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Introduction to Hash Maps

Explore the fundamentals of hash maps, a key data structure in coding interviews. Learn how they store and manage key-value pairs efficiently through hashing and collision resolution techniques. This lesson helps you understand typical operations like insertion, search, and removal, and when to apply hash maps to solve common problems such as two sum and word count.

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 chainingCollision resolution strategy where each slot in the hash table contains a linked list of entries that hash to the same index. or open addressingCollision 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.. In the average case, inserting a key-value pair takes O(1)O(1) 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 O ...