Linked Hash Map In Java

Last updated on Jan 23, 2023

I. Introduction

Overview of the concept of a hash map

A hash map, also known as a dictionary or associative array, is a data structure that uses a hash function to map keys to values. The keys are unique and are used to identify the associated value. The basic idea behind a hash map is to use the keys as indices in an array, so that the value can be quickly looked up using the key.

The hash function takes in a key as input and produces an index, also known as a hash code, as output. This index is then used to access the corresponding value in the array. The process of mapping the key to the index is known as "hashing."

One of the main advantages of using a hash map is its constant time complexity for basic operations such as insertion, deletion, and lookup, making it efficient for large datasets. Hash maps can also be useful for tasks such as caching, data compression, and implementing more complex data structures such as sets and graphs.

However, hash maps can also have collisions, which occur when two keys are mapped to the same index in the array. This can be handled by using separate chaining or open addressing.

Explanation of the specific implementation of a hash map in the data structure known as a linked hash map

A linked hash map is a specific implementation of a hash map that combines the features of both a hash table and a linked list. Like a regular hash map, it uses a hash function to map keys to values and stores the key-value pairs in an array. But unlike a regular hash map, it also maintains a doubly-linked list that runs through all the elements in the order they were inserted.

In a linked hash map, each element in the array is a linked list node that contains the key, value, and links to the next and previous nodes. When an element is added to the linked hash map, it is placed at the end of the linked list, preserving the insertion order. This allows for predictable iteration and makes it possible to implement access-order iteration, which iterates through the elements in the order they were last accessed.

When a key is looked up in the linked hash map, the hash function is used to find the index in the array where the key-value pair is stored. If there is a collision, the linked list at that index is searched for the correct key-value pair.

Additionally, A linked hash map also allows for the removal of the least recently accessed elements, which is useful in some use cases, like implementing a cache.

Linked Hash Map is a good choice when the iteration order is required or when the access-order iteration is needed.

II. How a Linked Hash Map Works

Description of the underlying data structure used in a linked hash map (i.e. a combination of a hash table and a linked list)

A linked hash map is a powerful data structure that combines the features of both a hash table and a linked list. In this article, we will take a closer look at the underlying data structure used in a linked hash map and how it works.

First, let's start with the hash table aspect of a linked hash map. Like a regular hash map, it uses a hash function to map keys to values and stores the key-value pairs in an array. This array is called the "bucket array" and each index in the array is called a "bucket." The hash function takes in a key as input and produces an index, also known as a hash code, as output. This index is then used to access the corresponding value in the array. The process of mapping the key to the index is known as "hashing."

However, unlike a regular hash map, a linked hash map also maintains a doubly-linked list that runs through all the elements in the order they were inserted. When an element is added to the linked hash map, it is placed at the end of the linked list, preserving the insertion order.

Each element in the bucket array is a linked list node that contains the key, value, and links to the next and previous nodes. When a key is looked up in the linked hash map, the hash function is used to find the index in the array where the key-value pair is stored. If there is a collision, the linked list at that index is searched for the correct key-value pair.

This combination of a hash table and a linked list in a linked hash map allows for improved performance over a regular hash map when dealing with large datasets. It also provides additional functionality such as access-order iteration and removal of least-recently accessed elements.

In summary, a linked hash map is a data structure that combines the fast look-up capabilities of a hash table with the predictable iteration order of a linked list. It uses a hash function to map keys to values, and stores the key-value pairs in an array, and also maintains a doubly-linked list that runs through all the elements in the order they were inserted. This combination makes the linked hash map a powerful tool in data management and manipulation.

Explanation of how elements are inserted, accessed, and removed from a linked hash map

A linked hash map is a powerful data structure that combines the features of both a hash table and a linked list. One of the main advantages of using a linked hash map is its constant time complexity for basic operations such as insertion, deletion, and lookup, making it efficient for large datasets. In this article, we will take a closer look at how elements are inserted, accessed, and removed from a linked hash map.

