How to Handle Hash Table Collisions? Understand Hash Resolution Methods in Data Structures Simply

Hash tables map keys to array slots via hash functions, and hash collisions occur when different keys map to the same slot. The core solution is to find new positions for colliding elements, with the main methods as follows: 1. **Chaining (Separate Chaining)**: Each slot stores a linked list, where colliding elements are appended to the list. For example, keys 1, 6, and 11 hashing to the same slot form a linked list [1, 6, 11]. **Advantages**: Simple implementation, suitable for dynamic data. **Disadvantages**: Extra space for linked lists; worst-case O(n) lookup. 2. **Open Addressing**: When collisions occur, empty slots are probed. Includes linear probing (i+1, wrapping around) and quadratic probing (i+1², etc.). For example, key 6 hashing to slot 1 (collision) probes slot 2; key 11 probes slot 3. **Advantages**: High space utilization. **Disadvantages**: Linear probing causes primary clustering; quadratic probing requires a larger array. Other methods: Double hashing (multiple hash functions) and common overflow area (primary table + overflow table), suitable for low-collision scenarios. Selection depends on the use case: Chaining (e.g., Java HashMap) suits dynamic, large datasets; Open addressing is better for fixed-size arrays with few collisions.