Table of Contents

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  1. Preface
  2. Introduction to Data Engineering Administration
  3. Authentication
  4. Running Mappings on a Cluster with Kerberos Authentication
  5. Authorization
  6. Cluster Configuration
  7. Cloud Provisioning Configuration
  8. Data Integration Service Processing
  9. Appendix A: Connections Reference
  10. Appendix B: Monitoring REST API

Authorization Overview

Authorization Overview

Authorization controls what a user can do on a Hadoop cluster. For example, a user must be authorized to submit jobs to the Hadoop cluster.
You can use the following systems to manage authorization for Data Engineering Integration:
HDFS permissions
By default, Hadoop uses HDFS permissions to determine what a user can do to a file or directory on HDFS. Additionally, Hadoop implements transparent data encryption in HDFS directories.
Apache Sentry
Sentry is a security plug-in that you can use to enforce role-based authorization for data and metadata on a Hadoop cluster. You can enable high availability for Sentry in the Hadoop cluster. Sentry can secure data and metadata at the table and column level. For example, Sentry can restrict access to columns that contain sensitive data and prevent unauthorized users from accessing the data.
Apache Ranger
Ranger is a security plug-in that you can use to authenticate users of a Hadoop cluster. Ranger manages access to files, folders, databases, tables, and columns. When you perform an action, Ranger verifies that the user meets the policy requirements and has the correct permissions on HDFS. You can enable high availability for Ranger in the Hadoop cluster.
Fine Grained Authorization
Fine grained authorization enables database administrators to impose column-level authorization on Hive tables and views. A more fine-grained level of authorization enables administrators to impose row and column level authorization. You can configure a Hive connection to observe fine grained authorization.

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