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Mastering Hadoop 3

You're reading from  Mastering Hadoop 3

Product type Book
Published in Feb 2019
Publisher Packt
ISBN-13 9781788620444
Pages 544 pages
Edition 1st Edition
Languages
Authors (2):
Chanchal Singh Chanchal Singh
Profile icon Chanchal Singh
Manish Kumar Manish Kumar
Profile icon Manish Kumar
View More author details

Table of Contents (23) Chapters

Title Page
Dedication
About Packt
Foreword
Contributors
Preface
Journey to Hadoop 3 Deep Dive into the Hadoop Distributed File System YARN Resource Management in Hadoop Internals of MapReduce SQL on Hadoop Real-Time Processing Engines Widely Used Hadoop Ecosystem Components Designing Applications in Hadoop Real-Time Stream Processing in Hadoop Machine Learning in Hadoop Hadoop in the Cloud Hadoop Cluster Profiling Who Can Do What in Hadoop Network and Data Security Monitoring Hadoop Other Books You May Enjoy Index

Defining HDFS


HDFS is designed to run on a cluster of commodity hardware. It is a fault-tolerant, scalable File System that handles the failure of nodes without data and can scale up horizontally to any number of nodes. The initial goal of HDFS was to serve large data files with high read and write performance.

The following are a few essentialfeatures of HDFS:

  • Fault tolerance: Downtime due to machine failure or data loss could result in a huge loss to a company; therefore, the companies want a highly available fault-tolerant system. HDFS is designed to handle failures and ensures data availability with corrective and preventive actions. Files stored in HDFS are split into small chunks and each chunk is referred to as a block. Each block is either 64 MB or 128 MB, depending on the configuration. Blocks are replicated across clusters based on the replication factor. This means that if the replication factor is three, then the block will be replicated to three machines. This assures that, if...
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