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

HDFS


HDFS is the default storage filesystem in Hadoop, which is distributed, considerably simple in design and extremely scalable, flexible, and with high fault tolerance capability. HDFS architecture has a master-slave pattern due to which the slave nodes can be better managed and utilized. HDFS can even run on commodity hardware, and the architecture accepts that some nodes can be down and still data has to be recovered and processed. HDFS has self-healing processes and speculative execution, which make the system fault tolerant, and is flexible to add/remove nodes and increases the scalability with reliability. HDFS is designed to be best suited for MapReduce programming. One key assumption in HDFS is Moving Computation is Cheaper than Moving Data.

Features of HDFS

The important features of HDFS are as follows:

  • Scalability: HDFS is scalable to petabytes or even more. HDFS is flexible enough to add or remove nodes, which can achieve scalability.

  • Reliability and fault tolerance: HDFS replicates...