What Are the Different Types of Hashing Techniques in Data Structure?

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Angela Bailey

In this tutorial, we will explore the various types of hashing techniques used in data structures. Hashing is a fundamental concept that plays a crucial role in efficient data storage and retrieval. It involves mapping data to a fixed-size array called a hash table using a hash function.

What is Hashing?

Hashing is a technique used to map large amounts of data to a fixed-size array, which allows for efficient storage and retrieval. It involves applying a hash function to the input data, which generates a unique numerical value called a hash code. This hash code is used as an index to store the data in the hash table.

Types of Hashing Techniques

There are several different types of hashing techniques commonly used in data structures. Each technique has its own advantages and disadvantages, making them suitable for specific use cases. Let’s explore some of these techniques:

1. Division Method

The division method is one of the simplest hashing techniques. It involves dividing the key by the size of the hash table and using the remainder as the index. For example, if we have a hash table with size 10 and our key is 27, we would calculate 27 % 10 = 7 and store the data at index 7.

  • Advantages: Simple implementation, evenly distributes keys.
  • Disadvantages: Poor performance when there are many collisions.

2. Multiplication Method

The multiplication method uses multiplication and fractional parts of the key to calculate the index in the hash table. It involves multiplying the key by a constant factor between 0 and 1, extracting its fractional part, and then multiplying it by the size of the hash table. The resulting value is used as the index.

  • Advantages: Distributes keys more evenly than the division method.
  • Disadvantages: Requires careful selection of the constant factor.

3. Folding Method

The folding method involves dividing the key into equal-sized parts, which are then summed up to calculate the hash code. This hash code is used as the index in the hash table. For example, if our key is 123456789, we could divide it into 12, 34, 56, and 78 and sum them up (12 + 34 + 56 + 78 = 180) to get our hash code.

  • Advantages: Can handle large keys efficiently.
  • Disadvantages: Requires careful selection of the folding technique.

4. Mid-Square Method

The mid-square method involves squaring the key and extracting a portion from the middle as the hash code. For example, if our key is 25, squaring it gives us 625, and extracting a portion from the middle (2) gives us our hash code.

  • Advantages: Simple implementation.

5. Universal Hashing

Universal hashing is a technique that uses a randomly generated hash function from a predefined set of functions. This helps to minimize collisions and provides better performance even for worst-case scenarios.

  • Advantages: Provides excellent average-case performance.
  • Disadvantages: More complex implementation.

In Conclusion

Hashing is a powerful technique used in data structures to efficiently store and retrieve large amounts of data. The different types of hashing techniques each have their own strengths and weaknesses, making them suitable for specific use cases.

By understanding these techniques, you can choose the most appropriate method for your applications and optimize the performance of your data storage and retrieval operations.

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