Insertion: When an element is inserted into a linked hash map, the first step is to compute the hash code of the key using a hash function. The hash code is then used to determine the index of the bucket array where the element should be stored. If the bucket is empty, a new node is created and added to the end of the linked list. If there is already an element in the bucket, the new element is added to the end of the linked list and the next and previous pointers of the new node and the last node are updated.

Access: When an element is accessed in a linked hash map, the first step is to compute the hash code of the key using a hash function. The hash code is then used to determine the index of the bucket array where the element is stored. If the bucket is empty, the element is not present in the linked hash map. If there is an element in the bucket, the linked list at that index is searched for the key-value pair. Once the key-value pair is found, the value is returned.

Removal: When an element is removed from a linked hash map, the first step is to compute the hash code of the key using a hash function. The hash code is then used to determine the index of the bucket array where the element is stored. If the bucket is empty, the element is not present in the linked hash map. If there is an element in the bucket, the linked list at that index is searched for the key-value pair. Once the key-value pair is found, the node is removed from the linked list and the next and previous pointers of the surrounding nodes are updated.

It's worth noting that linked hash maps also allow for the removal of the least recently accessed elements, which is useful in some use cases, like implementing a cache.

In summary, a linked hash map is a powerful data structure that allows for efficient insertion, access, and removal of elements. It uses a hash function to map keys to values, and stores the key-value pairs in an array and also maintains a doubly-linked list that runs through all the elements in the order they were inserted. This combination makes the linked hash map a powerful tool in data management and manipulation.

III. Advantages of Using a Linked Hash Map

Improved performance over a regular hash map when dealing with large datasets

A linked hash map is a specific implementation of a hash map that combines the features of both a hash table and a linked list. One of the main advantages of using a linked hash map over a regular hash map is its improved performance when dealing with large datasets.

In a regular hash map, when the number of elements in the map increases, the number of collisions also increases, which can lead to a decrease in performance. A collision occurs when two keys are mapped to the same index in the array. This can be handled by using separate chaining or open addressing, but it still adds complexity and overhead to the hash map.

On the other hand, a linked hash map utilizes a doubly-linked list that runs through all the elements in the order they were inserted. This linked list allows for predictable iteration and makes it possible to implement access-order iteration, which iterates through the elements in the order they were last accessed.

Additionally, linked hash map can also remove the least recently accessed element, which is useful in some use cases, like implementing a cache. This can help with reducing the number of collisions, and thus improving the performance, especially when dealing with large datasets.

Therefore, a linked hash map has improved performance over a regular hash map when dealing with large datasets due to the combination of the hash table and linked list data structures, which allows for predictable iteration, access-order iteration, and removal of least-recently accessed elements.

Preservation of insertion order, allowing for predictable iteration

A linked hash map is a specific implementation of a hash map that combines the features of both a hash table and a linked list. One of the main advantages of using a linked hash map is its preservation of insertion order, allowing for predictable iteration.

In a regular hash map, the order of the elements is not preserved, which means that iterating through the elements will not be in the order they were inserted. This can make it difficult to predict the order in which the elements will be accessed and can lead to unexpected behavior in certain situations.

On the other hand, a linked hash map utilizes a doubly-linked list that runs through all the elements in the order they were inserted. When an element is added to the linked hash map, it is placed at the end of the linked list, preserving the insertion order. This allows for predictable iteration through the elements and makes it easy to understand the order in which the elements will be accessed.

This predictable iteration can be useful in situations where the order of the elements is important, such as in certain algorithms or data processing tasks. Additionally, this predictable iteration also allows for access-order iteration, which iterates through the elements in the order they were last accessed. This can be useful in some use cases, like implementing a cache.

