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Java Concurrency and Parallelism
Java Concurrency and Parallelism

Java Concurrency and Parallelism : Master advanced Java techniques for cloud-based applications through concurrency and parallelism

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Java Concurrency and Parallelism

Concurrency, Parallelism, and the Cloud: Navigating the Cloud-Native Landscape

Welcome to an exciting journey into the world of Java’s concurrency and parallelism paradigms, which are crucial for developing efficient and scalable cloud-native applications. In this introductory chapter, we’ll establish a solid foundation by exploring the fundamental concepts of concurrency and parallelism, as well as their significance in contemporary software design. Through practical examples and hands-on practice problems, you’ll gain a deep understanding of these principles and their application in real-world scenarios.

As we progress, we’ll delve into the transformative impact of cloud computing on software development and its synergistic relationship with Java. You’ll learn how to leverage Java’s powerful features and libraries to tackle the challenges of concurrent programming in cloud-native environments. We’ll also explore case studies from...

Technical requirements

Here is the minimal Java JRE/JDK setup guide for macOS, Windows, and Linux. You can follow these steps:

  1. Download the desired version of Java JRE or JDK from the official Oracle website: https://www.oracle.com/java/technologies/javase-downloads.html.
  2. Choose the appropriate version and operating system to download.
  3. Install Java on your system:
    • macOS:
      1. Double-click the downloaded .dmg file.
      2. Follow the installation wizard and accept the license agreement.
      3. Drag and drop the Java icon into the Applications folder.
    • Windows:
      1. Run the downloaded executable (.exe) file.
      2. Follow the installation wizard and accept the license agreement.
      3. Choose the installation directory and complete the installation.
    • Linux:
      • Extract the downloaded .tar.gz archive to a directory of your choice.

    For system-wide installation, move the extracted directory to /usr/local/java.

  4. Set the environment variables:
    • macOS and Linux:
      1. Open the terminal.
      2. Edit the ~/.bash_profile or ~/.bashrc file (depending...

The dual pillars of concurrency versus parallelism – a kitchen analogy

Welcome to the kitchen of Java concurrency and parallelism! Here, we’ll whisk you through a culinary journey, unveiling the art of multitasking and high-speed cooking in programming. Imagine juggling different tasks like a master chef – that’s concurrency. Then, picture multiple chefs cooking in harmony for a grand feast – that’s parallelism. Get ready to spice up your Java applications with these essential skills, from handling user interactions to crunching massive data. Bon appétit to the world of efficient and responsive Java cooking!

Defining concurrency

In Java, concurrency allows a program to manage multiple tasks such that they seem to run simultaneously, enhancing performance even on single-core systems. A core refers to a processing unit within a computer’s CPU that is capable of executing programming instructions. While true parallel execution...

Java and the cloud – a perfect alliance for cloud-native development

Java’s journey with cloud computing is a testament to its adaptability and innovation. The fusion of their capabilities has created a powerful alliance for cloud-native development. Imagine yourself as an architect, wielding Java’s toolkit at the forefront of cloud technology. Here, Java’s versatility and robustness partner with the cloud’s agility and scalability to offer a canvas for innovation and growth. We’re not just discussing theoretical concepts – we’re stepping into a realm where Java’s pragmatic application in the cloud has revolutionized development, deployment, and application management. Let’s uncover how Java in the cloud era is not just an option, but a strategic choice for developers seeking to unlock the full potential of cloud-native development.

Exploring cloud service models and their impact on software development

Java...

Modern challenges in cloud-native concurrency and Java’s weapons of choice

The cloud’s concurrency challenges loom, but Java’s not backing down. We’ll tackle these challenges in transactions, data consistency, and microservices states, all while wielding tools such as Akka, Vert.x, and reactive programming. Choose your weapons wisely, for the cloud-native concurrency challenge is yours to conquer!

Wrangling distributed transactions in Java – beyond classic commits

In the wild jungle of distributed systems, managing transactions across services and databases can be a daunting task. Traditional methods stumble over network delays, partial failures, and diverse systems. But fear not, Java warriors! We’ve got your back with a robust arsenal of solutions:

  • Two-phase commit (2PC): This classic protocol ensures all parties in a transaction commit or roll back together. While not ideal for high-speed environments due to its blocking nature...

Conquering concurrency – best practices for robust cloud-native applications

Building cloud apps that juggle multiple tasks at once? It’s like managing a bustling zoo of data and operations! But fear not, because we’ve got the best practices to tame the concurrency beasts and build robust, scalable cloud apps. Here are the best practices to embed:

  • Early identification: Proactively identify and address concurrency challenges through early analysis, modeling, and code review:
    • Analyze application requirements: Identify critical sections, shared resources, and potential points of contention early in the design phase
    • Use concurrency modeling tools: Utilize modeling tools such as statecharts or Petri nets to visualize and analyze potential concurrency issues
    • Review existing code for concurrency bugs: Conduct code reviews and static analysis to identify potential race conditions, deadlocks, and other concurrency problems
  • Embrace immutable data: Embrace unchangeable...

Summary

Chapter 1 introduced the fundamental concepts of Java cloud-native development, focusing on concurrency and parallelism. It distinguished between managing tasks on single-core (concurrency) versus multi-core processors (parallelism), with practical Java examples. The chapter highlighted Java’s role in cloud computing, emphasizing its scalability, ecosystem, and community. Practical applications, including the Java AWS SDK and Lambda functions, illustrated Java’s adaptability across cloud models.

