A hash table, also known as a hash map, is a data structure that stores key-value pairs. It provides efficient insertion, deletion, and retrieval of elements based on their keys. Hash tables are widely used in computer science due to their ability to provide constant-time average-case performance for these operations.
The core idea behind a hash table is to use a hash function to map keys to indices in an array, called buckets or slots. Each bucket can store one or more key-value pairs. When an element is inserted into the hash table, its key is hashed using the hash function, and the resulting hash value determines the index where the element will be stored.
Hash tables offer fast access to elements because the time complexity for insertion, deletion, and retrieval operations is typically O(1) on average. However, in the worst-case scenario, when many keys hash to the same index, the time complexity can degrade to O(n), where n is the number of elements stored in the hash table.
To handle collisions, which occur when multiple keys hash to the same index, hash tables employ collision resolution techniques. Common collision resolution methods include:
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Chaining: Each bucket in the hash table is implemented as a linked list, and collisions are resolved by appending new elements to the linked list at the corresponding index.
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Open Addressing: In open addressing, collisions are resolved by probing for an alternative empty slot in the hash table. Linear probing, quadratic probing, and double hashing are examples of open addressing techniques.
Hash tables are used in various applications, including:
- Implementing associative arrays, dictionaries, and maps in programming languages.
- Database indexing and caching mechanisms.
- Symbol tables in compilers and interpreters.
- Network routing and packet forwarding algorithms.
Overall, hash tables are versatile data structures that offer efficient storage and retrieval of key-value pairs, making them an essential tool in many computing tasks.
