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Real-Time Big Data Analytics

You're reading from   Real-Time Big Data Analytics Design, process, and analyze large sets of complex data in real time

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Product type Paperback
Published in Feb 2016
Publisher
ISBN-13 9781784391409
Length 326 pages
Edition 1st Edition
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Author (1):
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Shilpi Saxena Shilpi Saxena
Author Profile Icon Shilpi Saxena
Shilpi Saxena
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Table of Contents (12) Chapters Close

Preface 1. Introducing the Big Data Technology Landscape and Analytics Platform FREE CHAPTER 2. Getting Acquainted with Storm 3. Processing Data with Storm 4. Introduction to Trident and Optimizing Storm Performance 5. Getting Acquainted with Kinesis 6. Getting Acquainted with Spark 7. Programming with RDDs 8. SQL Query Engine for Spark – Spark SQL 9. Analysis of Streaming Data Using Spark Streaming 10. Introducing Lambda Architecture Index

Coding our first Spark Streaming job


In this section, we will code and execute our first Spark Streaming job in Scala. We will also simulate the streaming data by creating a temporary stream.

Creating a stream producer

Perform the following steps to create a stream producer which continuously reads the input data provided by the user from the console and then further submits that data to a socket:

  1. Open and edit your Spark-Examples project and create a new Scala package and class named chapter.nine.StreamProducer.java.

  2. Next, edit StreamProducer.java and add the following piece of code:

    import java.net.*;
    import java.io.*;
    
    public class StreamProducer {
    
      public static void main(String[] args) {
    
        if (args == null || args.length < 1) {
          System.out.println("Usage - java chapter.nine.StreamProducer <port#>");
          System.exit(0);
        }
        System.out.println("Defining new Socket on " + args[0]);
    try (ServerSocket soc = new ServerSocket(Integer.parseInt(args[0]))) {
    
    System.out...
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