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

Big data characteristics


Big data maintenance and analysis are formed by the characteristics of data, including the structure or unstructured nature of the data, which helps in obtaining more accurate results from data processing. Big data elements can be referred to as the four V's; they are represented in the following figure:

Volume

When organizations collect information over the years, it makes an extremely huge volume of data. Such huge volume a of data may be generated from user information, application-generated audit information, and any unstructured information from the online sources. Analytic tools help in choosing the right set of data to perform the analysis and in recognizing the important metrics, which are appropriate to the perspective you may want to review from that information.

From the organization's perspective, a huge volume of information can be segregated into the following types of information:

  • Business identification data: Each organization performs certain business...