"Create external Hive function is not supported in Unity Catalog" when registering Hive UDFs

[FRG96]

I have enabled Unity Catalog in my AWS Databricks workspace, switching from the standard Hive Metastore. I have a few custom Hive UDFs in a JAR file that I have copied to /databricks/jars/ folder through init script. I want to be able to register those UDFs as permanent functions in Unity Catalog database using CREATE FUNCTION SQL Query in Notebook.

But when I do so, I get this error:

com.databricks.backend.common.rpc.SparkDriverExceptions$SQLExecutionException: org.apache.spark.sql.AnalysisException: [UC_COMMAND_NOT_SUPPORTED] Create external Hive function is not supported in Unity Catalog.
    at com.databricks.sql.managedcatalog.ManagedCatalogErrors$.operationNotSupportedException(ManagedCatalogErrors.scala:50)
    at com.databricks.sql.managedcatalog.ManagedCatalogSessionCatalog.rejectOperationsForUnityCatalog(ManagedCatalogSessionCatalog.scala:288)
    at com.databricks.sql.managedcatalog.ManagedCatalogSessionCatalog.rejectOperationsForUnityCatalog(ManagedCatalogSessionCatalog.scala:294)
    at com.databricks.sql.managedcatalog.ManagedCatalogSessionCatalog.createFunction(ManagedCatalogSessionCatalog.scala:1633)
    at org.apache.spark.sql.execution.command.CreateFunctionCommand.run(functions.scala:95)
    at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:80)
    at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:78)
    at org.apache.spark.sql.execution.command.ExecutedCommandExec.executeCollect(commands.scala:89)
    at org.apache.spark.sql.execution.QueryExecution$$anonfun$$nestedInanonfun$eagerlyExecuteCommands$1$1.$anonfun$applyOrElse$2(QueryExecution.scala:241)
    at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withCustomExecutionEnv$8(SQLExecution.scala:243)
    at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:392)
    at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withCustomExecutionEnv$1(SQLExecution.scala:188)
    at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:985)
    at org.apache.spark.sql.execution.SQLExecution$.withCustomExecutionEnv(SQLExecution.scala:142)
    at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:342)
    at org.apache.spark.sql.execution.QueryExecution$$anonfun$$nestedInanonfun$eagerlyExecuteCommands$1$1.$anonfun$applyOrElse$1(QueryExecution.scala:241)
    at org.apache.spark.sql.execution.QueryExecution.org$apache$spark$sql$execution$QueryExecution$$withMVTagsIfNecessary(QueryExecution.scala:226)
    at org.apache.spark.sql.execution.QueryExecution$$anonfun$$nestedInanonfun$eagerlyExecuteCommands$1$1.applyOrElse(QueryExecution.scala:239)
    at org.apache.spark.sql.execution.QueryExecution$$anonfun$$nestedInanonfun$eagerlyExecuteCommands$1$1.applyOrElse(QueryExecution.scala:232)
    at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$1(TreeNode.scala:512)
    at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:99)
    at org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:512)
    at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:31)
    at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:268)
    at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:264)
    at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:31)
    at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:31)
    at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:488)
    at org.apache.spark.sql.execution.QueryExecution.$anonfun$eagerlyExecuteCommands$1(QueryExecution.scala:232)
    at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$.allowInvokingTransformsInAnalyzer(AnalysisHelper.scala:324)
    at org.apache.spark.sql.execution.QueryExecution.eagerlyExecuteCommands(QueryExecution.scala:232)
    at org.apache.spark.sql.execution.QueryExecution.commandExecuted$lzycompute(QueryExecution.scala:186)
