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Privacera Platform

Privacera Plugin in Databricks
:
Databricks

Privacera provides two types of plugin solutions for access control in Databricks clusters. Both plugins are mutually exclusive and cannot be enabled on the same cluster.

Databricks Spark Fine-Grained Access Control (FGAC) Plugin

  • Recommended for SQL, Python, R language notebooks.

  • Provides FGAC on databases with row filtering and column masking features.

  • Uses privacera_hive, privacera_s3, privacera_adls, privacera_files services for resource-based access control, and privacera_tag service for tag-based access control.

  • Uses the plugin implementation from Privacera.

Databricks Spark Object Level Access Control (OLAC) Plugin

OLAC plugin was introduced to provide an alternative solution for Scala language clusters, since using Scala language on Databricks Spark has some security concerns.

  • Recommended for Scala language notebooks.

  • Provides OLAC on S3 locations which you are trying to access via Spark.

  • Uses privacera_s3 service for resource-based access control and privacera_tag service for tag-based access control.

  • Uses the signed-authorization implementation from Privacera.

Databricks cluster deployment matrix with Privacera plugin

Job/Workflow use-case for automated cluster:

Run-Now will create the new cluster based on the definition mentioned in the job description.

Table 55. 

Job Type  

Languages

FGAC/DBX version

OLAC/DBX Version

Notebook

Python/R/SQL

Supported [7.3, 9.1 , 10.4]

JAR

Java/Scala

Not supported

Supported[7.3, 9.1 , 10.4]

spark-submit

Java/Scala/Python

Not supported

Supported[7.3, 9.1 , 10.4]

Python

Python

Supported [7.3, 9.1 , 10.4]

Python wheel

Python

Supported [9.1 , 10.4]

Delta Live Tables pipeline

Not supported

Not supported



Job on existing cluster:

Run-Now will use the existing cluster which is mentioned in the job description.

Table 56. 

Job Type

Languages

FGAC/DBX version

OLAC

Notebook

Python/R/SQL

supported [7.3, 9.1 , 10.4]

Not supported

JAR

Java/Scala

Not supported

Not supported

spark-submit

Java/Scala/Python

Not supported

Not supported

Python

Python

Not supported

Not supported

Python wheel

Python

supported [9.1 , 10.4]

Not supported

Delta Live Tables pipeline

Not supported

Not supported



Interactive use-case

Interactive use-case is running a notebook of SQL/Python on an interactive cluster.

Table 57. 

Cluster Type

Languages

FGAC

OLAC

Standard clusters

Scala/Python/R/SQL

Not supported

Supported [7.3,9.1,10.4]

High Concurrency clusters

Python/R/SQL

Supported [7.3,9.1,10.4

Supported [7.3,9.1,10.4]

Single Node

Scala/Python/R/SQL

Not supported

Supported [7.3,9.1,10.4]