Java LinkedHashSet parallelStream() Method

🎓 Top 15 Udemy Courses (80-90% Discount): My Udemy Courses - Ramesh Fadatare — All my Udemy courses are real-time and project oriented courses.

▶️ Subscribe to My YouTube Channel (178K+ subscribers): Java Guides on YouTube

▶️ For AI, ChatGPT, Web, Tech, and Generative AI, subscribe to another channel: Ramesh Fadatare on YouTube

The LinkedHashSet.parallelStream() method in Java is used to create a parallel stream over the elements in a LinkedHashSet. 

Table of Contents

1. Introduction
2. parallelStream Method Syntax
3. Examples
   • Creating a Parallel Stream from a LinkedHashSet
   • Processing Elements in Parallel
4. Conclusion

Introduction

The LinkedHashSet.parallelStream() method is a member of the LinkedHashSet class in Java. It allows you to create a parallel stream over the elements in the LinkedHashSet, enabling parallel processing of the elements.

parallelStream() Method Syntax

The syntax for the parallelStream method is as follows:

public Stream<E> parallelStream()

• The method does not take any parameters.
• The method returns a Stream over the elements in the LinkedHashSet, which can be processed in parallel.

Examples

Creating a Parallel Stream from a LinkedHashSet

The parallelStream method can be used to create a parallel stream from a LinkedHashSet.

Example

import java.util.LinkedHashSet;
import java.util.stream.Stream;

public class ParallelStreamExample {
    public static void main(String[] args) {
        // Creating a LinkedHashSet of Strings
        LinkedHashSet<String> animals = new LinkedHashSet<>();

        // Adding elements to the LinkedHashSet
        animals.add("Lion");
        animals.add("Tiger");
        animals.add("Elephant");

        // Creating a parallel stream from the LinkedHashSet
        Stream<String> parallelStream = animals.parallelStream();

        // Printing the elements of the parallel stream
        parallelStream.forEach(animal -> System.out.println("Animal: " + animal));
    }
}

Output (order may vary due to parallel processing):

Animal: Lion
Animal: Tiger
Animal: Elephant

Processing Elements in Parallel

Parallel streams can be used to process elements in parallel, which can improve performance for certain operations.

Example

import java.util.LinkedHashSet;
import java.util.stream.Collectors;
import java.util.stream.Stream;

public class ParallelProcessingExample {
    public static void main(String[] args) {
        // Creating a LinkedHashSet of Strings
        LinkedHashSet<String> animals = new LinkedHashSet<>();

        // Adding elements to the LinkedHashSet
        animals.add("Lion");
        animals.add("Tiger");
        animals.add("Elephant");
        animals.add("Giraffe");
        animals.add("Zebra");

        // Creating a parallel stream from the LinkedHashSet
        Stream<String> parallelStream = animals.parallelStream();

        // Collecting the elements in uppercase in parallel
        LinkedHashSet<String> upperCaseAnimals = parallelStream
            .map(String::toUpperCase)
            .collect(Collectors.toCollection(LinkedHashSet::new));

        // Printing the elements of the upperCaseAnimals LinkedHashSet
        upperCaseAnimals.forEach(animal -> System.out.println("Animal: " + animal));
    }
}

Output (order may vary due to parallel processing):

Animal: LION
Animal: TIGER
Animal: ELEPHANT
Animal: GIRAFFE
Animal: ZEBRA

Conclusion

The LinkedHashSet.parallelStream() method in Java provides a way to create a parallel stream over the elements in a LinkedHashSet. By understanding how to use this method, you can leverage parallel processing to improve the performance of certain operations. This method is useful for processing collections in parallel, making it a valuable tool for managing large datasets and performing complex operations in your Java applications.

My Top and Bestseller Udemy Courses. The sale is going on with a 70 - 80% discount. The discount coupon has been added to each course below:

Build REST APIs with Spring Boot 4, Spring Security 7, and JWT

🆕 High-Demand 80–90% OFF

[NEW] Learn Apache Maven with IntelliJ IDEA and Java 25

🆕 High-Demand 80–90% OFF

ChatGPT + Generative AI + Prompt Engineering for Beginners

🚀 Trending Now 80–90% OFF

Spring 7 and Spring Boot 4 for Beginners (Includes 8 Projects)

🔥 Bestseller 80–90% OFF
Available in Udemy for Business

Building Real-Time REST APIs with Spring Boot - Blog App

🔥 Bestseller 80–90% OFF
Available in Udemy for Business

Building Microservices with Spring Boot and Spring Cloud

🌟 Top Rated 80–90% OFF
Available in Udemy for Business

Java Full-Stack Developer Course with Spring Boot and React JS

🔥 Bestseller 80–90% OFF
Available in Udemy for Business

Build 5 Spring Boot Projects with Java: Line-by-Line Coding

🌟 Top Rated 80–90% OFF

Testing Spring Boot Application with JUnit and Mockito

🔥 Bestseller 80–90% OFF
Available in Udemy for Business

Spring Boot Thymeleaf Real-Time Web Application - Blog App

🔥 Bestseller 80–90% OFF
Available in Udemy for Business

Master Spring Data JPA with Hibernate

🔥 Bestseller 80–90% OFF
Available in Udemy for Business

Spring Boot + Apache Kafka Course - The Practical Guide

🎓 Student Favorite 80–90% OFF
Available in Udemy for Business

Java Testing: Mastering JUnit 5 Framework

🆕 New 80–90% OFF

Reactive Programming in Java: Spring WebFlux and Testing

🌟 Top Rated 80–90% OFF

Spring Boot + RabbitMQ Course - The Practical Guide

🌟 Top Rated 80–90% OFF
Available in Udemy for Business

Functional Programming in Java (Includes Java Collections)

🎓 Student Favorite 80–90% OFF

ChatGPT for Java Developers: Boost Your Productivity with AI

🚀 Trending Now 80–90% OFF