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)

Configuring HDFS high availability

Let's take a look at the changes brought about in Hadoop over time.

During Hadoop 1.x

Hadoop 1.x started with the architecture of a single NameNode. All DataNodes used to send their block reports to that single NameNode. There was a secondary NameNode in the architecture, but its sole responsibility was to merge all edits to FSImage. With this architecture, the NameNode became the single point of failure (SPOF). Since it has all the metadata of all the DataNodes of the Hadoop cluster, in the event of NameNode crash, the Hadoop cluster becomes unavailable till the next restart of NameNode repair. If the NameNode cannot be recovered, then all the data in all the DataNodes would be completely...