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

RabbitMQ – messaging that works


RabbitMQ is one of the most sought after broker/queue services that works in production implementation with Storm. It's a very robust and versatile messaging system, that is supported both in open source as well as in a commercial version across all major operating systems. It has both durable and in-memory configuration on queues where the developers get enough flexibility to decide and choose on trade-offs between reliability and performance.

A few terms that would be used very often in context to RabbitMQ in particular, or any other queuing system are described as follows:

  • Producer/publisher: It's the client component that writes or sends the messages to the queue
  • Queue: It's actually the in-memory buffer that stores the message, from the time it's sent to the queue to the time it's read off the queue by a consumer application
  • Consumer/subscriber: It's the client component that receives or reads the messages off the queue

In the case of RabbitMQ, the producer...