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Mastering Hadoop

You're reading from   Mastering Hadoop Go beyond the basics and master the next generation of Hadoop data processing platforms

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Product type Paperback
Published in Dec 2014
Publisher
ISBN-13 9781783983643
Length 374 pages
Edition 1st Edition
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Author (1):
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Sandeep Karanth Sandeep Karanth
Author Profile Icon Sandeep Karanth
Sandeep Karanth
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Table of Contents (15) Chapters Close

Preface 1. Hadoop 2.X FREE CHAPTER 2. Advanced MapReduce 3. Advanced Pig 4. Advanced Hive 5. Serialization and Hadoop I/O 6. YARN – Bringing Other Paradigms to Hadoop 7. Storm on YARN – Low Latency Processing in Hadoop 8. Hadoop on the Cloud 9. HDFS Replacements 10. HDFS Federation 11. Hadoop Security 12. Analytics Using Hadoop A. Hadoop for Microsoft Windows Index

The security pillars

The four pillars of data security are as follows:

  • Authentication: This refers to challenging a system or user to prove their identity. Only authenticated identities are allowed to gain access into the data system. Authentication in Hadoop can be of two major kinds, simple authentication and pseudo-authentication. The former is a loose kind of security where trust is placed on the user's assertion about their identity. In the latter, systems such as Kerberos are used for authenticating a user. In the industry, the latter is recommended as a best practice. Hadoop even supports seamless integration with a number of user stores such as LDAP and Active Directory. With the help of these stores, Kerberos can be implemented as an authentication mechanism.
  • Authorization: Authorization refers to granting authenticated users access to data resources. In a multitenant system, or a multiteam organization sharing a single data cluster, policies, compliance, and regulatory norms...
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