In summary, the preservation of insertion order in a linked hash map allows for predictable iteration through the elements, making it easy to understand the order in which the elements will be accessed. This predictable iteration can be useful in situations where the order of the elements is important and also allows for access-order iteration which can be useful in some use cases like implementing a cache.

Additional functionality such as access-order iteration and removal of least-recently accessed elements

A linked hash map is a specific implementation of a hash map that combines the features of both a hash table and a linked list. One of the main advantages of using a linked hash map is its additional functionality such as access-order iteration and removal of least-recently accessed elements.

Access-order iteration: A linked hash map preserves the insertion order of elements by maintaining a doubly-linked list that runs through all the elements in the order they were inserted. This predictable iteration allows for access-order iteration, which iterates through the elements in the order they were last accessed. This can be useful in some use cases like implementing a cache, where the order in which elements are accessed can be used to determine which elements should be removed or retained.

Removal of least-recently accessed elements: A linked hash map also allows for the removal of the least recently accessed elements, which can be useful in some use cases, like implementing a cache. When a cache reaches its capacity, the least recently accessed elements can be removed to make room for new elements. This approach is known as "Least Recently Used" (LRU) and is an effective method of managing cache size.

In summary, a linked hash map has additional functionality such as access-order iteration and removal of least-recently accessed elements. This makes it a powerful tool in data management and manipulation and can be useful in some use cases like implementing a cache, where order of the elements and removal of least-recently accessed elements are important.

IV. Use Cases for a Linked Hash Map

Examples of how a linked hash map can be used in real-world applications, such as caching and data management

A linked hash map is a specific implementation of a hash map that combines the features of both a hash table and a linked list. It has several advantages over regular hash maps, such as predictable iteration and additional functionality like access-order iteration and removal of least-recently accessed elements. Here are some examples of how a linked hash map can be used in real-world applications:

Caching: Caching is one of the most common use cases for a linked hash map. A cache is a temporary storage area that holds frequently accessed data to reduce the number of times the data needs to be retrieved from a slower storage medium. A linked hash map can be used to implement a cache by using the keys as the cache keys and the values as the cached data. The access-order iteration and removal of least-recently accessed elements can be used to determine which elements should be removed or retained when the cache reaches its capacity.

Data Management: Another common use case for a linked hash map is data management. A linked hash map can be used to store and retrieve data in a fast and efficient way. For example, it can be used to implement a data structure that stores employee records, where the keys are the employee IDs and the values are the employee records. The predictable iteration can be used to iterate through the employee records in the order they were added.

Graphs: Linked hash map can be used to implement graphs, where each vertex is represented by a key-value pair and each edge is represented by a link between two vertices. The predictable iteration and access-order iteration can be used to iterate through the vertices and edges in a specific order.

These are just a few examples of how a linked hash map can be used in real-world applications. It is a powerful tool in data management and manipulation and can be used in various use cases where predictable iteration, access-order iteration, and removal of least-recently accessed elements are important.

Here is an example of Java code that uses a LinkedHashMap to implement a cache:

import java.util.LinkedHashMap;
import java.util.Map;

public class LRUCache<K, V> extends LinkedHashMap<K, V> {
    private final int maxEntries;

    public LRUCache(final int maxEntries) {
        super(maxEntries + 1, 1.0f, true);
        this.maxEntries = maxEntries;
    }

    @Override
    protected boolean removeEldestEntry(final Map.Entry<K, V> eldest) {
        return super.size() > maxEntries;
    }
}

This code defines a class called "LRUCache" that extends LinkedHashMap. The class takes one parameter in its constructor, "maxEntries," which represents the maximum number of entries the cache can hold. The class overrides the "removeEldestEntry" method inherited from the LinkedHashMap class. This method is called by the LinkedHashMap when a new entry is added and it returns true if the eldest entry should be removed. In this case, the method checks if the number of entries in the cache is greater than the "maxEntries" parameter, and if so, it returns true to remove the eldest entry.

