You're reading from Java Concurrency and Parallelism Master advanced Java techniques for cloud-based applications through concurrency and parallelism

Product type Paperback

Published in Aug 2024

Publisher Packt

ISBN-13 9781805129264

Length 496 pages

Edition 1st Edition

Languages

Java

Tools

Boost

Concepts

Application Development

Author (1):

Jay Wang

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Table of Contents (20) Chapters

Preface

1. Part 1: Foundations of Java Concurrency and Parallelism in Cloud Computing

2. Chapter 1: Concurrency, Parallelism, and the Cloud: Navigating the Cloud-Native Landscape FREE CHAPTER

3. Chapter 2: Introduction to Java’s Concurrency Foundations: Threads, Processes, and Beyond

4. Chapter 3: Mastering Parallelism in Java

5. Chapter 4: Java Concurrency Utilities and Testing in the Cloud Era

6. Chapter 5: Mastering Concurrency Patterns in Cloud Computing

7. Part 2: Java's Concurrency in Specialized Domains

8. Chapter 6: Java and Big Data – a Collaborative Odyssey

9. Chapter 7: Concurrency in Java for Machine Learning

10. Chapter 8: Microservices in the Cloud and Java’s Concurrency

11. Chapter 9: Serverless Computing and Java’s Concurrent Capabilities

12. Part 3: Mastering Concurrency in the Cloud – The Final Frontier

13. Chapter 10: Synchronizing Java’s Concurrency with Cloud Auto-Scaling Dynamics

14. Chapter 11: Advanced Java Concurrency Practices in Cloud Computing

15. Chapter 12: The Horizon Ahead

16. Index

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17. Other Books You May Enjoy

Appendix A: Setting up a Cloud-Native Java Environment

1. Appendix B: Resources and Further Reading

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...