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
About the Author
About the Reviewers
Pillars of Hadoop – HDFS, MapReduce, and YARN

Flume architecture

Flume architecture is a very flexible and customizable composed agent that can be configured as multitiered for a data flow process. The data flow design allows the source or data to be transferred or processed from the source to the destination. The components are wired together in chains and in different tiers called the logical node's configuration. The logical nodes are configured in three tiers, namely, Client, Collector, and Storage. The first tier is the Client that captures the data from data source and forwards the it to the Collector, which consolidates the data after processing and sends it to the Storage tier.

The Flume process and the logical components are controlled by the Flume Master. The logical nodes are very flexible and can be added or deleted dynamically by the Master.

Multitier topology

In Flume, Agents can be configured to be a Client, Collector, or Storage. A Client Agent ingests the data from a data source and pushes it to another Agent, using an...