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If you’re a software developer, architect, or systems engineer, exploring Java’s concurrency utilities and synchronization in the cloud, this book is an essential resource. Tech visionary Jay Wang, with over three decades of experience transforming industry giants, brings unparalleled expertise to guide you through Java’s concurrency and parallel processing in cloud computing.
This comprehensive book starts by establishing the foundational concepts of concurrency and parallelism, vital for cloud-native development, and gives you a complete overview, highlighting challenges and best practices. Wang expertly demonstrates Java’s role in big data, machine learning, microservices, and serverless computing, shedding light on how Java’s tools are effectively utilized in these domains. Complete with practical examples and insights, this book bridges theory with real-world applications, ensuring a holistic understanding of Java in cloud-based scenarios. You’ll navigate advanced topics, such as synchronizing Java’s concurrency with cloud auto-scaling and GPU computing, and be equipped with the skills and foresight to tackle upcoming trends in cloud technology.
This book serves as your roadmap to innovation and excellence in Java cloud applications, giving you in-depth knowledge and hands-on practice for mastering Java in the cloud era.
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Veröffentlichungsjahr: 2024
Java Concurrency and Parallelism
Master advanced Java techniques for cloud-based applications through concurrency and parallelism
Jay Wang
Copyright © 2024 Packt Publishing
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Jay Wang, a trailblazer in the IT sector, boasts a career spanning over two decades, marked by leadership roles at IT powerhouses such as Accenture, IBM, and a globally renowned telecommunications firm. An expert in Java since 2001 and cloud technologies since 2018, Jay excels in transitioning projects from monolithic to microservice architectures and cloud. As founder of Digitech Edge, he guides clients through AI-driven cloud solutions. His educational background includes an MS in management of IT from the University of Virginia and an MS in information systems from George Mason University.
Artur Skowroński is the head of Java/Kotlin engineering at VirtusLab. He has been in the industry for ten years. During this time, he has had the opportunity to work in various roles, such as software engineer, tech lead, architect, and even technical product manager. This diverse experience enables him to approach problems from a holistic perspective. He is also an active member of the tech community, serving as the lead of the Krakow Kotlin User Group and the author of the JVM Weekly Newsletter.
Akshay Phadke started his journey as a software engineer after graduating with a master of science in electrical and computer engineering from Georgia Institute of Technology in 2016. He has worked on building data-intensive applications and experiences across different industries such as networking and telecommunications, enterprise software, and finance. His work has spanned multiple areas of software development such as big data, data and platform engineering, CI/CD and DevOps, developer productivity and tooling, infrastructure and observability, and full stack web development. His professional interests include open source software, distributed systems, and building and scaling products in a start-up environment.
Welcome to Java Concurrency and Parallelism, which explores Java’s concurrency and parallelism within the context of modern cloud computing. As technology evolves, mastering these concepts is crucial for developing robust, scalable, and efficient cloud-native applications.
This book is structured into three distinct yet interconnected parts, each aimed at providing in-depth knowledge and practical skills to enhance your proficiency in Java concurrency. Part 1 lays the groundwork by introducing the fundamental principles of concurrency and parallelism, essential for any modern software development. This section covers the basics of Java concurrency, including threads and processes, and delves into advanced topics such as the java.util.concurrent package, the Fork/Join framework, and parallel streams. It also explores practical implementation strategies and concurrency patterns tailored for cloud environments, equipping you with the foundational tools needed to tackle the unique challenges of cloud-native Java applications.
Part 2 builds on the foundational knowledge from Part 1, focusing on how Java’s concurrency capabilities address complex challenges across various specialized domains. This part examines Java’s role in big data, machine learning, microservices, and serverless computing. Through practical examples, code snippets, and real-world use cases, it demonstrates how to harness Java’s concurrency features to build scalable, high-performance applications in these cutting-edge fields.
Part 3 synthesizes the knowledge from the previous sections, applying it to the advanced realm of cloud computing. It covers synchronization with cloud auto-scaling, and advanced concurrency practices and explores emerging trends such as edge computing and quantum computing. This section prepares you to leverage Java’s concurrency capabilities to their fullest potential, enabling you to stay at the forefront of technological advancements in cloud computing.
This book is intended for Java developers, software engineers, and cloud computing professionals who aim to deepen their understanding of concurrent programming and parallel processing in Java. A foundational knowledge of Java and a basic familiarity with cloud computing concepts will be beneficial. Whether you are an aspiring developer or an experienced professional, this book will provide you with the knowledge and skills to excel in developing cloud-native Java applications.
