[
https://issues.apache.org/jira/browse/SPARK-34563?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17296250#comment-17296250
]
Michael Kamprath commented on SPARK-34563:
------------------------------------------
I just tested this under Spark 3.1.1 keep everything else in my set up the
same, and it fails at the same point. However, the exception thrown looks
slightly different:
{code:java}
Py4JJavaError Traceback (most recent call last)
<ipython-input-2-ea419227c865> in <module>
8 print('Processing i = {0}'.format(i))
9 new_df = spark.range(RANGE_STEP*i + 1, RANGE_STEP*(i+1) + 1,
numPartitions=PARTITIONS)
---> 10 df = df.union(new_df).checkpoint()
11
12 df.count()
/usr/spark-3.1.1/python/pyspark/sql/dataframe.py in checkpoint(self, eager)
544 This API is experimental.
545 """
--> 546 jdf = self._jdf.checkpoint(eager)
547 return DataFrame(jdf, self.sql_ctx)
548
/usr/spark-3.1.1/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py in
__call__(self, *args)
1303 answer = self.gateway_client.send_command(command)
1304 return_value = get_return_value(
-> 1305 answer, self.gateway_client, self.target_id, self.name)
1306
1307 for temp_arg in temp_args:
/usr/spark-3.1.1/python/pyspark/sql/utils.py in deco(*a, **kw)
109 def deco(*a, **kw):
110 try:
--> 111 return f(*a, **kw)
112 except py4j.protocol.Py4JJavaError as e:
113 converted = convert_exception(e.java_exception)
/usr/spark-3.1.1/python/lib/py4j-0.10.9-src.zip/py4j/protocol.py in
get_return_value(answer, gateway_client, target_id, name)
326 raise Py4JJavaError(
327 "An error occurred while calling {0}{1}{2}.\n".
--> 328 format(target_id, ".", name), value)
329 else:
330 raise Py4JError(
Py4JJavaError: An error occurred while calling o65.checkpoint.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 8 in
stage 2.0 failed 4 times, most recent failure: Lost task 8.3 in stage 2.0 (TID
50) (10.20.30.17 executor 3): java.lang.IndexOutOfBoundsException: Index: 61,
Size: 0
at java.util.ArrayList.rangeCheck(ArrayList.java:659)
at java.util.ArrayList.get(ArrayList.java:435)
at
com.esotericsoftware.kryo.util.MapReferenceResolver.getReadObject(MapReferenceResolver.java:60)
at com.esotericsoftware.kryo.Kryo.readReferenceOrNull(Kryo.java:857)
at com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:811)
at
org.apache.spark.serializer.KryoDeserializationStream.readObject(KryoSerializer.scala:296)
at
org.apache.spark.serializer.DeserializationStream$$anon$1.getNext(Serializer.scala:168)
at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
at
org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown
Source)
at
org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at
org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:755)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1866)
at org.apache.spark.rdd.RDD.$anonfun$count$1(RDD.scala:1253)
at org.apache.spark.rdd.RDD.$anonfun$count$1$adapted(RDD.scala:1253)
at
org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2242)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at
org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
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:748)
Driver stacktrace:
at
org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2253)
at
org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2202)
at
org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2201)
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:2201)
at
org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1078)
at
org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1078)
at scala.Option.foreach(Option.scala:407)
at
org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1078)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2440)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2382)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2371)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at
org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:868)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2202)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2223)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2242)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2267)
at org.apache.spark.rdd.RDD.count(RDD.scala:1253)
at org.apache.spark.sql.Dataset.$anonfun$checkpoint$1(Dataset.scala:697)
at
org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3687)
at
org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:103)
at
org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163)
at
org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:772)
at
org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3685)
at org.apache.spark.sql.Dataset.checkpoint(Dataset.scala:688)
at org.apache.spark.sql.Dataset.checkpoint(Dataset.scala:651)
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)
Caused by: java.lang.IndexOutOfBoundsException: Index: 61, Size: 0
at java.util.ArrayList.rangeCheck(ArrayList.java:659)
at java.util.ArrayList.get(ArrayList.java:435)
at
com.esotericsoftware.kryo.util.MapReferenceResolver.getReadObject(MapReferenceResolver.java:60)
at com.esotericsoftware.kryo.Kryo.readReferenceOrNull(Kryo.java:857)
at com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:811)
at
org.apache.spark.serializer.KryoDeserializationStream.readObject(KryoSerializer.scala:296)
at
org.apache.spark.serializer.DeserializationStream$$anon$1.getNext(Serializer.scala:168)
at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
at
org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown
Source)
at
org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at
org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:755)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1866)
at org.apache.spark.rdd.RDD.$anonfun$count$1(RDD.scala:1253)
at org.apache.spark.rdd.RDD.$anonfun$count$1$adapted(RDD.scala:1253)
at
org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2242)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at
org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more
{code}
> Checkpointing a union with another checkpoint fails
> ---------------------------------------------------
>
> Key: SPARK-34563
> URL: https://issues.apache.org/jira/browse/SPARK-34563
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 3.0.2
> Environment: I am running Spark 3.0.2 in stand alone cluster mode,
> built for Hadoop 2.7, and Scala 2.12.12. I am using QFS 2.2.2 (Quantcast File
> System) as the underlying DFS. The nodes run on Debian Stretch, and Java is
> openjdk version "1.8.0_275".
