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)

Other popular real-time data streaming frameworks

Apart from Apache Storm, there are quite a few other open source real-time data streaming frameworks. In this section, I will discuss in brief only open source non-commercial frameworks. But, at the end of this section, I will provide a few URLs for a few commercial vendor products that offer some very interesting features.

Kafka Streams API

Kafka Streams is a library for building streaming applications. Kafka Streams is a client library for building applications and microservices, where the input and output data are stored in Kafka Clusters. The Kafka Streams API transforms and enriches the data.

The following are the important features of the Kafka Streams API:

  • It is part...