Introduction to Hash Maps
Explore the concept of hash maps as efficient data structures that store key-value pairs for fast data retrieval. Understand the core operations like insert, search, and remove, and learn about collision handling methods such as chaining and open addressing. This lesson helps you grasp how hash maps optimize lookups and how they can solve real-world problems like two sum and word count efficiently.
We'll cover the following...
About the pattern
A hash map, also known as a hash table, is a data structure that stores key-value pairs. It provides a way to efficiently map keys to values, allowing for quick retrieval of a value associated with a given key. Hash maps achieve this efficiency by using a hash function behind the scenes to compute an index (or hash code) for each key. This index determines where the corresponding value will be stored in an underlying array.
Below is an explanation of the staple methods of a hash map:
Insert(key, value): When a key-value pair is inserted into a hash map, the hash function computes an index based on the key. This index is used to determine the location in the hash map where the value will be stored. Because different keys may hash to the same index (collision), hash maps typically include a collision resolution strategy. Common methods include
chaining Collision resolution strategy where each slot in the hash table contains a linked list of entries that hash to the same index. open addressing Collision resolution strategy where collisions are resolved by probing through the hash table to find an empty slot, typically using methods like linear probing or quadratic probing. time, assuming the hash function distributes keys uniformly across the array. However, in the worst case (when all the keys hash to the same index), insertion can take up to ...