> Reporter: Michael Kamprath
> Priority: Major
>
> I have some PySpark code that periodically checkpoints a data frame that I
> am building in pieces by union-ing those pieces together as they are
> constructed. (Py)Spark fails on the second checkpoint, which would be a union
> of a new piece of the desired data frame with a previously checkpointed
> piece. Some simplified PySpark code that will trigger this problem is:
>
> {code:java}
> RANGE_STEP = 10000
> PARTITIONS = 5
> COUNT_UNIONS = 20
> df = spark.range(1, RANGE_STEP+1, numPartitions=PARTITIONS)
> for i in range(1, COUNT_UNIONS+1):
> print('Processing i = {0}'.format(i))
> new_df = spark.range(RANGE_STEP*i + 1, RANGE_STEP*(i+1) + 1,
> numPartitions=PARTITIONS)
> df = df.union(new_df).checkpoint()
> df.count()
> {code}
> When this code gets to the checkpoint on the second loop iteration (i=2) the
> job fails with an error:
>
> {code:java}
> Py4JJavaError: An error occurred while calling o119.checkpoint.
> : org.apache.spark.SparkException: Job aborted due to stage failure: Task 9
> in stage 10.0 failed 4 times, most recent failure: Lost task 9.3 in stage
> 10.0 (TID 264, 10.20.30.13, executor 0):
> com.esotericsoftware.kryo.KryoException: Encountered unregistered class ID:
> 9062
> at
> com.esotericsoftware.kryo.util.DefaultClassResolver.readClass(DefaultClassResolver.java:137)
> at com.esotericsoftware.kryo.Kryo.readClass(Kryo.java:693)
> at com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:804)
> at
> org.apache.spark.serializer.KryoDeserializationStream.readObject(KryoSerializer.scala:296)
> at
> org.apache.spark.serializer.DeserializationStream$$anon$1.getNext(Serializer.scala:168)
> at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown
> Source)
> at
> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:729)
> at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
> at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1804)
> at org.apache.spark.rdd.RDD.$anonfun$count$1(RDD.scala:1227)
> at org.apache.spark.rdd.RDD.$anonfun$count$1$adapted(RDD.scala:1227)
> at
> org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2154)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
> at org.apache.spark.scheduler.Task.run(Task.scala:127)
> at
> org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:462)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:465)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
> at java.lang.Thread.run(Thread.java:748)
> Driver stacktrace:
> at
> org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2059)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2008)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2007)
> at
> scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
> at
> scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
> at
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2007)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:973)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:973)
> at scala.Option.foreach(Option.scala:407)
> at
> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:973)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2239)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2188)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2177)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
> at
> org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:775)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2114)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2135)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2154)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2179)
> at org.apache.spark.rdd.RDD.count(RDD.scala:1227)
> at org.apache.spark.sql.Dataset.$anonfun$checkpoint$1(Dataset.scala:696)
> at
> org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3618)
> at
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:100)
> at
> org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:160)
> at
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:87)
> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:764)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
> at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3616)
> at org.apache.spark.sql.Dataset.checkpoint(Dataset.scala:687)
> at org.apache.spark.sql.Dataset.checkpoint(Dataset.scala:650)
> 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)
> Caused by: com.esotericsoftware.kryo.KryoException: Encountered unregistered
> class ID: 9062
> at
> com.esotericsoftware.kryo.util.DefaultClassResolver.readClass(DefaultClassResolver.java:137)
> at com.esotericsoftware.kryo.Kryo.readClass(Kryo.java:693)
> at com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:804)
> at
> org.apache.spark.serializer.KryoDeserializationStream.readObject(KryoSerializer.scala:296)
> at
> org.apache.spark.serializer.DeserializationStream$$anon$1.getNext(Serializer.scala:168)
> at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown
> Source)
> at
> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:729)
> at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
> at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1804)
> at org.apache.spark.rdd.RDD.$anonfun$count$1(RDD.scala:1227)
> at org.apache.spark.rdd.RDD.$anonfun$count$1$adapted(RDD.scala:1227)
> at
> org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2154)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
> at org.apache.spark.scheduler.Task.run(Task.scala:127)
> at
> org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:462)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:465)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
> ... 1 more
> {code}
>
> Note that the checkpoint directory is set, as the first checkpoint does
> succeed. Also, if the checkpoint method is removed, the sample code succeeds
> as expected, so the problems isolated to the use of the checkpoint.
>
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