Book Image

Distributed Computing in Java 9

Book Image

Distributed Computing in Java 9

Overview of this book

Distributed computing is the concept with which a bigger computation process is accomplished by splitting it into multiple smaller logical activities and performed by diverse systems, resulting in maximized performance in lower infrastructure investment. This book will teach you how to improve the performance of traditional applications through the usage of parallelism and optimized resource utilization in Java 9. After a brief introduction to the fundamentals of distributed and parallel computing, the book moves on to explain different ways of communicating with remote systems/objects in a distributed architecture. You will learn about asynchronous messaging with enterprise integration and related patterns, and how to handle large amount of data using HPC and implement distributed computing for databases. Moving on, it explains how to deploy distributed applications on different cloud platforms and self-contained application development. You will also learn about big data technologies and understand how they contribute to distributed computing. The book concludes with the detailed coverage of testing, debugging, troubleshooting, and security aspects of distributed applications so the programs you build are robust, efficient, and secure.
Table of Contents (17 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
Customer Feedback
2
Communication between Distributed Applications
3
RMI, CORBA, and JavaSpaces

Distributed computing for big data


Distributed computing is not required for all computing solutions. Consider that the business doesn't have any time constraints in system processing and an asynchronous remote process can do the job efficiently in the expected time of processing. Then, why should the business invest in having either a more competent resource or a distributed environment to bring performance improvements in such a process?

Over the past few years, organizations are looking at reducing costs and are investing in critical and essential business needs. This means that, if there is a real need for processing a complex data analysis and the organization has a number of additional resources available, it can make use of distributed computing wherein each computing resource, with its own memory, can process a bit of the complex analysis and contribute to its completion.

Not only that; instead of having a single huge computing resource, if we utilize multiple commodity hardware to...