What is Hashtable in Java? Explained with Examples

A Hashtable in Java is a synchronized data structure that stores key-value pairs using a hashing technique. It ensures thread safety in concurrent environments by determining the index for storing values, making it efficient for lookups. 

Unlike HashMap, it doesn’t allow null keys or values, and its iteration order is not guaranteed. Understanding what is a Hashtable is crucial for implementing thread-safe data structures in Java applications, particularly for legacy systems or simple multi-threaded use cases.

In this blog, we will explore what is a hashtable in Java, along with examples that are relevant within enterprises. 

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What is a Hashtable in Java?

A Hashtable is a synchronized, legacy Java collection that stores key-value pairs using hashing, unlike JavaScript’s Map or unsynchronized HashMap. It forbids null keys and values, ensuring thread safety but causing performance issues in high-concurrency applications. For scalable, modern Java or JavaScript environments, ConcurrentHashMap or asynchronous collections offer better alternatives than Hashtable.

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Hashtable vs HashMap in Java: Key Differences

Both Hashtable and HashMap rely on hashing code in Java to store key-value pairs efficiently, but their concurrency handling and usage contexts differ significantly. While ReactJS developers might often interact with Java backends, understanding these distinctions is critical when dealing with data caching or session management in full-stack applications. 

Although both classes use a hash table to store key-value pairs, they differ in some crucial aspects:

Example Scenario:

You maintain a legacy financial system that relies on Hashtable for thread-safe caching without refactoring. Migrating to HashMap requires extensive code changes and synchronization adjustments. Continuing with Hashtable ensures stability and backward compatibility while new systems adopt modern concurrent collections.

Now that you know what is a hashtable and how it compares with HashMap, let’s understand how it works internally and what makes it efficient.

How Does a Hashtable Work Internally? An Example

Understanding what is a hashtable Java involves knowing its internal workings. A Hashtable stores key-value pairs in an array called buckets, where each key’s hashcode determines the bucket index. When multiple keys share the same index, collisions occur, resolved by chaining, storing entries as linked lists within buckets.

Here are some of the key considerations:

• Collisions impact performance; excessive collisions can slow lookups from O(1) to O(n).
• To manage this, Hashtable monitors its load factor (default 0.75) and triggers rehashing, resizing the internal array and redistributing entries.
• Rehashing improves efficiency but is computationally expensive and should be minimized with proper capacity settings.
• For scenarios requiring insertion order, LinkedHashMap offers a modern alternative combining hash table efficiency with predictable iteration order.

This balance of hashing, collision handling, and resizing ensures Hashtable performs efficiently in typical use cases, though modern alternatives may suit evolving needs better.

This approach makes lookups very fast on average, typically O(1) time complexity.

Code Example:

import java.util.Hashtable;

public class HashtableExample {
    public static void main(String[] args) {
        Hashtable<String, Integer> ht = new Hashtable<>();
        ht.put("Apple", 1);
        ht.put("Banana", 2);
        ht.put("Cherry", 3);

        System.out.println("Value for key 'Apple': " + ht.get("Apple"));
        System.out.println("Value for key 'Banana': " + ht.get("Banana"));
        System.out.println("Value for key 'Cherry': " + ht.get("Cherry"));
    }
}

Output:

Value for key 'Apple': 1
Value for key 'Banana': 2
Value for key 'Cherry': 3

Output Explanation:

The keys "Apple," "Banana," and "Cherry" are hashed to compute their index, efficiently storing corresponding values. If two keys hash to the same index, they are handled by a linked bucket list to avoid collisions.

Let’s explore how to create a hash table Java with examples and constructors to address what is a hashtable in detail.

Step-by-Step Guide to Creating a Hashtable in Java

If you’re wondering what is a hashtable and how to create one, Java provides several constructors to initialize a hashtable based on your specific needs. Using the right constructor helps optimize both performance and memory usage by setting appropriate initial capacity and load factor.

Here’s a step-by-step guide to create a hashtable in Java:

Step 1: Choose the Default Constructor

• Creates an empty Hashtable with an initial capacity of 11 and a load factor of 0.75.
• Suitable for general use when you don’t know the expected size.

