I would like to dedicate this book to my family, especially my father, mother, and wife. My father is my role model and I cannot find words to thank him enough, and I'm missing him as he passed away last year. My wife and mother have supported me throughout my life. I'd also like to dedicate this book to a special one whom we are expecting this July. Packt Publishing has been very kind and supportive, and I would like to thank all the individuals who were involved in editing, reviewing, and publishing this book. Some of the content was taken from my experiences, research, studies, and from the audiences of some of my trainings. I would like to thank my audience who found the book worth reading and hope that you gain the knowledge and help and implement them in your projects.
Hadoop Essentials
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Hadoop Essentials
By:
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.
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Table of Contents (15 chapters)
Hadoop Essentials
Credits
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
Free Chapter
Introduction to Big Data and Hadoop
Hadoop Ecosystem
Pillars of Hadoop – HDFS, MapReduce, and YARN
Data Access Components – Hive and Pig
Storage Component – HBase
Data Ingestion in Hadoop – Sqoop and Flume
Streaming and Real-time Analysis – Storm and Spark
Index
Customer Reviews