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

Data access components

MapReduce is a very powerful framework, but has a huge learning curve to master and optimize a MapReduce job. For analyzing data in a MapReduce paradigm, a lot of our time will be spent in coding. In big data, the users come from different backgrounds such as programming, scripting, EDW, DBA, analytics, and so on, for such users there are abstraction layers on top of MapReduce. Hive and Pig are two such layers, Hive has a SQL query-like interface and Pig has Pig Latin procedural language interface. Analyzing data on such layers becomes much easier.

We will cover the concept of Hive and Pig in greater detail in Chapter 4, Data Access Component – Hive and Pig.