Building Java 8 Web Applications with Microservices

Building Java 8 Web Applications with Microservices

English | FLV | AVC 1280×720 | AAC 44KHz 2ch | 3.5 Hours | 1.65 GB

Building Java 8 Web Applications with Microservices LiveLessons Workshop utilizes live code demonstration to build a fully functional application using minimal external dependencies and Java 8. This application consumes a real-time feed of high-velocity data, contains services that make sense of the data, and presents it in a JavaFX dashboard. Along the way, you’ll encounter Java 8 streams, lambdas, new ways of working with collections, and the new date and time API.
What You Will Learn

  • Sort messages containing information about users to create a leaderboard of the most active Twitter users
  • Consume messages about tweet sentiment to create a pie chart that updates in real time to show overall mood on Twitter
  • Filter sentiment messages to create a view of happiness levels over a ten-minute period
  • Build a microservice that parses a file of real Twitter data and publishes these tweets via web sockets
  • Build a microservice that parses Twitter messages and emits just the username
  • Build a microservice that analyses Twitter messages for sentiment and publishes these moods
  • Connect the application to a live Twitter feed
Table of Contents

01 Introduction

Introduction to Java 8 Features
02 Overview of Java 8
03 Our application
04 Creating a stub user service
05 What are lambdas
06 The basics of JavaFX
07 New Java 8 methods on existing APIs
08 Introduction to Streams
09 Creating the UI
10 How did Java 8 help us

Lambdas Will Simplify Your Code
11 Create a stub mood service
12 Updating a pie chart with moods Part 1
13 Updating a pie chart with moods Part 2
14 Filtering moods to display happiness over time
15 Questions and discussion

Creating Simple WebSocket Services
16 An introduction to WebSockets Part 2
17 Creating a service to publish data from a file

Java 8 for Business Logic
18 Creating a simple user service
19 Creating a service to analyze tweet mood

Questions and Discussion
20 Questions and discussion

21 Summary