Describe a hash table

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Hashing is a technique for identifying unique objects from a group of similar objects. Hash functions are large keys converted into small keys in hashing techniques. The values of hash functions are stored in data structures which are known hash table.

A hash table is a data structure that stores key-value pairs, where each key is mapped to a unique index in an array using a hash function. This mapping allows for efficient retrieval, insertion, and deletion of elements. Here’s a breakdown of its components and operations:

Components:

  1. Array: A contiguous block of memory used to store the key-value pairs.
  2. Hash Function: A function that takes a key as input and generates a hash code or index in the array where the key-value pair will be stored.
  3. Collision Resolution: Handling situations where multiple keys map to the same index in the array. Common collision resolution techniques include chaining (using linked lists at each array index to store multiple key-value pairs) or open addressing (finding alternative locations within the array).

Operations:

  1. Insertion: Given a key-value pair, compute the hash code for the key and insert the pair into the corresponding index in the array.
  2. Retrieval: Given a key, compute the hash code, go to the corresponding index in the array, and retrieve the associated value.
  3. Deletion: Given a key, compute the hash code, go to the corresponding index in the array, and delete the key-value pair if it exists.
  4. Search: Similar to retrieval, given a key, compute the hash code, go to the corresponding index in the array, and check if the key exists.

Key properties of a hash table include:

  • Fast access: Retrieval, insertion, and deletion operations typically have an average-case time complexity of O(1), making hash tables efficient for storing and accessing data.
  • Hash function quality: The efficiency and effectiveness of a hash table heavily depend on the quality of the hash function. A good hash function should distribute keys uniformly across the array to minimize collisions.
  • Load factor: The ratio of the number of stored elements to the size of the array. A high load factor can increase the likelihood of collisions, leading to performance degradation. Resizing the array and rehashing the elements can mitigate this issue.

In interviews, it’s crucial to understand the principles behind hash tables, including their underlying mechanisms, efficiency considerations, and collision resolution strategies.