Compute access mode limitations
Databricks recommends using Unity Catalog and shared access mode for most workloads. Limitations apply to all access mode configurations. This article outlines various limitations for each access mode, including additional limitations added by Unity Catalog.
Databricks recommends using compute policies to simplify configuration options for most users. See Create and manage compute policies.
Note
No-isolation shared is a legacy access mode that does not support Unity Catalog.
Important
Init scripts and libraries have different support across access modes and Databricks Runtime versions. See Compute compatibility with libraries and init scripts.
Cluster limitations for Unity Catalog
On Databricks Runtime 13.2 and below, Scala is supported only on clusters that use single user access mode. To use Scala on a cluster that uses shared access mode, the cluster must be on Databricks Runtime 13.3 or above.
Workloads that use Databricks Runtime for Machine Learning are supported only on clusters that use single user access mode.
R is supported only on clusters that use single user access mode.
Spark-submit jobs are supported on single user access but not shared clusters. See Access modes.
Single user access mode limitations on Unity Catalog
Single user access mode on Unity Catalog has the following limtiations:
To read from a view, you must have
SELECT
on all referenced tables and views.Dynamic views are not supported.
Cannot use a single user cluster to access a table that has a row filter or column mask.
When used with credential passthrough, Unity Catalog features are disabled.
Cannot use a single user cluster to query tables created by a Unity Catalog-enabled Delta Live Tables pipeline, including streaming tables and materialized views created in Databricks SQL. To query tables created by a Delta Live Tables pipeline, you must use a shared cluster using Databricks Runtime 13.1 and above.
Structured Streaming limitations on Unity Catalog-enabled compute
Support for Structured Streaming on Unity Catalog tables depends on the Databricks Runtime version that you are running and on whether you are using shared or single user access mode.
Single user limitations
Support for Single User access is available on Databricks Runtime 11.3 LTS and above, with the following limitations:
Apache Spark continuous processing mode is not supported. See Continuous Processing in the Spark Structured Streaming Programming Guide.
StreamingQueryListener
cannot use credentials or interact with objects managed by Unity Catalog.Asynchronous checkpointing is not supported in Databricks Runtime 11.3 LTS and below. It is supported in Databricks Runtime 12.0 and above.