Answer:
A hashmap (or hash table) is a data structure that provides a way to store key-value pairs and allows for efficient retrieval of values based on their keys. The internal workings of a hashmap involve several key concepts, including hashing, buckets, and collision resolution. Here’s a breakdown of how a hashmap works internally:
1. Hash Function
- A hash function takes an input (the key) and produces an integer (the hash code). This integer is typically reduced to fit within the bounds of the array that will store the key-value pairs.
- The hash function should distribute keys uniformly across the available slots to minimize collisions.
2. Buckets
- The hashmap uses an array (often called the "buckets" array) to store the key-value pairs. Each index in this array can hold one or more entries.
- The index where a key-value pair is stored is determined by applying the hash function to the key and then taking the modulus with the size of the array (i.e.,
index = hash(key) % array_size).
3. Collision Handling
- A collision occurs when two different keys hash to the same index. There are several strategies to handle collisions:
- Chaining: Each bucket contains a linked list (or another data structure) of all entries that hash to the same index. When a collision occurs, the new key-value pair is added to the list at that index.
- Open Addressing: When a collision occurs, the algorithm searches for the next available slot in the array (using techniques like linear probing, quadratic probing, or double hashing).
4. Load Factor and Resizing
- The load factor is a measure of how full the hashmap is, typically defined as the number of entries divided by the number of buckets. A common threshold for resizing is a load factor of 0.7.
- When the load factor exceeds this threshold, the hashmap is resized (usually doubled in size), and all existing entries are rehashed and redistributed into the new array.
5. Operations
- Insertion: To insert a key-value pair, the hash function is applied to the key to find the appropriate index. If there’s a collision, the collision resolution strategy is applied.
- Search: To retrieve a value, the hash function is applied to the key to find the index. If there are multiple entries (due to collisions), the linked list or probing sequence is searched.
- Deletion: To delete a key-value pair, the hash function is used to find the index, and the entry is removed from the bucket or marked as deleted in the case of open addressing.
6. Performance
- The average time complexity for insertion, deletion, and search operations in a well-implemented hashmap is O(1). However, in the worst case (e.g., many collisions), the time complexity can degrade to O(n).
Summary
In summary, a hashmap is a powerful data structure that uses a combination of hashing, an array of buckets, and collision resolution techniques to provide efficient key-value storage and retrieval. Its performance can be significantly affected by the choice of hash function, the method of collision resolution, and the load factor.