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Java Concurrency and Parallelism

Java Concurrency and Parallelism

By : Jay Wang
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Java Concurrency and Parallelism

Java Concurrency and Parallelism

5 (1)
By: Jay Wang

Overview of this book

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.
Table of Contents (20 chapters)
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Part 1: Foundations of Java Concurrency and Parallelism in Cloud Computing
7
Part 2: Java's Concurrency in Specialized Domains
12
Part 3: Mastering Concurrency in the Cloud – The Final Frontier

Java and Hadoop – a perfect match

Apache Hadoop revolutionized big data storage and processing. At its core lies a strong connection with Java, the widely used programming language known for its versatility and robustness. This section explores how Java and Hadoop work together, providing the necessary tools for effective Hadoop application development.

Why Java? A perfect match for Hadoop development

Several factors make Java the go-to language for Hadoop development:

  • Java as the foundation of Hadoop:
    • Hadoop is written in Java, making it the native language for Hadoop development
    • Java’s object-oriented programming paradigm aligns perfectly with Hadoop’s distributed computing model
    • Java’s platform independence allows Hadoop applications to run seamlessly across different hardware and operating systems
  • Seamless integration with the Hadoop ecosystem:
    • The Hadoop ecosystem encompasses a wide range of tools and frameworks, many of which are built...

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