performing some operation (e.g., addition, XOR) on these parts to obtain the final index. This technique is particularly useful when dealing with keys that are longer than the hash table size.
For example, if the key is 123456789 and the hash table size is 1000, we can split the key into two parts (12 and 3456789). Then, we can add these two parts together and take the remainder after dividing by the table size:
hash(key) = (12 + 3456789) % table_size
4. Mid-Square Method
The mid-square method is another hashing technique commonly used for integer keys. It involves squaring the key, extracting a portion from the middle of the squared value, and using it as the index. This method works best when the key distribution is random.
For example, if the key is 42 and we want to map it to a hash table of size 10, we can square it to get 1764. Then, we extract the middle two digits (76) and take their remainder after dividing by 10:
hash(key) = (key^2 / 100) % table_size
Hashing is an essential concept in data structures that allows for efficient data storage and retrieval. The choice of hashing technique depends on factors such as key distribution, collision handling requirements, and performance considerations. In this article, we explored some of the most commonly used hashing methods: division method, multiplication method, folding method, and mid-square method.
By understanding these different types of hashing techniques, you can choose an appropriate one based on your specific requirements when implementing hash tables in your programs.