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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

Data sources


Due to the capability of processing variety of data and volume of data, data sources for Hadoop has increased and along with that the complexity has increased enormously. We now see huge amount of batch and streaming and real-time analysis processed in Hadoop, for which data ingestion can become a bottleneck or can break a system, if not designed according to the requirement.

Let's look at some of the data sources, which can produce enormous volume of data or consistent data continuously:

  • Data sensors: These are thousands of sensors, producing data continuously.

  • Machine Data: Produces data which should be processed in near real time for avoiding huge loss.

  • Telco Data: CDR data and other telecom data generates high volume of data.

  • Healthcare system data: Genes, images, ECR records are unstructured and complex to process.

  • Social Media: Facebook, Twitter, Google Plus, YouTube, and others get a huge volume of data.

  • Geological Data: Semiconductors and other geological data produce...

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