What Is Mean by Rehashing in Data Structure?

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Scott Campbell

What Is Mean by Rehashing in Data Structure?

When working with data structures, rehashing is a technique used to handle collisions that occur during the process of inserting elements into a hash table. It involves the creation of a new hash function or the modification of the existing one to rearrange elements in the table.

Understanding Hash Tables and Collisions

In order to grasp the concept of rehashing, it is important to first understand hash tables and collisions. A hash table is a data structure that stores key-value pairs, allowing for efficient retrieval and insertion operations. Each key is mapped to a specific index using a hash function.

Collisions occur when two or more keys are assigned to the same index in the hash table. This can happen due to various reasons such as different keys producing the same hash value or limited space in the table.

The Need for Rehashing

Collisions can negatively impact the performance of a hash table, leading to increased search and insertion times. Rehashing helps alleviate this issue by redistributing elements in such a way that collisions are minimized.

There are different approaches to resolving collisions, such as chaining (using linked lists or other data structures to store multiple elements at each index) or open addressing (finding alternate locations within the table for collided elements). Rehashing falls under open addressing techniques.

The Process of Rehashing

The process of rehashing involves creating a new hash function or modifying the existing one and then copying all elements from the original hash table into a larger-sized new table based on this new hashing scheme.

Steps involved in rehashing:

  • Create a new empty hash table with an increased size.
  • Generate a new hash function or modify the existing one.
  • Iterate through each element in the original hash table.
  • Calculate the new index for each element using the new hash function.
  • Insert the element into its new index in the new hash table.

It is crucial to choose a larger size for the new hash table to ensure that there is enough space to accommodate all elements without causing collisions. This also helps maintain an optimal load factor, which is the ratio of filled slots to total slots in the hash table.

Benefits and Trade-offs

Rehashing offers several benefits:

  • Improved Performance: By reducing collisions, rehashing improves search and insertion times, making operations more efficient.
  • Better Space Utilization: Rehashing allows for better utilization of space as elements are evenly distributed across the hash table.
  • Dynamically Resizable: Hash tables can be dynamically resized during rehashing, accommodating an increasing number of elements as needed.

However, rehashing also has some trade-offs:

  • Increased Memory Usage: Rehashing requires creating a larger-sized hash table, which can lead to increased memory usage.
  • Potential Performance Overhead: The process of rehashing itself incurs additional computational overhead. However, this is typically a one-time cost when resizing the hash table.

In Conclusion

Rehashing plays a vital role in improving the efficiency and performance of hash tables. By redistributing elements and minimizing collisions, rehashing ensures that search and insertion operations can be performed in a time-efficient manner. Understanding the concept of rehashing is essential for anyone working with data structures and looking to optimize their algorithms.

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