Which operation is typically slower in a hash table when the load factor is high?

In a hash table, when the load factor is high, the search operation tends to become slower due to an increased likelihood of collisions. A high load factor indicates that the number of elements stored in the hash table is close to the size of the underlying array used to store those elements. When more elements are concentrated in a limited space, the chances of two different elements being hashed to the same index increase, which creates a collision.

When a collision occurs, the hash table must handle it through methods such as chaining (where elements are stored in a linked list or another structure at each index) or open addressing (where the table is probed for the next available slot). In either case, the search process may involve traversing additional elements at the index where the collision occurred, thus increasing the time complexity for the search operation.

As a result, the average case for search operations can degrade from O(1) in an ideal situation to O(n) in scenarios with many collisions, directly impacting performance and making the search operation slower when the load factor is high. This outcome is a key characteristic of hash tables that users must account for when designing systems that utilize them.