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

YARN


YARN is Yet Another Resource Negotiator, the next generation compute and cluster management technology. YARN provides a platform to build/run multiple distributed applications in Hadoop. YARN was released in the Hadoop 2.0 version in 2012, marking a major change in Hadoop architecture. YARN took around 5 years to develop in an open community.

We discussed JobTracker being a single point of failure for MapReduce, and considering Hadoop is designed to run even in commodity servers, there is a good probability that the JobTracker can fail. JobTracker has two important functions: resource management, and job scheduling and monitoring.

YARN delegates and splits up the responsibility into separate daemons and achieves better performance and fault tolerance. Because of YARN, Hadoop, which could work only as a batch process, can now be designed to process interactive and real-time processing systems. This is a huge advantage as many systems, machines, sensors, and other sources generate huge...