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Practical Real-time Data Processing and Analytics

You're reading from Practical Real-time Data Processing and Analytics

Product type Book

Published in Sep 2017

Publisher Packt

ISBN-13 9781787281202

Pages 360 pages

Edition 1st Edition

Languages

Concepts

Table of Contents (20) Chapters

Title Page

Credits

About the Authors

About the Reviewers

www.PacktPub.com

Customer Feedback

Preface

1. Introducing Real-Time Analytics

2. Real Time Applications – The Basic Ingredients

3. Understanding and Tailing Data Streams

4. Setting up the Infrastructure for Storm

5. Configuring Apache Spark and Flink

6. Integrating Storm with a Data Source

7. From Storm to Sink

8. Storm Trident

9. Working with Spark

10. Working with Spark Operations

11. Spark Streaming

12. Working with Apache Flink

13. Case Study

Setting up infrastructure for data ingestion

There are multiple tools and frameworks available on the market for data ingestion. We will discuss the following in the scope of this book:

Apache Kafka
Apache NiFi
Logstash
Fluentd
Apache Flume

Apache Kafka

Kafka is message broker which can be connected to any real-time framework available on the market. In this book, we will use Kafka often for all types of examples. We will use Kafka as a data source which keeps data from files in queues for further processing. Download Kafka from https://www.apache.org/dyn/closer.cgi?path=/kafka/0.10.1.1/kafka_2.11-0.10.1.1.tgz to your local machine. Once the kafka_2.11-0.10.1.1.tgz file is downloaded, extract the files using the following command:

cp kafka_2.11-0.10.1.1.tgz /home/ubuntu/demo/kafkacd /home/ubuntu/demo/kafkatar -xvf kafka_2.11-0.10.1.1.tgz

The following files and folders are extracted as seen in the following screenshot:

Note

Change the listener's property in the server.properties file. It should be...

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