Book Image

Mastering Hadoop 3

By : Chanchal Singh, Manish Kumar
Book Image

Mastering Hadoop 3

By: Chanchal Singh, Manish Kumar

Overview of this book

Apache Hadoop is one of the most popular big data solutions for distributed storage and for processing large chunks of data. With Hadoop 3, Apache promises to provide a high-performance, more fault-tolerant, and highly efficient big data processing platform, with a focus on improved scalability and increased efficiency. With this guide, you’ll understand advanced concepts of the Hadoop ecosystem tool. You’ll learn how Hadoop works internally, study advanced concepts of different ecosystem tools, discover solutions to real-world use cases, and understand how to secure your cluster. It will then walk you through HDFS, YARN, MapReduce, and Hadoop 3 concepts. You’ll be able to address common challenges like using Kafka efficiently, designing low latency, reliable message delivery Kafka systems, and handling high data volumes. As you advance, you’ll discover how to address major challenges when building an enterprise-grade messaging system, and how to use different stream processing systems along with Kafka to fulfil your enterprise goals. By the end of this book, you’ll have a complete understanding of how components in the Hadoop ecosystem are effectively integrated to implement a fast and reliable data pipeline, and you’ll be equipped to tackle a range of real-world problems in data pipelines.
Table of Contents (23 chapters)
Title Page
Dedication
About Packt
Foreword
Contributors
Preface
Index

Data management


We discussed HDFS blocks and replication in the previous sections. NameNode stores all metadata information and is a single point of failure, which means that no one can use HDFS if NameNode is down. This metadata information is important and can be used to restart NameNode on other machines. Thus, it is important to take multiple backup copies of a metadata file so that, even if metadata is lost from the primary NameNode, the backup copy can be used to restart the NameNode on the same machine or another machine. In this section, we will discuss NameNode metadata files such as fsimage and edit log. We will discuss data integrity further by using checksum and taking snapshots of the directory to avoid data loss and modification. 

Metadata management

HDFS stores a large amount of structured and unstructured data in various formats. While the data is continuously growing to terabytes and petabytes, and your data is being used by Hadoop, you are likely to come across questions...