    at org.apache.spark.sql.execution.QueryExecution.commandExecuted(QueryExecution.scala:177)
    at org.apache.spark.sql.Dataset.<init>(Dataset.scala:238)
    at org.apache.spark.sql.Dataset$.$anonfun$ofRows$2(Dataset.scala:107)
    at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:985)
    at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:104)
    at org.apache.spark.sql.SparkSession.$anonfun$sql$1(SparkSession.scala:820)
    at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:985)
    at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:815)
    at org.apache.spark.sql.SQLContext.sql(SQLContext.scala:695)
    at com.databricks.backend.daemon.driver.SQLDriverLocal.$anonfun$executeSql$1(SQLDriverLocal.scala:91)
    at scala.collection.immutable.List.map(List.scala:293)
    at com.databricks.backend.daemon.driver.SQLDriverLocal.executeSql(SQLDriverLocal.scala:37)
    at com.databricks.backend.daemon.driver.SQLDriverLocal.repl(SQLDriverLocal.scala:145)
    at com.databricks.backend.daemon.driver.DriverLocal.$anonfun$execute$23(DriverLocal.scala:728)
    at com.databricks.unity.UCSEphemeralState$Handle.runWith(UCSEphemeralState.scala:41)
    at com.databricks.unity.HandleImpl.runWith(UCSHandle.scala:99)
    at com.databricks.backend.daemon.driver.DriverLocal.$anonfun$execute$20(DriverLocal.scala:711)
    at com.databricks.logging.UsageLogging.$anonfun$withAttributionContext$1(UsageLogging.scala:398)
    at scala.util.DynamicVariable.withValue(DynamicVariable.scala:62)
    at com.databricks.logging.AttributionContext$.withValue(AttributionContext.scala:147)
    at com.databricks.logging.UsageLogging.withAttributionContext(UsageLogging.scala:396)
    at com.databricks.logging.UsageLogging.withAttributionContext$(UsageLogging.scala:393)
    at com.databricks.backend.daemon.driver.DriverLocal.withAttributionContext(DriverLocal.scala:62)
    at com.databricks.logging.UsageLogging.withAttributionTags(UsageLogging.scala:441)
    at com.databricks.logging.UsageLogging.withAttributionTags$(UsageLogging.scala:426)
    at com.databricks.backend.daemon.driver.DriverLocal.withAttributionTags(DriverLocal.scala:62)
    at com.databricks.backend.daemon.driver.DriverLocal.execute(DriverLocal.scala:688)
    at com.databricks.backend.daemon.driver.DriverWrapper.$anonfun$tryExecutingCommand$1(DriverWrapper.scala:622)
    at scala.util.Try$.apply(Try.scala:213)
    at com.databricks.backend.daemon.driver.DriverWrapper.tryExecutingCommand(DriverWrapper.scala:614)
    at com.databricks.backend.daemon.driver.DriverWrapper.executeCommandAndGetError(DriverWrapper.scala:533)
    at com.databricks.backend.daemon.driver.DriverWrapper.executeCommand(DriverWrapper.scala:568)
    at com.databricks.backend.daemon.driver.DriverWrapper.runInnerLoop(DriverWrapper.scala:438)
    at com.databricks.backend.daemon.driver.DriverWrapper.runInner(DriverWrapper.scala:381)
    at com.databricks.backend.daemon.driver.DriverWrapper.run(DriverWrapper.scala:232)
    at java.lang.Thread.run(Thread.java:750)

[Debayan]

Hi, Custom UDFs are not yet supported in Unity Catalog.

[FRG96]

Oh. Is this info officially documented somewhere in the Databricks documentation for Unity Catalog?

Also, will there be any issue if I register the UDFs as temporary functions?

[jose_gonzalez]

According to the docs from here https://docs.databricks.com/data-governance/unity-catalog/index.html

• Python UDF support on shared clusters is supported in Private Preview. Contact your account team for access.

[Anonymous]

Hi @Franklin George​ 

Hope everything is going great.

Just wanted to check in if you were able to resolve your issue. If yes, would you be happy to mark an answer as best so that other members can find the solution more quickly? If not, please tell us so we can help you. 

Cheers!