Book Image

Modern Big Data Processing with Hadoop

By : V Naresh Kumar, Manoj R Patil, Prashant Shindgikar
Book Image

Modern Big Data Processing with Hadoop

By: V Naresh Kumar, Manoj R Patil, Prashant Shindgikar

Overview of this book

The complex structure of data these days requires sophisticated solutions for data transformation, to make the information more accessible to the users.This book empowers you to build such solutions with relative ease with the help of Apache Hadoop, along with a host of other Big Data tools. This book will give you a complete understanding of the data lifecycle management with Hadoop, followed by modeling of structured and unstructured data in Hadoop. It will also show you how to design real-time streaming pipelines by leveraging tools such as Apache Spark, and build efficient enterprise search solutions using Elasticsearch. You will learn to build enterprise-grade analytics solutions on Hadoop, and how to visualize your data using tools such as Apache Superset. This book also covers techniques for deploying your Big Data solutions on the cloud Apache Ambari, as well as expert techniques for managing and administering your Hadoop cluster. By the end of this book, you will have all the knowledge you need to build expert Big Data systems.
Table of Contents (12 chapters)

Real-time streaming components

In the following sections we will walk through some important real-time streaming components.

Message queue

The message queue lets you publish and subscribe to a stream of events/records. There are various alternatives we can use as a message queue in our real-time stream architecture. For example, there is RabbitMQ, ActiveMQ, and Kafka. Out of these, Kafka has gained tremendous popularity due to its various unique features. Hence, we will discuss the architecture of Kafka in detail. A discussion of RabbitMQ and ActiveMQ is beyond the scope of this book.

So what is Kafka?