Hashing and Maps
Hashing is the “secret weapon” of algorithmic interviews. It allows us to trade space for time, achieving O(1) lookups. This module covers everything from the math of hash functions to complex patterns like LRU Caches and Subarray Sums.
Module Contents
Master the magic of O(1) lookups. Understand Hash Functions, the Pigeonhole Principle, and Collision Resolution strategies.
Learn how hash tables handle the inevitable: when two keys want the same slot. Hardware depth on cache locality.
Hashing and Maps
[!NOTE] This module explores the core principles of Hashing and Maps, deriving solutions from first principles and hardware constraints to build world-class, production-ready expertise.
1. Practice
[!NOTE] Looking for hands-on algorithmic exercises? We have migrated all coding challenges for this module into the Problem Vault to give you a centralized, focused practice environment.
Module Chapters
Hash Functions & Collisions
Hash Functions & Collisions
Start LearningHashMap HashSet
Master the two most important data structures in modern programming: the Map and the Set.
Start Learning03. Chaining & Open Addressing
03. Chaining & Open Addressing
Start LearningCounting Problems
Learn the most common hashing pattern: The Frequency Map.
Start LearningSubarray Sum TwoSum
Master the 'Difference Lookup' pattern that solves Two Sum and Subarray Sum Equals K.
Start LearningCaching Applications
Design the most famous caching algorithm: The LRU Cache.
Start LearningReview & Cheat Sheet
Key Takeaways Hashing is the technique of mapping a large data set to a smaller range of indices (buckets) using a Hash Function. Collisions occur...
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