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2024.2
  • Immuta Documentation - 2024.2
  • What is Immuta?
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        • Configure a Snowflake Integration
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      • Phased Snowflake Onboarding Concept Guide
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      • Getting Started
      • How-to Guides
        • Configure a Databricks Unity Catalog Integration
        • Migrate to Unity Catalog
      • Databricks Unity Catalog Integration Reference Guide
    • Databricks Spark
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        • Configuration
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            • Python & SQL
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        • Databricks Change Data Feed
        • Databricks Libraries Introduction
        • Delta Lake API
        • Spark Direct File Reads
        • Databricks Metastore Magic
    • Starburst (Trino)
      • Getting Started
      • How-to Guides
        • Configure Starburst (Trino) Integration
        • Customize Read and Write Access Policies for Starburst (Trino)
      • Starburst (Trino) Integration Reference Guide
    • Redshift
      • Getting Started
      • How-to Guides
        • Configure Redshift Integration
        • Configure Redshift Spectrum
      • Reference Guides
        • Redshift Integration
        • Redshift Pre-Configuration Details
    • Azure Synapse Analytics
      • Getting Started
      • Configure Azure Synapse Analytics Integration
      • Reference Guides
        • Azure Synapse Analytics Integration
        • Azure Synapse Analytics Pre-Configuration Details
    • Amazon S3
    • Google BigQuery
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      • Securing Hive and Impala Without Sentry
      • Enabling ImmutaGroupsMapping
    • Registering Metadata
      • Data Sources in Immuta
      • Register Data Sources
        • Create a Data Source
        • Create an Amazon S3 Data Source
        • Create a Google BigQuery Data Source
        • Bulk Create Snowflake Data Sources
      • Data Source Settings
        • How-to Guides
          • Manage Data Sources and Data Source Settings
          • Manage Data Source Members
          • Manage Access Requests and Tasks
          • Manage Data Dictionary Descriptions
          • Disable Immuta from Sampling Raw Data
        • Data Source Health Checks Reference Guide
      • Schema Monitoring
        • How-to Guides
          • Run Schema Monitoring and Column Detection Jobs
          • Manage Schema Monitoring
        • Reference Guides
          • Schema Monitoring
          • Schema Projects
        • Why Use Schema Monitoring?
    • Catalogs
      • Getting Started with External Catalogs
      • Configure an External Catalog
      • Reference Guides
        • External Catalogs
        • Custom REST Catalogs
          • Custom REST Catalog Interface Endpoints
    • Tags
      • How-to Guides
        • Create and Manage Tags
        • Add Tags to Data Sources and Projects
      • Tags Reference Guide
  • People
    • Getting Started
    • Identity Managers (IAMs)
      • How-to Guides
        • Microsoft Entra ID
        • Okta LDAP Interface
        • Okta and OpenID Connect
        • Integrate Okta SAML SCIM with Immuta
        • OneLogin with OpenID
        • Configure SAML IAM Protocol
      • Reference Guides
        • Identity Managers
        • SAML Single Logout
        • SAML Protocol Configuration Options
    • Immuta Users
      • How-to Guides
        • Managing Personas and Permissions
        • Manage Attributes and Groups
        • User Impersonation
        • External User ID Mapping
        • External User Info Endpoint
      • Reference Guides
        • Attributes and Groups in Immuta
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  • Discover Your Data
    • Getting Started
    • Introduction
    • Architecture
    • Data Discovery
      • How-to Guides
        • Enable Sensitive Data Discovery (SDD)
        • Manage Identification Frameworks
        • Manage Patterns
        • Manage Rules
        • Manage SDD on Data Sources
        • Manage Global SDD Settings
        • Migrate From Legacy to Native SDD
      • Reference Guides
        • How Competitive Pattern Analysis Works
        • Built-in Pattern Reference
        • Built-in Discovered Tags Reference
    • Data Classification
      • How-to Guides
        • Activate Classification Frameworks
        • Adjust Identification and Classification Framework Tags
        • How to Use a Built-In Classification Framework with Your Own Tags
      • Built-in Classification Frameworks Reference Guide
  • Detect Your Activity
    • Getting Started
      • Monitor and Secure Sensitive Data Platform Query Activity
        • User Identity Best Practices
        • Integration Architecture
        • Snowflake Roles Best Practices
        • Register Data Sources
        • Automate Entity and Sensitivity Discovery
        • Detect with Discover: Onboarding Guide
        • Using Immuta Detect
      • General Immuta Configuration
        • User Identity Best Practices
        • Integration Architecture
        • Databricks Roles Best Practices
        • Register Data Sources
    • Introduction
    • Audit
      • How-to Guides
        • Export Audit Logs to S3
        • Export Audit Logs to ADLS
        • Run Governance Reports
      • Reference Guides
        • Universal Audit Model (UAM)
        • Snowflake Query Audit Logs
        • Databricks Unity Catalog Audit Logs
        • Databricks Query Audit Logs
        • Starburst (Trino) Query Audit Logs
        • UAM Schema
        • Audit Export CLI
        • Governance Report Types
      • Deprecated Audit Guides