You can then use this class to create a cache and add, access, and remove elements from it:

LRUCache<String, String> cache = new LRUCache<>(5);
cache.put("key1", "value1");
cache.put("key2", "value2");
// ...
String value = cache.get("key1"); // returns "value1"
cache.remove("key1");

In this example, a cache with a maximum capacity of 5 elements is created. Elements are added to the cache using the "put" method and accessed using the "get" method, just like a regular hash map. When the cache reaches its capacity, the least recently accessed elements will be removed automatically by the removeEldestEntry method.

It's worth noting that there are other implementation for caching like Guava Cache, Caffeine and Ehcache which also provide similar functionality.

Comparison to other data structures such as hash tables and linked lists

A linked hash map is a specific implementation of a hash map that combines the features of both a hash table and a linked list. It has several advantages over both data structures when used individually.

Compared to a hash table:

A linked hash map preserves the insertion order of elements, allowing for predictable iteration, which can be useful in situations where the order of elements is important. A regular hash table does not preserve the insertion order, making iteration unpredictable.
A linked hash map allows for access-order iteration and removal of least-recently accessed elements, which can be useful in some use cases like implementing a cache. A regular hash table does not have these additional functionalities.

Compared to a linked list:

A linked hash map provides fast lookup and insertion of elements using a hash function, making it more efficient for large datasets. A linked list does not have the same fast look-up capabilities and can become slow when dealing with large datasets.
A linked hash map also allows for access-order iteration and removal of least-recently accessed elements, which can be useful in some use cases like implementing a cache. A linked list does not have these additional functionalities.

Linked hash map combines the advantages of both a hash table and a linked list, providing fast look-up, predictable iteration, access-order iteration, and removal of least-recently accessed elements. It can be a useful data structure in situations where these features are needed, such as caching and data management. However, it's worth noting that other data structures like trees, Tries, bloom filters, etc. also have their own specific use cases and advantages.

V. Conclusion

Summary of key points discussed in the article

In this article, we discussed the concept of a linked hash map, a specific implementation of a hash map that combines the features of both a hash table and a linked list. We went over the following key points:

A linked hash map uses a hash function to map keys to values and stores the key-value pairs in an array, similar to a regular hash map. However, it also maintains a doubly-linked list that runs through all the elements in the order they were inserted.
The combination of a hash table and a linked list in a linked hash map allows for improved performance over a regular hash map when dealing with large datasets. It also provides additional functionality such as access-order iteration and removal of least-recently accessed elements.
We also looked at how elements are inserted, accessed, and removed from a linked hash map and how it has constant time complexity.
We also discussed how linked hash map can be used in real-world applications such as caching and data management, where predictable iteration, access-order iteration, and removal of least-recently accessed elements are important.
Finally, we compared linked hash map with other data structures such as hash tables and linked lists and highlighted its advantages over them.

Emphasis on the benefits and practical uses of a linked hash map as a powerful tool in data management and manipulation.

A linked hash map is a powerful data structure that combines the features of both a hash table and a linked list, making it a valuable tool in data management and manipulation.

One of the main benefits of a linked hash map is its improved performance when dealing with large datasets. It uses a hash function to map keys to values, and stores the key-value pairs in an array. Additionally, it maintains a doubly-linked list that runs through all the elements in the order they were inserted, which allows for predictable iteration. This predictable iteration allows for access-order iteration and removal of least-recently accessed elements, which can be useful in some use cases like implementing a cache.

Another key benefit of a linked hash map is its additional functionality such as access-order iteration and removal of least-recently accessed elements. This feature is useful for implementing a cache, where the order in which elements are accessed can be used to determine which elements should be removed or retained.

Additionally, linked hash map can be used in other real-world applications such as data management, where predictable iteration, access-order iteration, and removal of least-recently accessed elements are important. It can be used to store and retrieve data in a fast and efficient way, for example, it can be used to implement a data structure that stores employee records, where the keys are the employee IDs and the values are the employee records.