Data Structures and Algorithms

# Time Complexity of Hash Set Operations

## What is the time complexity of inserting, searching, and deleting elements in a hash set?

In a hash set, the time complexity of inserting, searching, and deleting elements is generally $O(1)$ on average. This means that these operations are performed in constant time, regardless of the size of the hashÂ set.

### Insertion

When inserting an element into a hash set, the hash function is applied to the element to determine its bucket index. If there are no collisions (i.e., no other elements in the same bucket), the insertion is done in constant time. However, if collisions occur and the bucket already contains elements, the insertion time may increase slightly due to the need to resolveÂ collisions.

Example of inserting an element into a hashÂ set:

#include <unordered_set>

int main() {
std::unordered_set<int> set;
set.insert(10);// O(1) on average
set.insert(20);// O(1) on average
set.insert(30);// O(1) on average
}

### Search

Searching for an element in a hash set is also an $O(1)$ operation on average. The hash function is applied to the element to determine its bucket index, and then the bucket is searched for the element. If there are no collisions, the search is done in constant time. If collisions exist, the search time may increase slightly, but it still remains constant onÂ average.

Example of searching for an element in a hashÂ set:

#include <unordered_set>

int main() {
std::unordered_set<int> set = {10, 20, 30};

// O(1) on average
bool found = set.find(20) != set.end();
}

### Deletion

Deleting an element from a hash set follows a similar process as searching. The hash function is applied to the element to locate its bucket, and then the element is removed from the bucket. The deletion operation is also $O(1)$ onÂ average.

Example of deleting an element from a hashÂ set:

#include <unordered_set>

int main() {
std::unordered_set<int> set = {10, 20, 30};
set.erase(20);// O(1) on average
}

It's important to note that the constant time complexity of hash set operations relies on a good hash function that minimizes collisions and ensures an even distribution of elements across the buckets. If the hash function is poorly designed or there are many collisions, the time complexity may degrade to O(n) in the worst case, where n is the number of elements in the hashÂ set.

This Question is from the Lesson:

### Data Structures and Algorithms

This lesson introduces the concept of data structures beyond arrays, and why we may want to use alternatives.

Answers to questions are automatically generated and may not have been reviewed.

This Question is from the Lesson:

### Data Structures and Algorithms

This lesson introduces the concept of data structures beyond arrays, and why we may want to use alternatives.

Part of the course:

## Professional C++

Comprehensive course covering advanced concepts, and how to use them on large-scale projects.

Free, unlimited access

### This course includes:

• 124 Lessons
• 550+ Code Samples
• 96% Positive Reviews
• Regularly Updated
• Help and FAQ
Free, Unlimited Access

### Professional C++

Comprehensive course covering advanced concepts, and how to use them on large-scale projects.