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Java Hashtable Vs Hashmap: Java Explained

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Developers who use the Java programming language must often pick between two collection classes — the Hashtable and Hashmap — to store and manage data in their applications. While their names are similar and they fulfill the same purpose, these two classes possess a number of important differences. In this article, we’ll provide an overview of Java Hashtables and Hashmaps, identify the key differences between them, outline the key advantages and disadvantages of using each class, explore common use cases for using a Hashtable or Hashmap, review helpful guidelines for choosing the right collection class, and discuss performance considerations when working with Java collections.

Overview of Java Hashtables

A Java Hashtable is a generic collection class used to store and manage data. This class is based on a hashing algorithm and has a key-value pair structure, meaning one element of the data collection is used as an index for the others. Using a Hashtable provides efficient data access since it allows look-ups in constant time, as long as the key is known. (Different hashing algorithms may perform look-up tasks faster than others.) A Hashtable is synchronized, meaning that any action upon the collection should be done in a single thread. It is also thread-safe, meaning that it is safe to use concurrently with multiple threads.

Hashtables are commonly used in Java applications to store and access data quickly and efficiently. They are also used to store objects in a key-value pair structure, allowing for easy retrieval of the object when the key is known. Hashtables are also used to store and access data in a multithreaded environment, as they are thread-safe and synchronized.

Overview of Java Hashmaps

Java Hashmaps are also generic collections used to store and manage data. This class is also based on a hash algorithm, just like a Hashtable, with a similarly structured key-value pair. Rather than being synchronized, though, a Hashmap is an unsynchronized class. Because it can be modified by multiple threads at once, this type of collection cannot guarantee thread safety. Therefore, any action taken on the collection should be done inside a synchronized block or method.

Hashmaps are often used when a program needs to quickly access data based on a key. This is because the hash algorithm used to store the data allows for fast retrieval of the data. Additionally, Hashmaps are often used when a program needs to store data that is constantly changing, as the unsynchronized nature of the class allows for quick updates.

Differences Between Java Hashtables and Hashmaps

The most significant difference between a Java Hashtable and Hashmap is that the Hashtable class is synchronized while the Hashmap class is not. All methods that interact with the collection itself should be included in a synchronized block or method if they are accessing a Hashmap in multiple threads. Additionally, while both collections use a hash algorithm to access data quickly, different hashing algorithms are used in each class; as a result, look-up speeds may vary.

Another difference between the two classes is that Hashtable does not allow null keys or values, while Hashmap does. This means that if you are using a Hashtable, you must ensure that all keys and values are not null. Finally, Hashtable is considered to be a legacy class, while Hashmap is the preferred choice for most applications.

Advantages and Disadvantages of Using a Hashtable or Hashmap

A major advantage of utilizing either the Hashtable or Hashmap class is that they provide efficient access to data since they use hashing algorithms. Additionally, if multiple threads are writing to or reading from a collection in your application, using a Hashtable can ensure atomic operation; this means that all modifications made to the collection are done in a single thread. On the other hand, a Hashmap offers greater flexibility when making modifications to the collection because synchronization is not needed for modifications made by multiple threads.

The main disadvantage of using either of these collection classes is that they cannot guarantee that all modifications made to the collection will be successful if synchronization is not used. Additionally, if too much hashing occurs when look-ups are performed, performance can suffer as a result.

Another disadvantage of using a Hashtable or Hashmap is that they are not thread-safe. This means that if multiple threads are accessing the same collection, there is a risk of data corruption due to race conditions. To prevent this, it is important to use synchronization when accessing the collection from multiple threads.

Common Use Cases for Java Hashtables and Hashmaps

The most common use case for utilizing Java Hashtables or Hashmaps is to store and access data quickly in applications. These collection classes supply efficient access to data due to the hashing algorithms used for look-ups, so they are ideal for large databases or other applications that require many look-ups. Additionally, both collections are highly useful for accessing global variables due to their thread-safety when using a Hashtable and flexibility when using a Hashmap.

Hashtables and Hashmaps are also useful for creating caches, as they can store data in memory for quick access. This is especially useful for applications that require frequent look-ups of the same data, as the data can be stored in the Hashtable or Hashmap and accessed quickly without having to query the database each time. Furthermore, these collections are also useful for creating data structures, such as linked lists, stacks, and queues.

Guidelines for Choosing the Right Collection Class

When picking between the two collection classes, start by asking what type of behavior you need your collection to have. If your application requires synchronization between multiple threads accessing the same collection, then you’ll need to use a Hashtable to ensure atomic operations on the data. Otherwise, if your application doesn’t involve multiple threads accessing/modifying collections at once, then you can use either a Hashtable or Hashmap.

Additionally, it’s important to consider memory constraints. Although fill ratios are similar between these two classes, at large volumes of data a Hashmap can use twice as much memory compared to a Hashtable. This can cause performance problems if an application does not have enough memory.

When deciding between a Hashtable and Hashmap, it is also important to consider the type of data you are working with. If you are dealing with primitive data types, then a Hashtable is the better choice. However, if you are dealing with objects, then a Hashmap is the better choice as it allows for more flexibility in terms of data types.

Performance Considerations When Working with Java Collections

If you choose either the Java Hashtable or Hashmap class for managing data in your application, there are several performance considerations you should keep in mind. First, ensure that you have an appropriate hashing algorithm associated with your collection class; this will ensure that look-ups return results quickly without consuming too much memory. Additionally, depending on the type of collection you use, make sure that any action taken upon it is performed within a synchronized block or method if it involves multiple threads.

Finally, to maintain optimal performance with Java collections, it’s important to monitor fill rates within each collection class. If a collection’s fill rate exceeds 0.75 (75%), efficiencies of look-up processes will be greatly reduced and memory usage will increase exponentially.

Now that you understand the differences between Java Hashtables and Hashmaps and how to choose and use them properly in your applications, you can select the appropriate class to suit your needs. As long as you’re aware of performance considerations and use your collections effectively, you’ll be able to control the complexity and performance of your application efficiently.

Anand Das

Anand Das

Anand is Co-founder and CTO of Bito. He leads technical strategy and engineering, and is our biggest user! Formerly, Anand was CTO of Eyeota, a data company acquired by Dun & Bradstreet. He is co-founder of PubMatic, where he led the building of an ad exchange system that handles over 1 Trillion bids per day.

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