aloalgoHash Maps & Sets Summary
A quick reference for hash map and set techniques and problems to practice. Hash maps and hash sets are among the most commonly used data structures in coding interviews. They provide average O(1) time for insertions, deletions, and lookups, making them the go-to tool for reducing brute-force O(n²) solutions down to O(n).A hash map (also called a dictionary in Python or an object/Map in JavaScript) stores key-value pairs, while a hash set stores unique keys without associated values. Both rely on a hash function that converts keys into array indices, enabling near-instant access. Understanding when and how to use these data structures is one of the highest-leverage skills for coding interviews.Key Concepts
The table below outlines the most important hash-based patterns. These patterns recur across a wide range of interview problems, from simple lookups to complex string matching.| Concept | Description |
|---|---|
| Hash Set | O(1) membership checking, unique elements only |
| Hash Map | O(1) key-value lookup and storage |
| Frequency Count | Count occurrences of elements |
| Two Sum Pattern | Store complements to find pairs |
| Anagram Check | Compare character frequency maps |
Complexity
| Operation | Average | Worst |
|---|---|---|
| Insert | O(1) | O(n) |
| Lookup | O(1) | O(n) |
| Delete | O(1) | O(n) |
When to Use Hash Maps vs Hash Sets
- Use a hash set when you only care about whether an element exists: duplicate detection, membership testing, or tracking visited nodes in a graph.
- Use a hash map when you need to associate data with each key: counting frequencies, storing indices for the Two Sum pattern, or grouping anagrams by their sorted key.
- Use a default dictionary (Python's defaultdict or similar) when building frequency counters or adjacency lists to avoid checking for key existence before inserting.
Chapters
Practice Problems
Easy
Medium
Hard
Was this helpful?
Company
Practice
© 2026 aloalgo. All rights reserved.