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Databricks Cluster create fail

wgsing
New Contributor

i facing the problem here in creating cluster in databricks.

Error as below :

Message

Cluster terminated.Reason:Unexpected launch failure

An unexpected error was encountered while setting up the cluster. Please retry and contact Databricks if the problem persists.

Internal error message: java.lang.RuntimeException: Internal error (no failure to report)

at com.databricks.backend.manager.AddResourcesStateHelper$.<init>(AddResourcesState.scala:204)

at com.databricks.backend.manager.AddResourcesStateHelper$.<clinit>(AddResourcesState.scala)

at com.databricks.backend.manager.ClusterManager.shouldStopAddingNodes(ClusterManager.scala:3475)

at com.databricks.backend.manager.ClusterManager.runAddResourceSteps(ClusterManager.scala:3625)

at com.databricks.backend.manager.ClusterManager.addResourcesToCluster(ClusterManager.scala:3529)

at com.databricks.backend.manager.ClusterManager.doAddContainersToCluster(ClusterManager.scala:1903)

at com.databricks.backend.manager.ClusterManager.$anonfun$doUpsizeCluster$1(ClusterManager.scala:1361)

at com.databricks.backend.manager.ClusterManager.$anonfun$resizeClusterWrapper$2(ClusterManager.scala:1285)

at com.databricks.backend.manager.ClusterManager.withAuditLog(ClusterManager.scala:2212)

at com.databricks.backend.manager.ClusterManager.$anonfun$resizeClusterWrapper$1(ClusterManager.scala:1282)

at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)

at com.databricks.logging.UsageLogging.$anonfun$recordOperation$1(UsageLogging.scala:341)

at com.databricks.logging.UsageLogging.executeThunkAndCaptureResultTags$1(UsageLogging.scala:435)

at com.databricks.logging.UsageLogging.$anonfun$recordOperationWithResultTags$4(UsageLogging.scala:455)

at com.databricks.logging.UsageLogging.$anonfun$withAttributionContext$1(UsageLogging.scala:215)

at scala.util.DynamicVariable.withValue(DynamicVariable.scala:62)

at com.databricks.logging.AttributionContext$.withValue(AttributionContext.scala:95)

at com.databricks.logging.UsageLogging.withAttributionContext(UsageLogging.scala:213)

at com.databricks.logging.UsageLogging.withAttributionContext$(UsageLogging.scala:210)

at com.databricks.backend.manager.ClusterManager.withAttributionContext(ClusterManager.scala:126)

at com.databricks.logging.UsageLogging.withAttributionTags(UsageLogging.scala:251)

at com.databricks.logging.UsageLogging.withAttributionTags$(UsageLogging.scala:243)

at com.databricks.backend.manager.ClusterManager.withAttributionTags(ClusterManager.scala:126)

at com.databricks.logging.UsageLogging.recordOperationWithResultTags(UsageLogging.scala:430)

at com.databricks.logging.UsageLogging.recordOperationWithResultTags$(UsageLogging.scala:350)

at com.databricks.backend.manager.ClusterManager.recordOperationWithResultTags(ClusterManager.scala:126)

at com.databricks.logging.UsageLogging.recordOperation(UsageLogging.scala:341)

at com.databricks.logging.UsageLogging.recordOperation$(UsageLogging.scala:313)

at com.databricks.backend.manager.ClusterManager.recordOperation(ClusterManager.scala:126)

at com.databricks.backend.manager.ClusterManager.resizeClusterWrapper(ClusterManager.scala:1282)

at com.databricks.backend.manager.ClusterManager.doUpsizeCluster(ClusterManager.scala:1329)

at com.databricks.backend.manager.ClusterManager.doSetupOrUpsize(ClusterManager.scala:2378)

at com.databricks.backend.manager.UpsizeThrottlingMonitor.$anonfun$processRequest$3(UpsizeThrottlingMonitor.scala:339)

at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)

at scala.util.Try$.apply(Try.scala:213)

at com.databricks.backend.manager.util.ConsolidatedClusterUpdateHelper.withConsolidatedClusterUpdate(ConsolidatedClusterUpdateHelper.scala:52)

at com.databricks.backend.manager.util.ConsolidatedClusterUpdateHelper.withConsolidatedClusterUpdateForAsync(ConsolidatedClusterUpdateHelper.scala:86)

at com.databricks.backend.manager.util.ConsolidatedClusterUpdateHelper.withConsolidatedClusterUpdateForAsync$(ConsolidatedClusterUpdateHelper.scala:84)

at com.databricks.backend.manager.UpsizeThrottlingMonitor.withConsolidatedClusterUpdateForAsync(UpsizeThrottlingMonitor.scala:105)

