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What is Hash Tables?
Hash tables are fundamental data structures in many programming languages, used to implement collections such as sets and maps. They store data by linking keys to values, providing efficient performance for operations like lookup, insertion, and deletion.
Unlike arrays and linked lists—which can become inefficient for these operations—hash tables offer a robust solution. For example, while unsorted arrays have linear time complexity for lookups, and binary search in sorted arrays is fast but inefficient for insertions, hash tables maintain speed and efficiency regardless of data size.
How They Work
A hash table uses an array to store data, allowing for speedy data access when the key is known. It implements a hash function to generate a unique index for each data item, optimizing both search and insertion operations.
Hashing
Hashing converts key values to indexes within an array. A common method uses the modulo operator to ensure values fit within the array's size, aiding in efficient data management.
Basic Operations
The major operations of a hash table include:
- Search: Locate an element in a hash table.
- Insert: Add an element to a hash table.
- Delete: Remove an entry from a hash table.
Hash Collision
Collisions occur when multiple keys hash to the same index. Solutions include:
- Chaining: Store elements with the same index in a linked list.
- Open Addressing: Use methods like linear probing, quadratic probing, or double hashing to resolve collisions without chaining.
Open Addressing Techniques
- Linear Probing: Check the next slot until an empty one is found, increasing i linearly.
- Quadratic Probing: Increase the separation between slots using a quadratic function.
- Double Hashing: Compute a secondary hash to determine the slot for insertion in case of a collision.
Table Resizing
Optimal performance in hash tables relies on proportionate sizing related to the number of records. When resizing, records move to a larger table, ensuring consistent performance.
