What is the difference between Hashing and Hash Tables?
Câu trả lời What is the difference between Hashing and Hash Tables?
Hashing and hash tables are closely related concepts in computer science, but they serve different purposes and have distinct characteristics.
Hashing
Hashing is a process that involves converting an input (or key) into a fixed-size string of characters, which is typically a hash code. This is done using a hash function. The primary purpose of hashing is to enable fast data retrieval. Here are some key points about hashing:
Hash Function: A hash function takes an input (or key) and returns a hash code, which is a fixed-size string of characters. The hash function is designed to distribute keys uniformly across the hash table to minimize collisions (when two keys hash to the same index) [1][2][3][4].
Deterministic: A good hash function is deterministic, meaning it will always produce the same hash code for the same input [4].
One-Way: Hash functions are typically one-way, meaning it is computationally infeasible to reverse the process and retrieve the original input from the hash code [4][14].
Applications: Hashing is used in various applications, including data retrieval, data integrity checks, and cryptography [6][14][18].
Hash Tables
A hash table (or hash map) is a data structure that uses hashing to map keys to values. It stores data in an array format, where each data value has a unique index generated by a hash function. Here are some key points about hash tables:
Structure: A hash table consists of an array of buckets or slots, each of which can store a key-value pair. The hash function determines the index at which a key-value pair should be stored [2][3][7][8].
Efficiency: Hash tables provide efficient insertion, deletion, and lookup operations, typically in constant time $$O(1)$$, assuming a good hash function and low collision rate [6][8][16].
Collision Resolution: Hash tables must handle collisions, which occur when multiple keys hash to the same index. Common collision resolution techniques include chaining (storing colliding elements in a linked list) and open addressing (finding another open slot in the array) [2][3][7][15].
