Book Image

Hadoop Essentials

By : Shiva Achari
Book Image

Hadoop Essentials

By: Shiva Achari

Overview of this book

This book jumps into the world of Hadoop and its tools, to help you learn how to use them effectively to optimize and improve the way you handle Big Data. Starting with the fundamentals Hadoop YARN, MapReduce, HDFS, and other vital elements in the Hadoop ecosystem, you will soon learn many exciting topics such as MapReduce patterns, data management, and real-time data analysis using Hadoop. You will also explore a number of the leading data processing tools including Hive and Pig, and learn how to use Sqoop and Flume, two of the most powerful technologies used for data ingestion. With further guidance on data streaming and real-time analytics with Storm and Spark, Hadoop Essentials is a reliable and relevant resource for anyone who understands the difficulties - and opportunities - presented by Big Data today. With this guide, you'll develop your confidence with Hadoop, and be able to use the knowledge and skills you learn to successfully harness its unparalleled capabilities.
Table of Contents (15 chapters)
Hadoop Essentials
Credits
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
3
Pillars of Hadoop – HDFS, MapReduce, and YARN
Index

Distributed filesystem


In Hadoop, we know that data is stored in a distributed computing environment, so the files are scattered across the cluster. We should have an efficient filesystem to manage the files in Hadoop. The filesystem used in Hadoop is HDFS, elaborated as Hadoop Distributed File System.

HDFS

HDFS is extremely scalable and fault tolerant. It is designed to efficiently process parallel processing in a distributed environment in even commodity hardware. HDFS has daemon processes in Hadoop, which manage the data. The processes are NameNode, DataNode, BackupNode, and Checkpoint NameNode.

We will discuss HDFS elaborately in the next chapter.