Compute access mode limitations for Unity Catalog
Databricks recommends using Unity Catalog and shared access mode for most workloads. This article outlines various limitations for each access mode with Unity Catalog. For details on access modes, see Access modes.
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 Where can init scripts be installed? and Cluster-scoped libraries.
Single user access mode limitations on Unity Catalog
Single user access mode on Unity Catalog has the following limitations. These are in addition to the general limitations for all Unity Catalog access mode. See General limitations for Unity Catalog.
Fine-grained access control limitations for Unity Catalog single user access mode
Dynamic views are not supported.
To read from a view, you must have
SELECT
on all referenced tables and views.You cannot access a table that has a row filter or column mask.
You cannot use a single user compute 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 compute using Databricks Runtime 13.3 LTS and above.
Streaming limitations for Unity Catalog single user access mode
- Asynchronous checkpointing is not supported in Databricks Runtime 11.3 LTS and below.
Shared access mode limitations on Unity Catalog
Shared access mode on Unity Catalog has the following limitations. These are in addition to the general limitations for all Unity Catalog access mode. See General limitations for Unity Catalog.
Databricks Runtime ML and Spark Machine Learning Library (MLlib) are not supported.
Spark-submit jobs are not supported.
On Databricks Runtime 13.3 and above, individual rows must not exceed the maximum size of 128MB.
When used with credential passthrough, Unity Catalog features are disabled.
Custom containers are not supported.
Language support for Unity Catalog shared access mode
- R is not supported.
- Scala is supported on Databricks Runtime 13.3 and above.
Spark API limitations for Unity Catalog shared access mode
- RDD APIs are not supported.
- DBUtils and other clients that directly read the data from cloud storage are only supported when you use an external location to access the storage location. See Create an external location to connect cloud storage to Azure Databricks.
- Spark Context (
sc
),spark.sparkContext
, andsqlContext
are not supported for Scala in any Databricks Runtime and are not supported for Python in Databricks Runtime 14.0 and above.- Databricks recommends using the
spark
variable to interact with theSparkSession
instance. - The following
sc
functions are also not supported:emptyRDD
,range
,init_batched_serializer
,parallelize
,pickleFile
,textFile
,wholeTextFiles
,binaryFiles
,binaryRecords
,sequenceFile
,newAPIHadoopFile
,newAPIHadoopRDD
,hadoopFile
,hadoopRDD
,union
,runJob
,setSystemProperty
,uiWebUrl
,stop
,setJobGroup
,setLocalProperty
,getConf
.
- Databricks recommends using the
UDF limitations for Unity Catalog shared access mode
User-defined functions (UDFs) have the following limitations with shared access mode:
Hive UDFs are not supported.
applyInPandas
andmapInPandas
are not supported in Databricks Runtime 14.2 and below.In Databricks Runtime 14.2 and above, Scala scalar UDFs are supported. Other Scala UDFs and UDAFs are not supported.
In Databricks Runtime 13.3 LTS and above, Python scalar UDFs and Pandas UDFs are supported. Other Python UDFs, including UDAFs, UDTFs, and Pandas on Spark are not supported.
See User-defined functions (UDFs) in Unity Catalog.
Streaming limitations for Unity Catalog shared access mode
Note
Some of the listed Kafka options have limited support when used for supported configurations on Azure Databricks. See Stream processing with Apache Kafka and Azure Databricks.
- For Scala,
foreach
,foreachBatch
,StreamingListeners
, andFlatMapGroupWithState
are not supported. - For Python,
foreachBatch
has new behavior in Databricks Runtime 14.0 and above. See Behavior changes for foreachBatch in Databricks Runtime 14.0. - For Scala,
from_avro
requires Databricks Runtime 14.2 or above. applyInPandasWithState
is not supported.- Working with socket sources is not supported.
- The
sourceArchiveDir
must be in the same external location as the source when you useoption("cleanSource", "archive")
with a data source managed by Unity Catalog. - For Kafka sources and sinks, the following options are unsupported:
kafka.sasl.client.callback.handler.class
kafka.sasl.login.callback.handler.class
kafka.sasl.login.class
kafka.partition.assignment.strategy
- The following Kafka options are supported in Databricks Runtime 13.3 LTS and above but unsupported in Databricks Runtime 12.2 LTS. You can only specify external locations managed by Unity Catalog for these options:
kafka.ssl.truststore.location
kafka.ssl.keystore.location
Network and file system access limitations for Unity Catalog shared access mode
Must run commands on compute nodes as a low-privilege user forbidden from accessing sensitive parts of the filesystem.
In Databricks Runtime 11.3 LTS and below, you can only create network connections to ports 80 and 443.
Cannot connect to the instance metadata service or Azure WireServer.
General limitations for Unity Catalog
The following limitations apply to all Unity Catalog-enabled access modes.
Streaming limitations for Unity Catalog
- 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.
See also Streaming limitations for Unity Catalog single user access mode and Streaming limitations for Unity Catalog shared access mode.
For more on streaming with Unity Catalog, see Using Unity Catalog with Structured Streaming.
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