Chapter 1, Concurrency, Parallelism, and the Cloud: Navigating the Cloud-Native Landscape, introduces the fundamental principles and distinctions between concurrency and parallelism in Java. It sets the stage for understanding how these concepts are critical in the development of modern cloud-native applications.
Chapter 2, Introduction to Java’s Concurrency Foundations: Threads, Processes, and Beyond, explores the basics of Java concurrency, including threads and processes. This chapter provides a solid introduction to the building blocks of concurrent programming in Java.
Chapter 3, Mastering Parallelism in Java, delves into tools and frameworks that enhance Java’s parallel processing capabilities. You will learn how to leverage multi-core processors and distributed systems to improve performance.
Chapter 4, Java Concurrency Utilities and Testing in the Cloud Era, focuses on practical implementation strategies and testing for cloud-based applications. You will discover how to design, implement, and validate concurrent systems that can thrive in distributed environments.
Chapter 5, Mastering Concurrency Patterns in Cloud Computing, provides a toolkit of concurrency patterns for cloud environments. These patterns serve as essential solutions for common challenges in cloud-native Java applications.
Chapter 6, Java and Big Data – a Collaborative Odyssey, examines Java’s role in big data and its concurrency tools. You will learn how Java efficiently processes massive datasets through parallel and distributed computing.
Chapter 7, Concurrency in Java for Machine Learning, demonstrates how Java’s concurrency features accelerate machine learning. This chapter shows how to build scalable, high-performance machine learning applications using multi-threading and parallel processing.
Chapter 8, Microservices in the Cloud and Java’s Concurrency, explores Java’s concurrency capabilities in microservices architectures. You will understand the strategies for managing concurrent operations in distributed environments to create resilient, scalable microservices.
Chapter 9, Serverless Computing and Java’s Concurrent Capabilities, illustrates Java’s adaptation to serverless architectures. You will discover how to build scalable, cost-effective solutions for varying workloads using Java’s concurrency models.
Chapter 10, Synchronizing Java’s Concurrency with Cloud Auto-Scaling Dynamics, covers synchronization with cloud auto-scaling. You will learn how to build applications that seamlessly adapt to the elastic nature of cloud environments.
Chapter 11, Advanced Java Concurrency Practices in Cloud Computing, delves into advanced concurrency techniques for the cloud. This chapter covers cutting-edge techniques such as GPU acceleration and implementing robust redundancy mechanisms.
Chapter 12, The Horizon Ahead, looks at emerging trends and future innovations in cloud computing. You will explore serverless Java beyond function as a service, Java’s role in edge computing, and its integration with AI and machine learning in cloud ecosystems.
You should have a few prerequisite skills or a certain level of knowledge in the following:
Basic knowledge of Java programmingBasic knowledge of cloud computing, especially the AWS environment, as most code examples for cloud applications are in AWSFamiliarity with Java frameworks such as Spring CloudExperience with build tools such as MavenBasic understanding of containerization using DockerAwareness of Quarkus for building cloud-native applicationsWe hope this book provides you with the insights and tools needed to master Java concurrency in the cloud era, transforming you from proficient developers into experts ready to tackle the challenges and opportunities of tomorrow’s technological landscape.
Software/hardware covered in the book
Operating system requirements
Java, AWS account, Spring cloud, Docker, and Quarkus
Windows, macOS, or Linux
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Due to a recent tech update and page limit constraints, many code snippets in this book are shortened versions. They are used in chapters for demonstration purposes only. Some code has also been revised based on the update. For the most current, complete, and functional code, please refer to the book’s accompanying GitHub repository. The repository should be considered the primary and preferred source for all code examples.
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import java.util.stream.IntStream; public class ParallelKitchen { public static void main(String[] args) { IntStream.range(0, 10).parallel().forEach(i -> { System.out.println(“Cooking dish #” + i + “ in parallel...”); // Simulate task try { Thread.sleep(600); } catch (InterruptedException e) { Thread.currentThread().interrupt(); } }); } }Any command-line input or output is written as follows:
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Submit your proof of purchaseThat’s it! We’ll send your free PDF and other benefits to your email directlyThe first part of the book lays the groundwork for understanding and implementing concurrency and parallelism in Java, focusing on cloud computing environments. It introduces key concepts, tools, and patterns that form the backbone of efficient and scalable Java applications in the cloud.
This part includes the following chapters:
Chapter 1, Concurrency, Parallelism, and the Cloud: Navigating the Cloud-Native LandscapeChapter 2, Introduction to Java's Concurrency Foundations: Threads, Processes, and BeyondChapter 3, Mastering Parallelism in JavaChapter 4, Java Concurrency Utilities and Testing in the Cloud EraChapter 5, Mastering Concurrency Patterns in Cloud Computing