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Cloudera Administration Handbook

You're reading from   Cloudera Administration Handbook A complete, hands-on guide to building and maintaining large Apache Hadoop clusters using Cloudera Manager and CDH5

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Product type Paperback
Published in Jul 2014
Publisher Packt
ISBN-13 9781783558964
Length 254 pages
Edition 1st Edition
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Author (1):
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Rohit Menon Rohit Menon
Author Profile Icon Rohit Menon
Rohit Menon
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Table of Contents (11) Chapters Close

Preface 1. Getting Started with Apache Hadoop 2. HDFS and MapReduce FREE CHAPTER 3. Cloudera's Distribution Including Apache Hadoop 4. Exploring HDFS Federation and Its High Availability 5. Using Cloudera Manager 6. Implementing Security Using Kerberos 7. Managing an Apache Hadoop Cluster 8. Cluster Monitoring Using Events and Alerts 9. Configuring Backups Index

Components of Apache Hadoop

Apache Hadoop is composed of two core components. They are:

  • HDFS: The HDFS is responsible for the storage of files. It is the storage component of Apache Hadoop, which was designed and developed to handle large files efficiently. It is a distributed filesystem designed to work on a cluster and makes it easy to store large files by splitting the files into blocks and distributing them across multiple nodes redundantly. The users of HDFS need not worry about the underlying networking aspects, as HDFS takes care of it. HDFS is written in Java and is a filesystem that runs within the user space.
  • MapReduce: MapReduce is a programming model that was built from models found in the field of functional programming and distributed computing. In MapReduce, the task is broken down to two parts: map and reduce. All data in MapReduce flows in the form of key and value pairs, <key, value>. Mappers emit key and value pairs and the reducers receive them, work on them, and produce the final result. This model was specifically built to query/process the large volumes of data stored in HDFS.

We will be going through HDFS and MapReduce in depth in the next chapter.

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