> For the complete documentation index, see [llms.txt](https://documentation.immuta.com/2024.3/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://documentation.immuta.com/2024.3/integrations/databricks-spark/reference-guides/configuration-settings/cluster-policies/scala.md).

# Scala

{% hint style="info" %}
**Scala clusters**: This configuration is for Scala-only clusters.
{% endhint %}

Where Scala language support is needed, this configuration can be used in the Custom [access mode](https://docs.databricks.com/clusters/cluster-ui-preview.html).

According to Databricks’ cluster type support documentation, Scala clusters are intended for [single users only](https://docs.databricks.com/clusters/configure.html#standard-clusters). However, nothing inherently prevents a Scala cluster from being configured for multiple users. Even with the Immuta SecurityManager enabled, there are limitations to user isolation within a Scala job.

For a secure configuration, it is recommended that clusters intended for Scala workloads are limited to Scala jobs only and are made homogeneous through the use of [project equalization](/2024.3/integrations/databricks-spark/reference-guides/configuration-settings/scala-security.md) or externally via convention/cluster ACLs. (In homogeneous clusters, all users are at the same level of groups/authorizations; this is enforced externally, rather than directly by Immuta.)

For full details on Databricks’ best practices in configuring clusters, read their [governance documentation](https://docs.databricks.com/security/data-governance.html).


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