at com.databricks.backend.manager.UpsizeThrottlingMonitor.$anonfun$processRequest$2(UpsizeThrottlingMonitor.scala:339)

at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)

at com.databricks.logging.UsageLogging.$anonfun$withAttributionContext$1(UsageLogging.scala:215)

at scala.util.DynamicVariable.withValue(DynamicVariable.scala:62)

at com.databricks.logging.AttributionContext$.withValue(AttributionContext.scala:95)

at com.databricks.logging.UsageLogging.withAttributionContext(UsageLogging.scala:213)

at com.databricks.logging.UsageLogging.withAttributionContext$(UsageLogging.scala:210)

at com.databricks.backend.manager.UpsizeThrottlingMonitor.withAttributionContext(UpsizeThrottlingMonitor.scala:105)

at com.databricks.backend.manager.UpsizeThrottlingMonitor.$anonfun$processRequest$1(UpsizeThrottlingMonitor.scala:338)

at com.databricks.backend.common.util.ParallelRunHelper.$anonfun$runTask$1(ParallelRunHelper.scala:52)

at scala.runtime.java8.JFunction1$mcVI$sp.apply(JFunction1$mcVI$sp.java:23)

at com.databricks.backend.common.util.GenericParallelRunHelper.$anonfun$runInParallel$3(ParallelRunHelper.scala:283)

at com.databricks.logging.UsageLogging.$anonfun$withAttributionContext$1(UsageLogging.scala:215)

at scala.util.DynamicVariable.withValue(DynamicVariable.scala:62)

at com.databricks.logging.AttributionContext$.withValue(AttributionContext.scala:95)

at com.databricks.logging.UsageLogging.withAttributionContext(UsageLogging.scala:213)

at com.databricks.logging.UsageLogging.withAttributionContext$(UsageLogging.scala:210)

at com.databricks.backend.common.util.GenericParallelRunHelper.withAttributionContext(ParallelRunHelper.scala:176)

at com.databricks.logging.UsageLogging.withAttributionTags(UsageLogging.scala:251)

at com.databricks.logging.UsageLogging.withAttributionTags$(UsageLogging.scala:243)

at com.databricks.backend.common.util.GenericParallelRunHelper.withAttributionTags(ParallelRunHelper.scala:176)

at com.databricks.backend.common.util.GenericParallelRunHelper.$anonfun$runInParallel$2(ParallelRunHelper.scala:283)

at scala.concurrent.Future$.$anonfun$apply$1(Future.scala:659)

at scala.util.Success.$anonfun$map$1(Try.scala:255)

at scala.util.Success.map(Try.scala:213)

at scala.concurrent.Future.$anonfun$map$1(Future.scala:292)

at scala.concurrent.impl.Promise.liftedTree1$1(Promise.scala:33)

at scala.concurrent.impl.Promise.$anonfun$transform$1(Promise.scala:33)

at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:64)

at com.databricks.threading.NamedExecutor$$anon$2.$anonfun$run$1(NamedExecutor.scala:359)

at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)

at com.databricks.logging.UsageLogging.$anonfun$withAttributionContext$1(UsageLogging.scala:215)

at scala.util.DynamicVariable.withValue(DynamicVariable.scala:62)

at com.databricks.logging.AttributionContext$.withValue(AttributionContext.scala:95)

at com.databricks.logging.UsageLogging.withAttributionContext(UsageLogging.scala:213)

at com.databricks.logging.UsageLogging.withAttributionContext$(UsageLogging.scala:210)

at com.databricks.threading.NamedExecutor.withAttributionContext(NamedExecutor.scala:287)

at com.databricks.threading.NamedExecutor$$anon$2.run(NamedExecutor.scala:358)

at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)

at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)

at java.base/java.lang.Thread.run(Thread.java:834)

1 ACCEPTED SOLUTION

Accepted Solutions

Anonymous
Not applicable

Hi @Giin Sing Wongโ€‹  It could have issues with AWS account quotas. Please check if you have the required CPU cores available in quota and share the cluster id and workspace URL if it continues to happen.

View solution in original post

3 REPLIES 3

-werners-
Esteemed Contributor III

@Giin Sing Wongโ€‹ , could it be that your CPU quota has been reached?

Anonymous
Not applicable

Hi @Giin Sing Wongโ€‹  It could have issues with AWS account quotas. Please check if you have the required CPU cores available in quota and share the cluster id and workspace URL if it continues to happen.

jose_gonzalez
Databricks Employee
Databricks Employee

Hi @Giin Sing Wongโ€‹ ,

Just a friendly follow-up. Is this issue still happening or you were able to resolve it by increasing your account's quota? Please let us know.

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