What Is Chaining in Hashing in Data Structure?

//

Heather Bennett

What Is Chaining in Hashing in Data Structure?

Hashing is a fundamental concept in data structures that allows for efficient retrieval and storage of data. It involves mapping data to an index using a hash function.

However, collisions can occur when two different data elements generate the same hash value. One popular technique to handle collisions is called chaining.

Understanding Hashing

Before diving into chaining, let’s quickly recap hashing. In hashing, a hash function takes an input (data element) and returns a unique numerical value called the hash code. This hash code is used as an index to store or retrieve the data element from a data structure known as a hash table.

A good hash function should evenly distribute the hash codes across the hash table, minimizing collisions and ensuring efficient retrieval of elements.

Collisions in Hashing

Collisions occur when two or more elements generate the same hash code. Imagine a scenario where we have two different elements, “apple” and “banana,” both generating the same hash code of 5. In this case, storing both elements at index 5 would lead to a collision.

To handle collisions, various techniques exist in hashing, such as open addressing and chaining. Chaining is one of the most commonly used methods due to its simplicity and efficiency.

The Concept of Chaining

In chaining, each index in the hash table contains a linked list known as a chain. When a collision occurs, instead of overwriting the existing element at that index, we append the new element to its corresponding chain.

This way, multiple elements with different keys but identical hash codes can be stored together in separate nodes within the same index.

The Process

Let’s see how chaining works step by step:

  1. A hash function is applied to the key of the element to generate a hash code.
  2. The hash code is used as an index to locate the corresponding chain in the hash table.
  3. If the chain at that index is empty, the element is simply inserted as the first node in that chain.
  4. If the chain already contains elements, a new node with the element is appended to the end of that chain.

When searching for an element, we follow a similar process:

  1. The hash function generates a hash code for the key.
  2. We traverse the chain at that index and compare each element’s key until we find a match or reach the end of the chain (indicating no match).

Advantages of Chaining

Chaining offers several advantages:

  • Efficient Collision Handling: Chaining allows for multiple elements with identical hash codes to be stored together, minimizing collisions and ensuring efficient retrieval.
  • Dynamic Size: The size of a chained hash table can dynamically adjust based on the number of elements, without requiring frequent resizing operations like some other collision resolution techniques.

Disadvantages of Chaining

While chaining has its benefits, it also has some drawbacks:

  • Extra Memory Usage: Chaining requires additional memory to store pointers or references between elements within each chain.
  • Inefficient Cache Performance: Chained elements may not be stored contiguously in memory, leading to suboptimal cache performance.

Conclusion

Chaining is a popular collision resolution technique in hashing that allows for efficient handling of collisions. By using linked lists as chains within the hash table, elements with identical hash codes can be stored together. While it has its advantages and disadvantages, chaining remains an effective method for ensuring efficient retrieval and storage in hash tables.

Discord Server - Web Server - Private Server - DNS Server - Object-Oriented Programming - Scripting - Data Types - Data Structures

Privacy Policy