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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

HDFS

HDFS is the default storage filesystem in Hadoop, which is distributed, considerably simple in design and extremely scalable, flexible, and with high fault tolerance capability. HDFS architecture has a master-slave pattern due to which the slave nodes can be better managed and utilized. HDFS can even run on commodity hardware, and the architecture accepts that some nodes can be down and still data has to be recovered and processed. HDFS has self-healing processes and speculative execution, which make the system fault tolerant, and is flexible to add/remove nodes and increases the scalability with reliability. HDFS is designed to be best suited for MapReduce programming. One key assumption in HDFS is Moving Computation is Cheaper than Moving Data.

Features of HDFS

The important features of HDFS are as follows:

  • Scalability: HDFS is scalable to petabytes or even more. HDFS is flexible enough to add or remove nodes, which can achieve scalability.
  • Reliability and fault tolerance: HDFS replicates...
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