        • Legacy to UAM Migration
        • Download Audit Logs
        • System Audit Logs
    • Detection
      • Use the Detect Dashboards
      • Reference Guides
        • Detect
        • Detect Dashboards
        • Unknown Users in Audit Logs
    • Monitors
      • Manage Monitors and Observations
      • Detect Monitors Reference Guide
  • Secure Your Data
    • Getting Started with Secure
      • Automate Data Access Control Decisions
        • The Two Paths: Orchestrated RBAC and ABAC
        • Managing User Metadata
        • Managing Data Metadata
        • Author Policy
        • Test and Deploy Policy
      • Compliantly Open More Sensitive Data for ML and Analytics
        • Managing User Metadata
        • Managing Data Metadata
        • Author Policy
      • Federated Governance for Data Mesh and Self-Serve Data Access
        • Defining Domains
        • Managing Data Products
        • Managing Data Metadata
        • Apply Federated Governance
        • Discover and Subscribe to Data Products
    • Introduction
      • Scalability and Evolvability
      • Understandability
      • Distributed Stewardship
      • Consistency
      • Availability of Data
    • Authoring Policies in Secure
      • Authoring Policies at Scale
      • Data Engineering with Limited Policy Downtime
      • Subscription Policies
        • How-to Guides
          • Author a Subscription Policy
          • Author an ABAC Subscription Policy
          • Subscription Policies Advanced DSL Guide
          • Author a Restricted Subscription Policy
          • Clone, Activate, or Stage a Global Policy
        • Reference Guides
          • Subscription Policies
          • Subscription Policy Access Types
          • Advanced Use of Special Functions
      • Data Policies
        • Overview
        • How-to Guides
          • Author a Masking Data Policy
          • Author a Minimization Policy
          • Author a Purpose-Based Restriction Policy
          • Author a Restricted Data Policy
          • Author a Row-Level Policy
          • Author a Time-Based Restriction Policy
          • Certifications Exemptions and Diffs
          • External Masking Interface
        • Reference Guides
          • Data Policy Types
          • Masking Policies
          • Row-Level Policies
          • Custom WHERE Clause Functions
          • Data Policy Conflicts and Fallback
          • Custom Data Policy Certifications
          • Orchestrated Masking Policies
    • Domains
      • Getting Started with Domains
      • Domains Reference Guide
    • Projects and Purpose-Based Access Control
      • Projects and Purpose Controls
        • Getting Started
        • How-to Guides
          • Create a Project
          • Create and Manage Purposes
          • Adjust a Policy
          • Project Management
            • Manage Projects and Project Settings
            • Manage Project Data Sources
            • Manage Project Members
        • Reference Guides
          • Projects and Purposes
          • Policy Adjustments
        • Why Use Purposes?
      • Equalized Access
        • Manage Project Equalization
        • Project Equalization Reference Guide
        • Why Use Project Equalization?
      • Masked Joins
        • Enable Masked Joins
        • Why Use Masked Joins?
      • Writing to Projects
        • How-to Guides
          • Create and Manage Snowflake Project Workspaces
          • Create and Manage Databricks Project Workspaces
          • Write Data to the Workspace
        • Reference Guides
          • Project Workspaces
          • Project UDFs (Databricks)
    • Data Consumers
      • Subscribe to a Data Source
      • Query Data
        • Querying Snowflake Data
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        • Querying Starburst (Trino) Data
        • Querying Redshift Data
        • Querying Azure Synapse Analytics Data
      • Subscribe to Projects
  • Application Settings
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      • BI Tools
        • BI Tool Configuration Recommendations
        • Power BI Configuration Example
        • Tableau Configuration Example
      • Add a License Key
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      • Manage Encryption Keys
      • System Status Bundle
    • Reference Guides
      • Data Processing, Encryption, and Masking Practices
      • Metadata Ingestion
  • Releases
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    • Immuta Release Lifecycle
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    • Immuta Support Matrix Overview
    • Immuta CLI Release Notes
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    • The Immuta CLI
      • Install and Configure the Immuta CLI
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        • Manage Sensitive Data Discovery Rules
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    • The Immuta API
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          • Configure an Amazon S3 Integration
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      • Immuta V2 API
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      • Immuta V1 API
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          • Get Fingerprint Status
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          • Manage the Data Dictionary
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            • Write Policies Payloads and Response Schema Reference Guide
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        • Subscribe to and Manage Data Sources
        • Manage Projects and Purposes
          • Manage Projects
          • Manage Purposes
        • Generate Governance Reports
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  • 2024.3

