Beginner Topic 10 of 52 Data Structures
Hash Tables
Structures mapping keys to buckets via a hash function.
How it works
A hash table maps keys to array indexes using a hash function, giving average O(1) insert, lookup and delete. A good function spreads keys evenly, and collisions where two keys land in the same slot are handled by chaining or open addressing. When the load factor grows too large, the table resizes and rehashes all entries to keep operations fast.
Where it is used
Dictionaries and sets in most languages, caches, symbol tables in compilers, database indexes, deduplication and counting frequencies use hash tables. They convert many linear searches into constant-time lookups.
Common pitfall
A poor hash function or adversarial keys can degrade operations to O(n). Mutable keys that change after insertion become unreachable. Iteration order may be arbitrary, resizing causes occasional latency spikes, and hashing floating-point or composite keys needs care.
Where it fits in the course
Hash Tables is topic 10 of 52 in Data Structures, rated Beginner. It follows Priority Queue. The next topic is Hash Collisions.
Practice and explore
- Open the interactive lesson, with a mini quiz.
- Take the Data Structures quiz.
- Explore the Hash Table visualizer: Hash function, buckets and chaining collisions.
How to study this topic
- Read the explanation above and restate the definition in your own words.
- Open the interactive lesson and answer its mini quiz.
- Read the common pitfall, then write a short example that avoids it.
- Check your understanding in the Data Structures quiz, and revisit the topic if you miss a question.
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Related topics
- Priority Queue (Data Structures)
- Hash Collisions (Data Structures)
- Deque (Data Structures)
- Chaining (Data Structures)
- Distributed Hash Tables (Distributed Systems & Cloud)
- Tables, Rows and Columns (Databases)
- Truth Tables (Computer Architecture & Logic)