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Modern Big Data Processing with Hadoop

You're reading from   Modern Big Data Processing with Hadoop Expert techniques for architecting end-to-end big data solutions to get valuable insights

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Product type Paperback
Published in Mar 2018
Publisher Packt
ISBN-13 9781787122765
Length 394 pages
Edition 1st Edition
Languages
Concepts
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Authors (3):
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Manoj R Patil Manoj R Patil
Author Profile Icon Manoj R Patil
Manoj R Patil
Prashant Shindgikar Prashant Shindgikar
Author Profile Icon Prashant Shindgikar
Prashant Shindgikar
V Naresh Kumar V Naresh Kumar
Author Profile Icon V Naresh Kumar
V Naresh Kumar
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Toc

Table of Contents (12) Chapters Close

Preface 1. Enterprise Data Architecture Principles FREE CHAPTER 2. Hadoop Life Cycle Management 3. Hadoop Design Consideration 4. Data Movement Techniques 5. Data Modeling in Hadoop 6. Designing Real-Time Streaming Data Pipelines 7. Large-Scale Data Processing Frameworks 8. Building Enterprise Search Platform 9. Designing Data Visualization Solutions 10. Developing Applications Using the Cloud 11. Production Hadoop Cluster Deployment

Data security

Data has become a very important asset for businesses when making very critical decisions. As the complexity of the infrastructure that generates and uses this data, its very important to have some control over the access patterns of this data. In the Hadoop ecosystem, we have Apache Ranger, which is another open source project that helps in managing the security of big data.

What is Apache Ranger?

Apache Ranger is an application that enables data architects to implement security policies on a big data ecosystem. The goal of this project is to provide a unified way for all Hadoop applications to adhere to the security guidelines that are defined.

Here are some of the features of Apache Ranger:

  • Centralized administration...
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