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On this page
  • Feature Availability
  • Supported Databricks Cluster Configurations
  • Databricks-Specific Details
  • Prerequisites
  • Supported Databricks Runtime Versions
  • Supported Databricks Cluster Types
  • Supported Access Mode and Languages
  • Supported Features
  • Workspaces
  • Tag Ingestion
  • User Impersonation
  • Query Audit
  • Multiple Databricks Instances
  • Limitation

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  1. Data and Integrations
  2. Databricks Spark
  3. Reference Guides

Databricks Spark Pre-Configuration Details

PreviousDatabricks Spark IntegrationNextConfiguration Settings

Last updated 2 months ago

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This page describes the Databricks integration, configuration options, and features. See the for a tutorial on enabling Databricks and these features through the App Settings page.

Feature Availability

Supported Databricks Cluster Configurations

The table below outlines the integrations supported for various Databricks cluster configurations. For example, the only integration available to enforce policies on a cluster configured to run on Databricks Runtime 9.1 is the Databricks Spark integration.

Example cluster
Databricks Runtime
Unity Catalog in Databricks
Databricks Spark integration
Databricks Unity Catalog integration

Cluster 1

9.1

Unavailable

Unavailable

Cluster 2

10.4

Unavailable

Unavailable

Cluster 3

11.3

Unavailable

Cluster 4

11.3

Cluster 5

11.3

Legend:

  • The feature or integration is enabled.

  • The feature or integration is disabled.

Databricks-Specific Details

Prerequisites

  • Databricks instance has network level access to Immuta tenant

  • Permissions and access to download (outside Internet access) or transfer files to the host machine

Recommended Databricks Workspace Configurations:

Supported Databricks Runtime Versions

Supported Databricks Cluster Types

Supported Access Mode and Languages

Immuta supports the Custom access mode.

  • Supported Languages:

    • Python

    • SQL

    • R (requires advanced configuration; work with your Immuta support professional to use R)

    • Scala (requires advanced configuration; work with your Immuta support professional to use Scala)

Supported Features

The Immuta Databricks integration supports the following Databricks features:

Workspaces

Tag Ingestion

User Impersonation

Query Audit

Audit limitations

Capturing the code or query that triggers the Spark plan makes audit records more useful in assessing what users are doing.

Multiple Databricks Instances

A user can configure multiple integrations of Databricks to a single Immuta tenant and use them dynamically or with workspaces.

Limitation

Immuta does not support Databricks clusters with Photon acceleration enabled.

/

Databricks instance: Premium tier workspace and

Note: Azure Databricks authenticates users with Microsoft Entra ID. Be sure to configure your Immuta tenant with an IAM that uses the same user ID as does Microsoft Entra ID. Immuta's Spark security plugin will look to match this user ID between the two systems. See this for details.

See for a list of Databricks Runtimes Immuta supports.

: Databricks users can see the on queried tables if they are allowed to read raw data and meet specific qualifications.

: Users can register their Databricks Libraries with Immuta as trusted libraries, allowing Databricks cluster administrators to avoid Immuta security manager errors when using third-party libraries.

: Immuta supports the use of external metastores in local or remote mode.

: In addition to supporting direct file reads through workspace and scratch paths, Immuta allows direct file reads in Spark for file paths.

Users can have additional write access in their integration using project workspaces. Users can integrate a single or multiple workspaces with a single Immuta tenant. For more details, see the page.

The Immuta Databricks integration cannot ingest tags from Databricks, but you can connect any of these to work with your integration.

Impersonation allows users to query data as another Immuta user. To enable user impersonation, see the page.

Immuta will audit queries that come from interactive notebooks, notebook jobs, and JDBC connections, but will not audit . Furthermore, Immuta only audits Spark jobs that are associated with Immuta tables. Consequently, Immuta will not audit a query in a notebook cell that does not trigger a Spark job, unless immuta.spark.audit.all.queries is set to true; for more details about this configuration and auditing all queries in Databricks, see .

To audit the code or query that triggers the Spark plan, Immuta hooks into Databricks where notebook cells and JDBC queries execute and saves the cell or query text. Then, Immuta pulls this information into the audits of the resulting Spark jobs. Examples of a saved cell/query and the resulting audit record are provided on the page.

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Databricks integration page
Cluster access control enabled
Workspace access control enabled
Personal access tokens enabled
Microsoft Entra ID page
All-purpose (interactive) clusters
Job clusters
Change Data Feed
Databricks Change Data Feed
Databricks Libraries
External Metastores
Spark Direct File Reads
Databricks Project Workspaces
User Impersonation
Databricks query audit logs
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✅
✅
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✅
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✅
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Project Workspaces
Databricks Tag Ingestion
User Impersonation
Query Audit
Multiple Integrations
Scala or R submit jobs
supported external catalogs
this page
Limited Enforcement in Databricks