org.apache.spark.SparkException: Job aborted due to stage failure: Authorized committer failed while pushing dataframe to azure cosmos db.

[manasa]

I am writing data to the azure cosmos db using OLTP connector using below code

cfg["spark.cosmos.write.strategy"]="ItemOverwrite"   
 json_df.write.format("cosmos.oltp").options(**cfg).mode("APPEND").save()

I am getting below error

 

Please let me know if you have faced similar issue or if you have any fix.

Feel free to ask more details

[Debayan]

Hi, could you please post the whole text of the error (not the screenshot.)?

Please tag @Debayan​ with your next response which will notify me, Thank you!

[manasa]

Hi @Debayan Mukherjee​ 

Here is the error message

An error occurred while calling o1616.save.

: org.apache.spark.SparkException: Job aborted due to stage failure: Authorized committer (attemptNumber=0, stage=1306, partition=0) failed; but task commit success, data duplication may happen. reason=TaskKilled(preempted by scheduler,Vector(AccumulableInfo(61880,None,Some(248166),None,false,true,None), AccumulableInfo(61882,None,Some(0),None,false,true,None), AccumulableInfo(61883,None,Some(430),None,false,true,None), AccumulableInfo(61901,None,Some(19155841),None,false,true,None), AccumulableInfo(61902,None,Some(4240),None,false,true,None), AccumulableInfo(61903,None,Some(134710060),None,false,true,None), AccumulableInfo(61904,None,Some(19155841),None,false,true,None), AccumulableInfo(61909,None,Some(0),None,false,true,None), AccumulableInfo(61910,None,Some(19155841),None,false,true,None), AccumulableInfo(61911,None,Some(8),None,false,true,None), AccumulableInfo(61912,None,Some(395),None,false,true,None), AccumulableInfo(61913,None,Some(0),None,false,true,None), AccumulableInfo(61914,None,Some(0),None,false,true,None)),Vector(LongAccumulator(id: 61880, name: Some(internal.metrics.executorRunTime), value: 248166), LongAccumulator(id: 61882, name: Some(internal.metrics.resultSize), value: 0), LongAccumulator(id: 61883, name: Some(internal.metrics.jvmGCTime), value: 430), LongAccumulator(id: 61901, name: Some(internal.metrics.input.bytesRead), value: 19155841), LongAccumulator(id: 61902, name: Some(internal.metrics.input.recordsRead), value: 4240), LongAccumulator(id: 61903, name: Some(internal.metrics.input.sampledTimeReadNano), value: 134710060), LongAccumulator(id: 61904, name: Some(internal.metrics.input.sampledBytesRead), value: 19155841), LongAccumulator(id: 61909, name: Some(internal.metrics.io.requestBytesCount), value: 0), LongAccumulator(id: 61910, name: Some(internal.metrics.io.responseBytesCount), value: 19155841), LongAccumulator(id: 61911, name: Some(internal.metrics.io.requestCount), value: 8), LongAccumulator(id: 61912, name: Some(internal.metrics.io.requestMsDuration), value: 395), LongAccumulator(id: 61913, name: Some(internal.metrics.io.retryCount), value: 0), LongAccumulator(id: 61914, name: Some(internal.metrics.io.retryDelayMsDuration), value: 0)),WrappedArray(1757792296, 367759552, 0, 0, 4755036, 0, 4755036, 0, 14168641, 0, 0, 0, 0, 0, 0, 0, 64, 4546, 7, 3349, 7895))

at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:3334)

at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:3266)

at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:3257)

at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)

at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)

at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)

at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:3257)

at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleStageFailed$1(DAGScheduler.scala:1418)

at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleStageFailed$1$adapted(DAGScheduler.scala:1418)

at scala.Option.foreach(Option.scala:407)

at org.apache.spark.scheduler.DAGScheduler.handleStageFailed(DAGScheduler.scala:1418)

at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:3543)

at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:3484)

at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:3472)

at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:51)

at org.apache.spark.scheduler.DAGScheduler.$anonfun$runJob$1(DAGScheduler.scala:1172)

