Executor heartbeat timed Out : Error in Spark Job

Question

I am getting below error in Spark Job using Python Programming. The Error says "Executor heartbeat timed out". Error log attached below:

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)

Below are the error:

Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 38 in stage 9.0 failed 4 times, most recent failure: Lost task 38.3 in stage 9.0 (TID 532, alp-pos-005.unix.cosng.net, executor 24): ExecutorLostFailure (executor 24 exited caused by one of the running tasks) Reason: Executor heartbeat timed out after 154863 ms

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

After keeping spark.network.timeout 10000000, then the below error is coming.

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

Any help would be highly appreciated at this point.

Thanks gnish

Answer 1

Usually the problem related to this cases are memory, but one easy way to do a workaround to the problem is increase the spark.network.timeout. This helps but this is not long term solution.

So just try this:

spark-submit --conf spark.network.timeout 10000000 python_script.py