Book Image

JBoss: Developer's Guide

By : Elvadas Nono Woguia
Book Image

JBoss: Developer's Guide

By: Elvadas Nono Woguia

Overview of this book

Have you often wondered what is the best JBoss product to solve a specific problem? Do you want to get started with a specific JBoss product and know how to integrate different JBoss products in your IT Systems? Then this is the book for you. Through hands-on examples from the business world, this guide presents details on the major products and how you can build your own Enterprise services around the JBoss ecosystem. Starting with an introduction to the JBoss ecosystem, you will gradually move on to developing and deploying clustered application on JBoss Application Server, and setting up high availability using undertow or HA proxy loadbalancers. As you are moving to a micro service archicture, you will be taught how to package existing Java EE applications as micro service using Swarm or create your new micro services from scratch by coupling most popular Java EE frameworks like JPA, CDI with Undertow handlers. Next, you will install and configure JBoss Data grid in development and production environments, develop cache based applications and aggregate various data source in JBoss data virtualization. You will learn to build, deploy, and monitor integration scenarios using JBoss Fuse and run both producers/consumers applications relying on JBoss AMQ. Finally, you will learn to develop and run business workflows and make better decisions in your applications using Drools and Jboss BPM Suite Platform.
Table of Contents (10 chapters)

Grid computing

JBoss DataGrid is also a computing grid; nodes can be used to perform distributed computing. JBoss Datagrid provides various mechanisms to empower data stored in these nodes:

  • Distributed streams that aim to transform a cache entry set into a Java 8 Stream
  • Distributed executors that extend the Java Executor stack to schedule tasks on cache instances

Distributed Streams

Data grid can also be used as a grid computing engine to perform various computation tasks on large and distributed datasets. Users can turn all the cache entries of a local, replication, or invalidation cache into a regular Java Stream using the following operations:

cache.entrySet().stream()
cache.entrySet().parallelStream()

So, instead of iterating...