Step 2: Use Constructor with Initial Capacity

• Initialize the Hashtable with a specific capacity if you expect a certain number of entries.
• Helps reduce the need for resizing, but setting it too high wastes memory.

Step 3: Use Constructor with Initial Capacity and Load Factor

• Allows fine control by setting how full the Hashtable can get before resizing (load factor).
• A low load factor reduces collisions but increases memory consumption.
• A high load factor saves memory but may increase collisions and slow performance.

Step 4: Use Constructor from an Existing Map

• Copies all key-value pairs from an existing Map into the new Hashtable.
• Useful for converting other map implementations into a Hashtable.

Code Example:

import java.util.Hashtable;
import java.util.HashMap;
import java.util.Map;

public class HashtableConstructorsExample {
    public static void main(String[] args) {
        // Default constructor
        Hashtable<String, Integer> ht1 = new Hashtable<>();
        System.out.println("Default constructor size: " + ht1.size());

        // Constructor with initial capacity
        Hashtable<String, Integer> ht2 = new Hashtable<>(20);
        System.out.println("Initial capacity 20, size: " + ht2.size());

        // Constructor with initial capacity and load factor
        Hashtable<String, Integer> ht3 = new Hashtable<>(20, 0.5f);
        System.out.println("Capacity 20, load factor 0.5, size: " + ht3.size());

        // Constructor from another Map
        Map<String, Integer> map = new HashMap<>();
        map.put("A", 1);
        map.put("B", 2);
        Hashtable<String, Integer> ht4 = new Hashtable<>(map);
        System.out.println("Hashtable from Map, size: " + ht4.size());
    }
}

Output:

Default constructor size: 0
Initial capacity 20, size: 0
Capacity 20, load factor 0.5, size: 0
Hashtable from Map, size: 2

Output Explanation:

Each Hashtable is initially empty except for the one created from an existing Map, which contains two entries. The initial capacity and load factor settings affect internal resizing and performance but not the immediate size. The size() method reflects the actual number of stored entries at creation time.

Important Consideration: Choosing a huge initial capacity or a very low load factor can cause unnecessary memory use without a significant performance gain. It’s best to balance these values based on your application’s expected data size and concurrency needs.

These constructors give you flexibility in how to make a hash table in Java, balancing between performance and memory use.

Hashtable Constructors Explained

When creating a Hashtable Java, selecting the right constructor is crucial for balancing memory usage and performance. Different constructors offer flexibility depending on your expected data volume and access patterns.

• Hashtable(): Creates a hashtable with default settings—initial capacity of 11 and load factor 0.75. Best for general use when the expected size and load are unknown.
• Hashtable(int initialCapacity): Ideal when you know the approximate number of entries in advance. Setting the initial capacity helps avoid costly resizing operations during runtime.
• Hashtable(int initialCapacity, float loadFactor): Allows fine-tuning of the load factor, which controls how full the hashtable can get before resizing. A lower load factor reduces collisions but increases memory usage, while a higher load factor saves memory at the risk of more collisions.
• Hashtable(Map<? extends K, ? extends V> m): Quickly initializes a Hashtable by copying all entries from an existing map. Useful for converting between map implementations.

Quick Tips for Choosing Parameters:

• If your application expects many insertions, increase the initial capacity to minimize resizing.
• Choose a load factor around 0.75 for a good balance between memory consumption and collision rate.
• For memory-sensitive applications, consider a higher load factor but be aware it might affect lookup speed.

Each constructor serves different scenarios, and choosing the right one ensures efficient use of hashtable in Java for your specific requirements.

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Now that we’ve covered how to create hashtables, let’s look at the common operations you can perform on a hash table Java, including examples.

Common Hashtable Operations and Key Methods in Java

Understanding what a hashtable is also involves knowing its core and advanced methods. These methods help you manipulate and interact with the data stored efficiently. Below is a comprehensive overview of key Hashtable in Java methods, with simple descriptions and practical use cases.

Hashtable Methods: Core and Advanced

Hashtable provides a rich set of methods that let you perform various operations, from basic insertion and retrieval to more advanced concurrent programming patterns. Understanding these methods will help you manage data efficiently and avoid common pitfalls.

