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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

Beyond the basics – advanced Hadoop concepts for Java developers and architects

While understanding the core concepts of Hadoop, such as HDFS and MapReduce, is essential, there are several advanced Hadoop components and technologies that Java developers and architects should be familiar with. In this section, we’ll explore YARN and HBase, two important components of the Hadoop ecosystem, focusing on their practical applications and how they can be leveraged in real-world projects.

Yet another resource negotiator

Yet Another Resource Negotiator (YARN) is a resource management and job scheduling framework in Hadoop. It separates resource management and processing components, allowing multiple data processing engines to run on Hadoop. Its key concepts are as follows:

  • ResourceManager: Manages the global assignment of resources to applications
  • NodeManager: Monitors and manages resources on individual nodes in a cluster
  • ApplicationMaster: Negotiates resources...

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