Я получаю сообщение об ошибке ниже в Spark Job с использованием программирования Python. В сообщении об ошибке написано: «Истекло время сердцебиения исполнителя». Журнал ошибок прилагается ниже:
Py4JJavaError: An error occurred while calling o152.parquet.
: org.apache.spark.SparkException: Job aborted.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:224)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:154)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:104)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:102)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.doExecute(commands.scala:122)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:80)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:80)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:656)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:656)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:656)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:273)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:267)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:225)
at org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:549)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Thread.java:748)
Ниже приведены ошибки:
Причина: org.apache.spark.SparkException: задание прервано из-за сбоя этапа: задача 38 на этапе 9.0 не удалась 4 раза, последний сбой: потерянная задача 38.3 на этапе 9.0 (TID 532, alp-pos-005. unix.cosng.net, исполнитель 24): ExecutorLostFailure (исполнитель 24 завершил работу из-за одной из запущенных задач) Причина: истекло время сердцебиения исполнителя через 154863 мс.
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1651)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1639)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1638)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1638)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:831)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1872)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1821)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1810)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2034)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:194)
... 31 more
После сохранения spark.network.timeout 10000000 появляется следующая ошибка.
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 59 in stage 19.0 failed 4 times, most recent failure: Lost task 59.3 in stage 19.0 (TID 3614, alp-pos-004.unix.cosng.net, executor 29): ExecutorLostFailure (executor 29 exited caused by one of the running tasks) Reason: Container marked as failed: container_e150_1579619385046_0042_01_000038 on host: alp-pos-004.unix.cosng.net. Exit status: 143. Diagnostics: [2020-01-23 12:42:08.482]Container killed on request. Exit code is 143
[2020-01-23 12:42:08.482]Container exited with a non-zero exit code 143.
[2020-01-23 12:42:08.482]Killed by external signal
Любая помощь будет очень признательна на этом этапе.
Спасибо gnish