Below is a table summarizing the key Hashtable methods, their purposes, and when to use them:

Key Method Usage Insights

• rehash(): This method is automatically triggered when the Hashtable’s load factor threshold is reached, resizing internal buckets to optimize hashing code in Java and reduce collisions. Like CSS minimizing browser redraws, rehashing improves access speed, but frequent resizing may cause delays. Setting appropriate initial capacity and load factor helps balance performance and memory.
• putIfAbsent(): Ideal for multi-threaded contexts, this method atomically adds a key-value pair only if the key is missing, preventing overwrites without external locks. Like HTTP’s PUT requests, it ensures safe updates without unintended side effects in concurrent environments.
• computeIfAbsent(): Commonly used for lazy initialization, this method computes and inserts a value only when the key is absent, improving efficiency in cache-like structures. Like dynamic HTML content that loads on demand, it avoids unnecessary computation and supports thread-safe population of Hashtable entries.

Now, let’s understand how you can iterate over a hashtable.

How to Iterate Over a Hashtable?

Understanding what is a Hashtable Java is essential for managing key-value data efficiently, especially in legacy or multi-threaded applications. Hashtables use a synchronized hashing mechanism to store data, unlike modern concurrent maps, making traversal techniques critical for thread safety. Integrating Hashtable operations with backend systems like SQL or MySQL and frontend frameworks like Bootstrap in full-stack Java applications requires efficient, safe iteration.

• Enumeration Interface: Supports legacy iteration over keys or values without fail-fast behavior, which can cause inconsistent traversal during concurrent modifications. Suitable for simple, synchronized scenarios but risky in high-concurrency environments.
• Iterator Interface: Provides fail-fast iteration on most collections, but the default Iterator of Hashtable is not fail-safe unless you explicitly synchronize the map. Without synchronization, concurrent modifications can cause unpredictable behavior or exceptions.
• Ensuring Thread Safety: To safely iterate over a Hashtable in multi-threaded environments, wrap it with Collections.synchronizedMap() provides a synchronized view, or use concurrent collections like ConcurrentHashMap, which offer built-in thread-safe iteration.

Use Cases: 

In Java applications integrating SQL/MySQL for data persistence or Bootstrap for frontend UI, synchronized and predictable data retrieval from Hashtables is vital to maintain state consistency and responsiveness.

Code Example:

import java.util.Hashtable;
import java.util.Enumeration;
import java.util.Iterator;
import java.util.Map;
import java.util.Collections;

public class HashtableIterationExample {
    public static void main(String[] args) {
        Hashtable<String, Integer> ht = new Hashtable<>();
        ht.put("Apple", 50);
        ht.put("Banana", 30);
        ht.put("Cherry", 20);

        // Using Enumeration to iterate keys
        System.out.println("Using Enumeration:");
        Enumeration<String> keysEnum = ht.keys();
        while (keysEnum.hasMoreElements()) {
            String key = keysEnum.nextElement();
            System.out.println(key + " => " + ht.get(key));
        }

        // Creating synchronized map for thread-safe iteration with Iterator
        Map<String, Integer> syncMap = Collections.synchronizedMap(ht);

        // Using Iterator over synchronized map's entrySet
        System.out.println("\nUsing Iterator with synchronizedMap:");
        synchronized (syncMap) {
            Iterator<Map.Entry<String, Integer>> iterator = syncMap.entrySet().iterator();
            while (iterator.hasNext()) {
                Map.Entry<String, Integer> entry = iterator.next();
                System.out.println(entry.getKey() + " => " + entry.getValue());
            }
        }
    }
}

Output:

Using Enumeration:
Apple => 50
Banana => 30
Cherry => 20

Using Iterator with synchronizedMap:
Apple => 50
Banana => 30
Cherry => 20

Output Explanation:

This example shows iteration using Enumeration, which is not fail-fast, and an Iterator wrapped inside a synchronized map to ensure thread safety. The synchronized block around the Iterator prevents concurrent modifications, which is essential in multi-threaded environments.

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Let’s explore some of the advantages and disadvantages of Hashtable Java to explain what is a hashtable and its efficacy in computational operations. 

