What is the load factor of a hash table and how does it affect performance?

The load factor of a hash table is the ratio of the number of elements stored in the hash table to the total number of slots or buckets available in the hash table. It is calculated by dividing the number of elements by the total number of slots.

Load factor = Number of elements / Total number of slots

The load factor affects the performance of a hash table in several ways:

1. Collision probability: As the load factor increases, the probability of collisions (i.e., two or more elements being mapped to the same slot) also increases. This is because the number of elements is increasing while the number of slots remains constant. Higher collision probability can lead to longer search times and reduced performance.

2. Efficiency of hash functions: Hash functions are used to map elements to specific slots in the hash table. A higher load factor can make it more challenging for hash functions to distribute elements evenly across the slots, resulting in more collisions. This can impact the efficiency of the hash function and overall performance.

3. Space utilization: A higher load factor means that more slots in the hash table are occupied by elements. This reduces the available space for new elements, potentially leading to more frequent resizing of the hash table. Resizing involves creating a new hash table with a larger number of slots and rehashing all the elements, which can be a costly operation in terms of time and memory.

4. Time complexity: The load factor affects the average time complexity of operations such as insertion, deletion, and search in a hash table. Generally, a lower load factor leads to better performance as it reduces the probability of collisions and improves the efficiency of hash functions.

In summary, the load factor of a hash table is a measure of how full the hash table is. It affects the performance by influencing collision probability, efficiency of hash functions, space utilization, and time complexity of operations. It is important to choose an appropriate load factor to balance space efficiency and performance in hash table implementations.