What Is Extendible Hashing in Data Structure?

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Scott Campbell

Extendible Hashing in Data Structure

Data structures play a vital role in organizing and managing data efficiently. One such data structure is Extendible Hashing, which offers a scalable solution for handling large amounts of data while maintaining quick access times. In this article, we will explore what Extendible Hashing is and how it works.

Understanding Hashing

Before diving into Extendible Hashing, let’s briefly understand the concept of hashing. Hashing is a technique that maps data to a fixed-size array called a hash table using a hash function. This function takes an input value and produces a unique index or address where the data will be stored.

  • Hash Function: A hash function generates the index or address for storing data in the hash table.
  • Hash Table: It is an array that stores the data using the indexes generated by the hash function.

What Is Extendible Hashing?

Extendible Hashing is an efficient hashing technique that dynamically adjusts its structure to accommodate more entries without causing collisions or excessive memory consumption. It achieves this by utilizing a directory structure and bucket organization.

The Directory Structure

The directory structure in Extendible Hashing consists of fixed-size buckets (blocks) arranged in a binary tree-like structure. Each bucket has an associated local depth, which indicates how many bits of the hashed key are used to determine its placement within the directory.

The directory acts as an index to locate buckets where specific keys are stored. Initially, the directory contains only one entry pointing to a single bucket.

The Bucket Organization

Each bucket in Extendible Hashing can store multiple key-value pairs. When inserting a new key-value pair into the hash table, the hash function is applied to the key to find the appropriate bucket in the directory.

If the bucket has enough space, the new entry can be inserted directly. However, if the bucket is full, it needs to be split into two buckets. The local depth of the new buckets is increased by one, indicating that an additional bit of the hashed key is used for placement.

Handling Collisions

Extendible Hashing effectively handles collisions by dynamically adjusting the directory structure and redistributing entries among buckets. When a collision occurs during an insertion, the affected bucket is split into two new buckets with increased local depth.

The directory is then updated to point both entries to their respective new buckets. This process ensures that each key has a unique location in the hash table and minimizes collisions.

Benefits of Extendible Hashing

Extendible Hashing offers several advantages over other hashing techniques:

  • Scalability: Extendible Hashing can handle a large number of entries without degrading performance.
  • Minimal Memory Usage: It optimizes memory usage by dynamically splitting buckets only when necessary.
  • Efficient Lookup: Due to its hierarchical structure, Extendible Hashing provides quick access times for retrieving data.

Conclusion

In conclusion, Extendible Hashing is a powerful data structure that provides efficient and scalable storage for large amounts of data. By dynamically adjusting its structure and redistributing entries, it ensures optimal memory usage and quick access times. Understanding Extendible Hashing can greatly benefit anyone working with large datasets and seeking efficient data organization techniques.

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