Advantages and Disadvantages of Hashtable

The Hashtable class in Java provides synchronized key-value storage, making it thread-safe for basic concurrent access. However, its legacy design and coarse-grained locking lead to performance bottlenecks in modern containerized environments using Docker and orchestration platforms like Kubernetes.. For scalable microservices deployed in Kubernetes clusters, finer concurrency controls provided by ConcurrentHashMap are preferred.

Here’s a tabular format to address the advantages and disadvantages of a Hashtable. 

Let’s explore some examples and best practices for Hashable in Java with code. 

Practical Examples and Best Practices for Hashtable in Java

The Hashtable class in Java is part of the legacy collections framework and is commonly used for thread-safe key-value data storage. While it offers simple synchronization, it can impact performance in high-concurrency situations compared to more modern alternatives like ConcurrentHashMap. Understanding a Hashtable's thread-safety guarantees, iteration mechanics, and memory considerations is critical to legacy and current applications. 

Below is a Hashtable example demonstrating basic operations like insertion, retrieval, iteration, and size checking.

Code Example:

import java.util.Hashtable;
import java.util.Enumeration;
import java.util.Map;

public class HashtableDemo {
    public static void main(String[] args) {
        // Initialize Hashtable
        Hashtable<String, Integer> hashtable = new Hashtable<>();

        // Insert key-value pairs
        hashtable.put("Employee1", 50000);
        hashtable.put("Employee2", 60000);
        hashtable.put("Employee3", 55000);

        // Retrieve value for a specific key
        int employee1Salary = hashtable.get("Employee1");
        System.out.println("Salary of Employee1: " + employee1Salary);

        // Iterate over Hashtable using Enumeration
        Enumeration<String> keys = hashtable.keys();
        System.out.println("Hashtable Contents:");
        while (keys.hasMoreElements()) {
            String key = keys.nextElement();
            System.out.println(key + " = " + hashtable.get(key));
        }

        // Check size of the Hashtable
        System.out.println("Total employees in hashtable: " + hashtable.size());
    }
}

Output:

Salary of Employee1: 50000
Hashtable Contents:
Employee3 = 55000
Employee2 = 60000
Employee1 = 50000
Total employees in hashtable: 3

Output Explanation:

The program first retrieves and prints Employee1's salary, which is ₹50,000. Then, it iterates over all the key-value pairs using an Enumeration of keys and prints each pair.

The order of the entries may vary because a Hashtable does not guarantee the order of elements based on insertion. Lastly, it prints the total number of entries in the Hashtable, which is 3, reflecting the three key-value pairs inserted.

Also Read: Top 12 Java Open Source Projects on GitHub You Should Explore in 2025

Let’s explore some of the best practices for the Hashtable in Java applications to comprehensively understand what is a hashtable. 

Best Practices for Hashtable in Java

When choosing a Hashtable in Java, it’s crucial to understand its strengths and limitations, especially in multi-threaded applications. While Hashtable provides thread safety through synchronized methods, it may introduce performance bottlenecks in high-concurrency scenarios compared to alternatives like ConcurrentHashMap. Using a Hashtable effectively requires careful handling of null values, iteration behavior, and awareness of its legacy status in modern Java development

• Use When Thread Safety is Needed but Simplicity Suffices: Hashtable’s synchronized methods make it a straightforward choice for simple concurrent access, but it might not be the most efficient.
• Prefer ConcurrentHashMap for High-Concurrency Scenarios: ConcurrentHashMap offers finer-grained locking and higher throughput for better performance in multithreaded applications.
• Avoid Null Keys and Values: Since Hashtable does not support nulls, always check data before insertion to prevent NullPointerException.
• Consider Alternatives for New Projects: In most modern Java applications, HashMap or ConcurrentHashMap are preferred unless you have legacy code or specific synchronization requirements.
• Mind Iterator Behavior: When iterating over a Hashtable, remember that its enumerators are not fail-fast. Be cautious when modifying the hashtable during iteration to avoid inconsistent results.

Also Read: Top 22 Open Source Java Projects to Enhance Your Development Skills

How Can upGrad Help You Learn Java and Data Structures?

Learning key data structures and understanding what is a Hashtable and hashing code in Java is essential for building efficient and thread-safe applications. Understanding concepts such as synchronization, hashing mechanics, and performance optimization ensures you write reliable, scalable code across real-world projects.

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