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

Apache Flume


Flume is extremely popular data ingestion system, which can be used to ingest data from different multiple sources and can put it in multiple destinations. Flume provides a framework to handle and process data on a larger scale, and it is very reliable.

Flume is usually described as distributed, reliable, scalable, manageable, and customizable to ingest and process data from different multiple data sources to multiple destinations.

As we already discussed about the different type of data sources. One thing which makes the design more difficult is that data formats changes frequently in some cases especially social media data in JSON, and usually a Big Data systems has multiple data sources. Flume is extremely efficient in handling such scenarios and provides a greater control over each data source and the processing layer. Flume can be configured in three modes: single node, pseudo-distributed, and fully-distributed mode.

Flume is adapted due to its capability to be highly reliable...