我们在 VNet 中使用 Azure Databricks 和单节点群集（运行时版本 10.4 LTS）。我们还需要使用自定义/私有 python 模块（wheel）。
在集群上安装库后，一切正常，但在集群重新启动并安装库后，执行任何单元时都会出现以下错误（取消/重新附加不能解决问题）：
+ Failure starting repl. Try detaching and re-attaching the notebook.
java.lang.Exception: org.apache.hadoop.hive.ql.metadata.HiveException: java.lang.RuntimeException: Unable to instantiate org.apache.hadoop.hive.metastore.HiveMetaStoreClient
at org.apache.spark.sql.hive.HiveExternalCatalog.$anonfun$withClient$2(HiveExternalCatalog.scala:160)
at org.apache.spark.sql.hive.HiveExternalCatalog.maybeSynchronized(HiveExternalCatalog.scala:112)
at org.apache.spark.sql.hive.HiveExternalCatalog.$anonfun$withClient$1(HiveExternalCatalog.scala:150)
at com.databricks.backend.daemon.driver.ProgressReporter$.withStatusCode(ProgressReporter.scala:364)
at com.databricks.spark.util.SparkDatabricksProgressReporter$.withStatusCode(ProgressReporter.scala:34)
at org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:149)
at org.apache.spark.sql.hive.HiveExternalCatalog.databaseExists(HiveExternalCatalog.scala:300)
at org.apache.spark.sql.internal.SharedState.externalCatalog$lzycompute(SharedState.scala:201)
at org.apache.spark.sql.internal.SharedState.externalCatalog(SharedState.scala:192)
at org.apache.spark.sql.hive.HiveSessionStateBuilder.externalCatalog(HiveSessionStateBuilder.scala:59)
at org.apache.spark.sql.hive.HiveSessionStateBuilder.$anonfun$resourceLoader$1(HiveSessionStateBuilder.scala:66)
at org.apache.spark.sql.hive.HiveSessionResourceLoader.client$lzycompute(HiveSessionStateBuilder.scala:160)
at org.apache.spark.sql.hive.HiveSessionResourceLoader.client(HiveSessionStateBuilder.scala:160)
at org.apache.spark.sql.hive.HiveSessionResourceLoader.$anonfun$addJar$1(HiveSessionStateBuilder.scala:164)
at org.apache.spark.sql.hive.HiveSessionResourceLoader.$anonfun$addJar$1$adapted(HiveSessionStateBuilder.scala:163)
at scala.collection.immutable.List.foreach(List.scala:431)
at org.apache.spark.sql.hive.HiveSessionResourceLoader.addJar(HiveSessionStateBuilder.scala:163)
at org.apache.spark.sql.execution.command.AddJarsCommand.$anonfun$run$1(resources.scala:33)
at org.apache.spark.sql.execution.command.AddJarsCommand.$anonfun$run$1$adapted(resources.scala:33)
at scala.collection.immutable.Stream.foreach(Stream.scala:533)
at org.apache.spark.sql.execution.command.AddJarsCommand.run(resources.scala:33)
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$1(QueryExecution.scala:160) …