Databricks Spark
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This integration enforces policies on Databricks securables registered in the legacy Hive metastore. Once these securables are registered as Immuta data sources, users can query policy-enforced data on Databricks clusters.
The guides in this section outline how to integrate Databricks Spark with Immuta.
This getting started guide outlines how to integrate Databricks with Immuta.
: Configure the Databricks Spark integration.
: Manually update your cluster to reflect changes in the Immuta init script or cluster policies.
: Register a Databricks library with Immuta as a trusted library to avoid Immuta security manager errors when using third-party libraries.
: Raise the caching on-cluster and lower the cache timeouts for the Immuta web service to allow use of project UDFs in Spark jobs.
: Run R and Scala spark-submit jobs on your Databricks cluster.
: Access DBFS in Databricks for non-sensitive data.
: Resolve errors in the Databricks Spark configuration.
: This guide describes the design and components of the integration.
: This guide provides an overview of the Immuta features that provide security for your users and Databricks clusters and that allow you to prove compliance and monitor for anomalies.
: This guide provides an overview of registering Databricks securables and protecting them with Immuta policies.
: This guide provides an overview of how Databricks users access data registered in Immuta.