Explain the concept of hash collision and its impact on hashing.

Hash collision occurs when two different inputs produce the same hash value. In other words, it is a situation where two or more keys are mapped to the same location in a hash table. This can happen due to the limited range of hash values compared to the potentially infinite number of possible inputs.

The impact of hash collisions on hashing depends on the specific collision resolution strategy employed. There are mainly two approaches to handle collisions: chaining and open addressing.

1. Chaining: In chaining, each bucket of the hash table contains a linked list of elements that hash to the same location. When a collision occurs, the new element is simply appended to the linked list. However, as the number of collisions increases, the length of the linked lists grows, leading to decreased performance. The time complexity of operations like insertion, deletion, and search in a hash table with chaining is directly proportional to the length of the linked lists.

2. Open Addressing: In open addressing, when a collision occurs, the algorithm probes for an alternative location within the hash table to store the element. This can be done using various techniques such as linear probing, quadratic probing, or double hashing. However, as the number of collisions increases, the number of probes required to find an empty slot also increases, resulting in decreased performance. Additionally, open addressing requires the hash table to have a load factor less than 1 to avoid excessive clustering, which further reduces the efficiency of the hash table.

Overall, hash collisions have a negative impact on hashing as they increase the time complexity of operations and reduce the efficiency of the hash table. The frequency of collisions depends on the quality of the hash function used, the size of the hash table, and the number of elements being hashed. Therefore, it is crucial to choose a good hash function and appropriately size the hash table to minimize the chances of collisions and optimize the performance of the hashing algorithm.