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

at com.databricks.spark.util.FrameProfiler$.record(FrameProfiler.scala:80)

at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:1160)

at org.apache.spark.SparkContext.runJobInternal(SparkContext.scala:2731)

at org.apache.spark.SparkContext.runJob(SparkContext.scala:2714)

at org.apache.spark.sql.execution.datasources.v2.V2TableWriteExec.writeWithV2(WriteToDataSourceV2Exec.scala:388)

at org.apache.spark.sql.execution.datasources.v2.V2TableWriteExec.writeWithV2$(WriteToDataSourceV2Exec.scala:364)

at org.apache.spark.sql.execution.datasources.v2.AppendDataExec.writeWithV2(WriteToDataSourceV2Exec.scala:250)

at org.apache.spark.sql.execution.datasources.v2.V2ExistingTableWriteExec.run(WriteToDataSourceV2Exec.scala:343)

at org.apache.spark.sql.execution.datasources.v2.V2ExistingTableWriteExec.run$(WriteToDataSourceV2Exec.scala:342)

at org.apache.spark.sql.execution.datasources.v2.AppendDataExec.run(WriteToDataSourceV2Exec.scala:250)

at org.apache.spark.sql.execution.datasources.v2.V2CommandExec.$anonfun$result$1(V2CommandExec.scala:47)

at com.databricks.spark.util.FrameProfiler$.record(FrameProfiler.scala:80)

at org.apache.spark.sql.execution.datasources.v2.V2CommandExec.result$lzycompute(V2CommandExec.scala:47)

at org.apache.spark.sql.execution.datasources.v2.V2CommandExec.result(V2CommandExec.scala:45)

at org.apache.spark.sql.execution.datasources.v2.V2CommandExec.executeCollect(V2CommandExec.scala:54)

at org.apache.spark.sql.execution.QueryExecution$$anonfun$$nestedInanonfun$eagerlyExecuteCommands$1$1.$anonfun$applyOrElse$3(QueryExecution.scala:238)

at org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:153)

at org.apache.spark.sql.execution.QueryExecution$$anonfun$$nestedInanonfun$eagerlyExecuteCommands$1$1.$anonfun$applyOrElse$2(QueryExecution.scala:238)

at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withCustomExecutionEnv$8(SQLExecution.scala:227)

at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:410)

at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withCustomExecutionEnv$1(SQLExecution.scala:172)

at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:1035)

at org.apache.spark.sql.execution.SQLExecution$.withCustomExecutionEnv(SQLExecution.scala:122)

at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:360)

at org.apache.spark.sql.execution.QueryExecution$$anonfun$$nestedInanonfun$eagerlyExecuteCommands$1$1.$anonfun$applyOrElse$1(QueryExecution.scala:237)

at org.apache.spark.sql.execution.QueryExecution.org$apache$spark$sql$execution$QueryExecution$$withMVTagsIfNecessary(QueryExecution.scala:220)

at org.apache.spark.sql.execution.QueryExecution$$anonfun$$nestedInanonfun$eagerlyExecuteCommands$1$1.applyOrElse(QueryExecution.scala:233)

at org.apache.spark.sql.execution.QueryExecution$$anonfun$$nestedInanonfun$eagerlyExecuteCommands$1$1.applyOrElse(QueryExecution.scala:226)

at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$1(TreeNode.scala:519)

at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:106)

at org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:519)

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:316)

at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:312)

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:495)

at org.apache.spark.sql.execution.QueryExecution.$anonfun$eagerlyExecuteCommands$1(QueryExecution.scala:226)

at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$.allowInvokingTransformsInAnalyzer(AnalysisHelper.scala:372)

at org.apache.spark.sql.execution.QueryExecution.eagerlyExecuteCommands(QueryExecution.scala:226)

at org.apache.spark.sql.execution.QueryExecution.commandExecuted$lzycompute(QueryExecution.scala:180)

at org.apache.spark.sql.execution.QueryExecution.commandExecuted(QueryExecution.scala:171)

at org.apache.spark.sql.execution.QueryExecution.assertCommandExecuted(QueryExecution.scala:287)

at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:964)

at org.apache.spark.sql.DataFrameWriter.saveInternal(DataFrameWriter.scala:346)

at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:258)

at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)

at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)

at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)

at java.lang.reflect.Method.invoke(Method.java:498)

at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)

at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:380)

at py4j.Gateway.invoke(Gateway.java:306)

at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)

at py4j.commands.CallCommand.execute(CallCommand.java:79)

at py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:195)

at py4j.ClientServerConnection.run(ClientServerConnection.java:115)

at java.lang.Thread.run(Thread.java:750)

[Debayan]

Hi, I do not see any exact error on the issue, primarily it is looking there is connection issue from control plane to data plane. It would be better if you could raise a case to Databricks support on the same and we can triage it.

[Anonymous]

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