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Hadoop Essentials

You're reading from   Hadoop Essentials Delve into the key concepts of Hadoop and get a thorough understanding of the Hadoop ecosystem

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Product type Paperback
Published in Apr 2015
Publisher Packt
ISBN-13 9781784396688
Length 194 pages
Edition 1st Edition
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Author (1):
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Shiva Achari Shiva Achari
Author Profile Icon Shiva Achari
Shiva Achari
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Table of Contents (9) Chapters Close

Preface 1. Introduction to Big Data and Hadoop FREE CHAPTER 2. Hadoop Ecosystem 3. Pillars of Hadoop – HDFS, MapReduce, and YARN 4. Data Access Components – Hive and Pig 5. Storage Component – HBase 6. Data Ingestion in Hadoop – Sqoop and Flume 7. Streaming and Real-time Analysis – Storm and Spark Index

Need of a data processing tool on Hadoop

MapReduce is the key to perform processing on Big Data, but it is complex to understand, design, code, and optimize. MapReduce has a high learning curve, which requires good programming skills to master. Usually Big Data users come from different backgrounds such as Programming, Database administrators, scripting, Analyst, Data science, Data Managers, and so on, and not all users can adapt to the programming model of MapReduce. Hence we have different abstractions for the data access components for Hadoop.

The data access components are very useful for developers as they may not need to learn MapReduce programming in detail and can still utilize the MapReduce framework in an interface in which they can be much more comfortable and can help in faster development and better manageability of the code. Abstractions can help ad hoc processing on data quickly and concentrate on the business logic.

The two widely used data access components in the Hadoop...

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