Oct 08, 2026 by Offer

What is a hash table (With Examples): Interview Answer Guide 2027

A hash table stores key-value pairs by running each key through a hash function that maps it to an array index, giving average O(1) insert, lookup, and delete. A strong hash table interview question answer explains the hash-to-index mechanism, how collisions are handled — chaining or open addressing — and why load factor triggers resizing.

What the Hash Table Interview Question Tests

Whether you can explain the mechanism: key → hash function → index → bucket.
Whether you know collision strategies — chaining vs. open addressing — and their trade-offs.
Whether you understand degradation: bad hash functions or high load factors push operations toward O(n).

How to Answer the Hash Table Interview Question

Trace concrete keys through a tiny table of size 5:

Example 1 — basic insert. hash("ada") = 12 → 12 mod 5 = slot 2. Store ("ada", …) at index 2. Lookup re-hashes and jumps to slot 2 directly.
Example 2 — collision. hash("bo") = 17 → 17 mod 5 = slot 2, already taken. With chaining, slot 2 becomes a list: [("ada", …), ("bo", …)].
Example 3 — resizing. Table holds 4 entries in 5 slots (load factor 0.8 > 0.7): allocate 10 slots and rehash every key into the bigger table.
Example 4 — real world. Python dicts, Java HashMaps, and database indexes are all hash tables — which is why dict lookup feels instant.

Sample close: "Tracing keys by hand once makes the whole structure obvious — and obvious is what you want under interview pressure."

Common Mistakes With the Hash Table Interview Question

Claiming hash tables are 'always O(1)'. Worst case is O(n) when everything collides — average vs. worst case matters.
Forgetting the hash function must be deterministic and well-distributed; a bad one clusters keys.
Not knowing what load factor is: entries divided by buckets, and tables resize when it gets too high.

Hash tables underpin dicts, sets, caches, and database indexes — interviewers assume you know them cold. The candidates who stand out explain collisions and resizing, not just 'it hashes the key.'

Keep Reading

FAQ

How does a hash table work?

A hash function converts each key into an array index; the value is stored at that index. Lookup re-hashes the key and jumps straight to the slot — average O(1).

What happens when two keys hash to the same index?

That is a collision. Chaining stores multiple entries per bucket (e.g., a linked list); open addressing probes for the next free slot.

What is load factor?

Entries divided by bucket count. As it rises, collisions increase, so tables resize — typically doubling — when it passes a threshold like 0.7.

Why can hash table lookup degrade to O(n)?

If many keys collide into one bucket (bad hash function or attack), lookup scans the whole chain. Good hashing and resizing keep this rare.

Preparing for Telstra's interview? Our 2027 Telstra Online Assessment | Video Interview Tutorials has practice questions and answers — $79 one-time, instant download.