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  • Triggering an ephemeral override request
  • Configuring overrides in Immuta-enabled clusters

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  1. Configuration
  2. Connect Data Platforms
  3. Databricks
  4. Databricks Spark
  5. Reference Guides
  6. Databricks Spark Integration Configuration

Ephemeral Overrides

Last updated 3 months ago

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In the context of the Databricks Spark integration, Immuta uses the term ephemeral to describe data sources where the associated compute resources can vary over time. This means that the compute bound to these data sources is not fixed and can change. All Databricks data sources in Immuta are ephemeral.

Ephemeral overrides are specific to each data source and user. They effectively bind cluster compute resources to a data source for a given user. Immuta uses these overrides to determine which cluster compute to use when connecting to Databricks for various maintenance operations.

The operations that use the ephemeral overrides include

  • Visibility checks on the data source for a particular user. These checks assess how to apply row-level policies for specific users.

  • Stats collection triggered by a specific user.

  • Validating a custom WHERE clause policy against a data source. When owners or governors create custom WHERE clause policies, Immuta uses compute resources to validate the SQL in the policy. In this case, the ephemeral overrides for the user writing the policy are used to contact a cluster for SQL validation.

  • High cardinality column detection. Certain advanced policy types (e.g., minimization) in Immuta require a high cardinality column, and that column is computed on data source creation. It can be recomputed on demand and, if so, will use the ephemeral overrides for the user requesting computation.

Triggering an ephemeral override request

An ephemeral override request can be triggered when a user queries the securable corresponding to a data source in a Databricks cluster with the Spark plug-in configured. The actual triggering of this request depends on the .

Ephemeral overrides can also be set for a data source in the Immuta UI by navigating to the data source page, clicking on the data source actions button, and selecting Ephemeral overrides from the dropdown menu.

Ephemeral override requests made from a cluster for data sources and users where ephemeral overrides were set in the UI will not be successful.

If ephemeral overrides are never set (either through the user interface or the cluster configuration), the system will continue to use the connection details directly associated with the data source, which are set during .

Configuring overrides in Immuta-enabled clusters

Ephemeral overrides can be problematic in environments that have a dedicated cluster to handle maintenance activities, since ephemeral overrides can cause these operations to execute on a different cluster than the dedicated one.

To reduce the risk that a user has overrides set to a cluster (or multiple clusters) that aren't currently up, complete one of the following actions:

  • Direct all clusters' HTTP paths for overrides to a cluster dedicated for metadata queries using the .

  • Disable ephemeral overrides completely by setting the to false.

Ephemeral overrides best practices

  1. Disable ephemeral overrides for clusters when using multiple workspaces and dedicate a single cluster to serve queries from Immuta in a single workspace.

  2. If you use multiple E2 workspaces without disabling ephemeral overrides, avoid applying the where user row-level policy to data sources.

configuration settings
data source registration
IMMUTA_EPHEMERAL_HOST_OVERRIDE_HTTPPATH Spark environment variable
IMMTUA_EPHEMERAL_HOST_OVERRIDE Spark environment variable