Lecture 359:- Introduction to Hashing

Hashing is a technique used in computer science to efficiently store, retrieve, and search for data in a data structure called a hash table. The primary goal of hashing is to quickly find a specific element in a large collection of data.

In simple terms, hashing works by taking an input (or key) and applying a hash function to convert it into a fixed-size value, typically an integer, known as the hash code or hash value. This hash value is then used as an index to store or retrieve the corresponding data in the hash table.

The key features of a good hash function are:

1. Deterministic: The same key should always produce the same hash value.
2. Fast to compute: The hash function should be efficient to compute to ensure quick access to data.
3. Uniform distribution: The hash function should distribute the keys uniformly across the hash table to minimize collisions (two different keys producing the same hash value).

Hashing is widely used in various applications, including:

1. Data storage: Hash tables are used in databases and programming languages for efficient data storage and retrieval operations.
2. Caching: Hashing is used in caching mechanisms to quickly identify whether certain data is already available or needs to be recomputed.
3. Cryptography: Hash functions are used in cryptography for creating digital signatures and message authentication codes.
4. Hash-based searching algorithms: Hashing is used in various search algorithms like hash maps and hash sets.

It's important to note that while hashing provides fast data retrieval, collisions (different keys producing the same hash value) can occur. Collision resolution techniques are used to handle such situations and ensure that data is correctly stored and retrieved from the hash table. Common collision resolution methods include chaining (using linked lists to handle collisions) and open addressing (finding alternative positions for colliding elements).