Significant Java updates such as Project Loom and advanced garbage collection methods were discussed for optimizing performance. Java’s effectiveness in complex environments was showcased through case studies of Netflix and X (formerly Twitter), among others. These focused on microservices, real-time data processing, and scalability.

The narrative then shifted to practical strategies for distributed transactions, data consistency, and microservices state management...

Exercise – exploring Java executors

Objective: In this exercise, you will explore different types of executors provided by the Java Concurrency API. You will refer to the Java documentation, use a different executor implementation, and observe its behavior in a sample program.

Instructions:

  • Visit the Java documentation for the Executors class: https://docs.oracle.com/javase/8/docs/api/java/util/concurrent/Executors.html.
  • Read through the documentation and familiarize yourself with the different factory methods provided by the Executors class for creating Executor instances.
  • Choose a different executor implementation other than the fixed thread pool used in the previous examples. Some options include the following:
    • Executors.newCachedThreadPool()
    • Executors.newSingleThreadExecutor()
    • Executors.newScheduledThreadPool(int corePoolSize)
  • Create a new Java class called ExecutorExploration and replace the Executor creation line with the chosen executor implementation...

Questions

  1. What is the primary advantage of using microservices in cloud-based Java applications?
    1. Increased security through monolithic architecture
    2. Easier to scale and maintain individual services
    3. Eliminating the need for databases
    4. Unified, single-point configuration for all services
  2. In Java concurrency, which mechanism is used to handle multiple threads trying to access a shared resource simultaneously?
    1. Inheritance
    2. Synchronization
    3. Serialization
    4. Polymorphism
  3. Which of the following is NOT a feature of Java’s java.util.concurrent package?
    1. Fork/join framework
    2. ConcurrentHashMap
    3. ExecutorService
    4. Stream API
  4. In serverless computing, which feature is a key benefit when using Java?
    1. Static typing
    2. Manual scaling
    3. Automatic scaling and management of resources
    4. Low-level hardware access
  5. What is a common challenge when managing distributed data in Java cloud applications?
    1. Graphics rendering
    2. Data consistency and synchronization
    3. Single-thread execution
    4. User interface design
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Key benefits

  • Master concurrency and parallelism to overcome cloud computing challenges in Java
  • Build scalable solutions with Big Data, ML, microservices, and serverless architectures
  • Explore cloud scaling, GPU utilization, and future tech innovations in Java applications
  • Purchase of the print or Kindle book includes a free PDF eBook

Description

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.

Who is this book for?

This book is for Java developers, software engineers, and cloud architects with intermediate Java knowledge. It's ideal for professionals transitioning to cloud-native development or seeking to enhance their concurrent programming skills. DevOps engineers and tech leads involved in cloud migration will also find valuable insights. Basic Java proficiency, familiarity with cloud concepts, and some experience with distributed systems is expected.

What you will learn

  • Understand Java concurrency in cloud app development
  • Get to grips with the core concepts of serverless computing in Java
  • Boost cloud scaling and performance using Java skills
  • Implement Java GPU acceleration for advanced computing tasks
  • Gain insights into Java's role in the evolving cloud and AI technology
  • Access hands-on exercises for real-world Java applications
  • Explore diverse Java case studies in tech and fintech
  • Implement Java in AI-driven cloud and data workflows
  • Analyze Java's application in IoT and real-time analytics
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Publication date : Aug 30, 2024
Length: 496 pages
Edition : 1st
Language : English
ISBN-13 : 9781805129264
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Table of Contents

17 Chapters
Part 1: Foundations of Java Concurrency and Parallelism in Cloud Computing Chevron down icon Chevron up icon
Chapter 1: Concurrency, Parallelism, and the Cloud: Navigating the Cloud-Native Landscape Chevron down icon Chevron up icon
Chapter 2: Introduction to Java’s Concurrency Foundations: Threads, Processes, and Beyond Chevron down icon Chevron up icon
Chapter 3: Mastering Parallelism in Java Chevron down icon Chevron up icon
Chapter 4: Java Concurrency Utilities and Testing in the Cloud Era Chevron down icon Chevron up icon
Chapter 5: Mastering Concurrency Patterns in Cloud Computing Chevron down icon Chevron up icon
Part 2: Java's Concurrency in Specialized Domains Chevron down icon Chevron up icon
Chapter 6: Java and Big Data – a Collaborative Odyssey Chevron down icon Chevron up icon
Chapter 7: Concurrency in Java for Machine Learning Chevron down icon Chevron up icon
Chapter 8: Microservices in the Cloud and Java’s Concurrency Chevron down icon Chevron up icon
Chapter 9: Serverless Computing and Java’s Concurrent Capabilities Chevron down icon Chevron up icon
Part 3: Mastering Concurrency in the Cloud – The Final Frontier Chevron down icon Chevron up icon
Chapter 10: Synchronizing Java’s Concurrency with Cloud Auto-Scaling Dynamics Chevron down icon Chevron up icon
Chapter 11: Advanced Java Concurrency Practices in Cloud Computing Chevron down icon Chevron up icon
Chapter 12: The Horizon Ahead Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon
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