Commonly Asked Data Structure Interview Questions on Hashing

Last Updated : 28 Feb, 2025

Hashing is a technique to map data to fixed-size values using a hash function, often used for quick lookups, insertions, and deletions in applications like databases and caches. The core concept behind hashing is to map large data to smaller fixed-size values, typically integers, through a hash function. Various data structures like hash tables, hash maps, and hash sets make use of hashing to perform fast operations. This article covers commonly asked interview questions on hashing and the data structures used for it.

Table of Content

Theoretical Questions for Interviews on Hashing

1. What is Hashing?

Hashing is a technique used to convert data into fixed-size values called hash codes, which are used as keys to index into hash tables or hash maps for efficient data retrieval.

2. What is a Hash Function?

A hash function is an algorithm that converts an input into a fixed-size hash code, which determines the index for storing or retrieving data in a hash table.

3. What are the properties of a good hash function?

Some properties of good hash functions are:

Uniform distribution: A good hash function spreads values evenly across the hash table to avoid clustering.
Efficiency: It should compute hash values quickly with minimal computational overhead.
Deterministic: The same input should always produce the same hash value.
Minimizing collisions: It should reduce the chances of different inputs mapping to the same hash value.

4. What is a perfect hash function?

A perfect hash function is a hash function that maps distinct keys to distinct indices without any collisions. It guarantees an O(1) lookup time in a hash table, but finding a perfect hash function may be computationally expensive.

5. What is a Hash Table and Hash Map?

A hash table is a data structure that stores key-value pairs. It uses a hash function to compute an index for each key, allowing efficient data retrieval. while A hash map is similar to a hash table, used in higher-level languages. It stores key-value pairs and uses a hash function for indexing.

6. What is the Difference Between Hash Table and Hash Map?

Feature	Hash Table	Hash Map
Thread Safety	Typically thread-safe (in some languages like Java)	Not thread-safe by default
Null Keys/Values	Does not allow `null` as a key or value (in most languages)	Allows `null` as a key or value (in some languages like Java)
Resizing	Requires manual resizing in some implementations	Resizes dynamically as the number of elements increases
Collision Handling	Typically uses separate chaining or open addressing	Uses the same collision handling methods as hash tables
Performance	Slightly slower due to thread-safety mechanisms in some cases	Tends to be faster in non-concurrent environments
Use Case	Used in situations where thread safety is required	Used when thread safety is not a concern (most modern applications)
Example in Java	`Hashtable`	`HashMap`

7. What are Collisions in Hashing?

A Hashing collision occurs when two different keys produce the same hash code. This is resolved using techniques like open addressing or separate chaining.

8. What is Open Addressing and separate chaining ?

Open addressing and separate chaining are collision resolution methods where in Open Addressing, the algorithm searches for the next available slot in the hash table upon a collision. while, Separate chaining stores multiple elements at the same index by using linked lists or other data structures to resolve collisions.

9. What is Hash Code in Hashing?

A hash code is the output of a hash function, used as an index to store or retrieve data in a hash table.

10. What is the time complexity of search, insert, and delete operations in a Hash Table?

The time complexity for these operations is O(1) on average, but it can degrade to O(n) in the worst case with many collisions.

11. What is the time complexity of pushing and retrieving an element from a hashmap?

The time complexity for pushing and retrieving the elements from a Hashmap O(1) using put and get methods respectively.

12. Explain the concept of Load Factor in Hash Tables.

The load factor in Hash Table is the ratio of elements to slots in a hash table. A high load factor indicates more collisions, leading to slower performance. Hash tables resize when this threshold is exceeded.

13. What is the purpose of rehashing in a hash table?

Rehashing is the process of resizing a hash table when the load factor exceeds a certain threshold. It involves creating a new, larger table and re-inserting the elements from the old table using their hash codes. Rehashing ensures that the table maintains efficient performance as it grows.

14. How would you implement a hash table with separate chaining?

Create a hash table where each index holds a linked list to store elements that hash to the same index. Implement basic operations like insert(), get(), and remove().

15. What is cuckoo hashing?

Cuckoo hashing is a collision resolution technique that uses two hash functions to store keys in a hash table.

16. What are bloom filters, and how do they relate to hashing?

A bloom filter is a probabilistic data structure used to test whether an element is a member of a set. It uses multiple hash functions to map elements to a bit array, allowing for fast membership testing, but with a small probability of false positives.

Commonly Asked Data Structure Interview Questions on Hashing

Theoretical Questions for Interviews on Hashing

Top Coding Interview Questions on Hashing

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