HashMap in Data Structure

What is a HashMap?

A hashmap is a data structure that connects keys with values. It uses a hash function to generate an index into an array of buckets, from which the needed value can be extracted. Simply said, it's similar to a real-world dictionary in that you know the 'word' (key) and can instantly retrieve its meaning (value).

Need of HashMap in Data Structure

• HashMaps are essential in data structures because they allow for efficient key-value pair storing and retrieval.
• They offer quick access to data via hashing, making them excellent for applications that require frequent data access.

Applications of HashMap

• Database Indexing
• Caching
• Routers & DNS Resolution
• Language Interpretation
• Counting Frequency

Advantages of HashMap

• Fast data access: Hashmaps are extremely efficient because they can access data in O(1) average time.
• Flexible keys: Hashmaps, unlike arrays, can utilize any data type for keys, providing greater versatility.

Disadvantages of HashMap

• Inefficient space usage: HashMaps frequently allocate more space than is required to handle future entries (and avoid collisions), which might waste memory.
• Collision handling: While collision solutions exist, they can be complicated to develop and have a detrimental influence on performance when there are a lot of them.

Different Methods of HashMap

Following are some key methods of HashMap:

• put(key, value): put(key, value) adds a key-value pair to the HashMap.
• get(key): get(key) returns the value associated with the supplied key.
• containsKey(key): Determines whether the HashMap contains a particular key.
• remove(key): Deletes the key-value pair associated with the given key.
• size(): size() returns the number of key-value pairs in the HashMap.
• isEmpty(): Determines whether the HashMap is empty.
• clear(): clean() removes all key-value pairs from the HashMap.