Book Image

Practical Real-time Data Processing and Analytics

Book Image

Practical Real-time Data Processing and Analytics

Overview of this book

With the rise of Big Data, there is an increasing need to process large amounts of data continuously, with a shorter turnaround time. Real-time data processing involves continuous input, processing and output of data, with the condition that the time required for processing is as short as possible. This book covers the majority of the existing and evolving open source technology stack for real-time processing and analytics. You will get to know about all the real-time solution aspects, from the source to the presentation to persistence. Through this practical book, you’ll be equipped with a clear understanding of how to solve challenges on your own. We’ll cover topics such as how to set up components, basic executions, integrations, advanced use cases, alerts, and monitoring. You’ll be exposed to the popular tools used in real-time processing today such as Apache Spark, Apache Flink, and Storm. Finally, you will put your knowledge to practical use by implementing all of the techniques in the form of a practical, real-world use case. By the end of this book, you will have a solid understanding of all the aspects of real-time data processing and analytics, and will know how to deploy the solutions in production environments in the best possible manner.
Table of Contents (20 chapters)
Title Page
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface

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...