This is an expensive and long-running job that gets about halfway done before failing. The stack trace is included below, but here is the salient part:
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 4881 in stage 1.0 failed 4 times, most recent failure: Lost task 4881.3 in stage 1.0 (TID 7305, 10.37.129.129): ExecutorLostFailure (executor 116 exited caused by one of the running tasks) Reason: Remote RPC client disassociated. Likely due to containers exceeding thresholds, or network issues. Check driver logs for WARN messages.
This job has been running fine for months up to this point. I have tried increasing the node size, but still receiving this error. I saw from a Google search that this might be YARN not having enough provisioned memory, but I was under the impression that it was all configured under the hood with Databricks. Should I try tweaking these values? If so which?
Here is the full stack-trace:
---------------------------------------------------------------------------Py4JJavaError Traceback (most recent call last)
<ipython-input-2-b42178413d3f> in <module>() 254 )
255--> 256final_data.write .format('com.databricks.spark.redshift').option('preactions', delete_stmt).option('url', REDSHIFT_URL).option('dbtable', load_table).option('tempdir', REDSHIFT_TEMPDIR +'/courses_monthly').mode("append").save()/databricks/spark/python/pyspark/sql/readwriter.py in save(self, path, format, mode, partitionBy, **options) 528 self.format(format) 529if path is None:--> 530self._jwrite.save() 531else: 532 self._jwrite.save(path)/databricks/spark/python/lib/py4j-0.10.1-src.zip/py4j/java_gateway.py in __call__(self, *args) 931 answer = self.gateway_client.send_command(command) 932 return_value = get_return_value(
--> 933 answer, self.gateway_client, self.target_id, self.name)
934 935for temp_arg in temp_args:/databricks/spark/python/pyspark/sql/utils.py in deco(*a, **kw) 61def deco(*a,**kw): 62try:---> 63return f(*a,**kw) 64except py4j.protocol.Py4JJavaError as e: 65 s = e.java_exception.toString()/databricks/spark/python/lib/py4j-0.10.1-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name) 310 raise Py4JJavaError(
311"An error occurred while calling {0}{1}{2}.\n".--> 312 format(target_id, ".", name), value)
313else: 314 raise Py4JError(
Py4JJavaError: An error occurred while calling o305.save.
: org.apache.spark.SparkException: Job aborted.
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand$$anonfun$run$1.apply$mcV$sp(InsertIntoHadoopFsRelationCommand.scala:149)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand$$anonfun$run$1.apply(InsertIntoHadoopFsRelationCommand.scala:115)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand$$anonfun$run$1.apply(InsertIntoHadoopFsRelationCommand.scala:115)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:115)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:60)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:58)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:136)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:133)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:114)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:86)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:86)
at org.apache.spark.sql.execution.datasources.DataSource.write(DataSource.scala:511)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:211)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:194)
at com.databricks.spark.redshift.RedshiftWriter.unloadData(RedshiftWriter.scala:278)
at com.databricks.spark.redshift.RedshiftWriter.saveToRedshift(RedshiftWriter.scala:346)
at com.databricks.spark.redshift.DefaultSource.createRelation(DefaultSource.scala:106)
at org.apache.spark.sql.execution.datasources.DataSource.write(DataSource.scala:443)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:211)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:237)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:280)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:128)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:211)
at java.lang.Thread.run(Thread.java:745)
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 4881 in stage 1.0 failed 4 times, most recent failure: Lost task 4881.3 in stage 1.0 (TID 7305, 10.37.129.129): ExecutorLostFailure (executor 116 exited caused by one of the running tasks) Reason: Remote RPC client disassociated. Likely due to containers exceeding thresholds, or network issues. Check driver logs for WARN messages.
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1452)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1440)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1439)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1439)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:811)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1665)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1620)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1609)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:632)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1868)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1881)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1901)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand$$anonfun$run$1.apply$mcV$sp(InsertIntoHadoopFsRelationCommand.scala:143)
... 34 more
