Bug: Barrier Executor Stage Not Retried on Task Failure
Status: Closed | Priority: Major | Resolution: Not A Problem
Created: 26/May/23 20:37
Affects Version/s: 3.3.2

When running a stage using barrier executor, the expectation is that a failure in a task will result in the stage being retried. However, if an exception is thrown from a task, the stage is not retried and the job fails.

Running the pyspark code below will cause a single task to fail, failing the stage without retrying.
{code:java}
def test_func(index: int) -> list:
    if index == 0:
        raise RuntimeError("Thrown from test func")
    return []

start_rdd = sc.parallelize([i for i in range(10)], 10)
result = start_rdd.barrier().mapPartitionsWithIndex(lambda i, c: test_func(i))

result.collect(){code}
 

This failure is seen running locally via the pyspark shell and on a K8s cluster.

 

Stack trace from local execution:
{noformat}
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/opt/homebrew/anaconda3/lib/python3.9/site-packages/pyspark/rdd.py", line 1197, in collect
    sock_info = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
  File "/opt/homebrew/anaconda3/lib/python3.9/site-packages/pyspark/python/lib/py4j-0.10.9.5-src.zip/py4j/java_gateway.py", line 1321, in __call__
  File "/opt/homebrew/anaconda3/lib/python3.9/site-packages/pyspark/sql/utils.py", line 190, in deco
    return f(*a, **kw)
  File "/opt/homebrew/anaconda3/lib/python3.9/site-packages/pyspark/python/lib/py4j-0.10.9.5-src.zip/py4j/protocol.py", line 326, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.
: org.apache.spark.SparkException: Job aborted due to stage failure: Could not recover from a failed barrier ResultStage. Most recent failure reason: Stage failed because barrier task ResultTask(0, 0) finished unsuccessfully.
org.apache.spark.api.python.PythonException: Traceback (most recent call last):
  File "/opt/homebrew/anaconda3/lib/python3.9/site-packages/pyspark/python/lib/pyspark.zip/pyspark/worker.py", line 686, in main
    process()
  File "/opt/homebrew/anaconda3/lib/python3.9/site-packages/pyspark/python/lib/pyspark.zip/pyspark/worker.py", line 676, in process
    out_iter = func(split_index, iterator)
  File "<stdin>", line 1, in <lambda>
  File "<stdin>", line 3, in test_func
RuntimeError: Thrown from test func


	at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:559)
	at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:765)
	at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:747)
	at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:512)
	at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
	at scala.collection.Iterator.foreach(Iterator.scala:943)
	at scala.collection.Iterator.foreach$(Iterator.scala:943)
	at org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28)
	at scala.collection.generic.Growable.$plus$plus$eq(Growable.scala:62)
	at scala.collection.generic.Growable.$plus$plus$eq$(Growable.scala:53)
	at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:105)
	at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:49)
	at scala.collection.TraversableOnce.to(TraversableOnce.scala:366)
	at scala.collection.TraversableOnce.to$(TraversableOnce.scala:364)
	at org.apache.spark.InterruptibleIterator.to(InterruptibleIterator.scala:28)
	at scala.collection.TraversableOnce.toBuffer(TraversableOnce.scala:358)
	at scala.collection.TraversableOnce.toBuffer$(TraversableOnce.scala:358)
	at org.apache.spark.InterruptibleIterator.toBuffer(InterruptibleIterator.scala:28)
	at scala.collection.TraversableOnce.toArray(TraversableOnce.scala:345)
	at scala.collection.TraversableOnce.toArray$(TraversableOnce.scala:339)
	at org.apache.spark.InterruptibleIterator.toArray(InterruptibleIterator.scala:28)
	at org.apache.spark.rdd.RDD.$anonfun$collect$2(RDD.scala:1021)
	at org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2268)
	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
	at org.apache.spark.scheduler.Task.run(Task.scala:136)
	at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:548)
	at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1504)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:551)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
	at java.lang.Thread.run(Thread.java:750)


	at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2672)
	at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2608)
	at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2607)
	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:2607)
	at org.apache.spark.scheduler.DAGScheduler.handleTaskCompletion(DAGScheduler.scala:2111)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2857)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2802)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2791)
	at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
	at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:952)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2228)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2249)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2268)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2293)
	at org.apache.spark.rdd.RDD.$anonfun$collect$1(RDD.scala:1021)
	at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
	at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
	at org.apache.spark.rdd.RDD.withScope(RDD.scala:406)
	at org.apache.spark.rdd.RDD.collect(RDD.scala:1020)
	at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:180)
	at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
	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.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)
	at py4j.ClientServerConnection.run(ClientServerConnection.java:106)
	at java.lang.Thread.run(Thread.java:750){noformat}