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)

Summary

In this chapter, the main objective was to learn about various Hadoop design alternatives. We've learned a lot when it comes to the Hadoop cluster and its best practices for deployment in a typical production environment. We started with a basic understanding about Hadoop and we proceeded to Hadoop configuration, installation, and HDFS architecture. We also learned about various techniques for achieving HDFS high availability. We also looked into YARN architecture. Finally, we looked at various file formats and how to choose one based on your use case.

In the next chapter, we will see how to ingest data into a newly created Hadoop cluster.