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Posted to issues@spark.apache.org by "Dale Richardson (JIRA)" <ji...@apache.org> on 2017/09/13 23:19:02 UTC
[jira] [Comment Edited] (SPARK-21418) NoSuchElementException:
None.get in DataSourceScanExec with
sun.io.serialization.extendedDebugInfo=true
[ https://issues.apache.org/jira/browse/SPARK-21418?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16165448#comment-16165448 ]
Dale Richardson edited comment on SPARK-21418 at 9/13/17 11:18 PM:
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I'm getting the same stackdump in 2.2.0 while using apache-avro (current snapshot) in structured streaming with a globbed hdfs input path. I do not get this error if I use a non-globbed input path.
I should note that this is without setting sun.io.serialization.extendedDebugInfo at all.
was (Author: tigerquoll):
I'm getting the same stackdump in 2.2.0 while using apache-avro (current snapshot) in structured streaming with a globbed hdfs input path. I do not get this error if I use a non-globbed input path.
> NoSuchElementException: None.get in DataSourceScanExec with sun.io.serialization.extendedDebugInfo=true
> -------------------------------------------------------------------------------------------------------
>
> Key: SPARK-21418
> URL: https://issues.apache.org/jira/browse/SPARK-21418
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.2.0
> Reporter: Daniel Darabos
> Assignee: Sean Owen
> Priority: Minor
> Fix For: 2.2.1, 2.3.0
>
>
> I don't have a minimal reproducible example yet, sorry. I have the following lines in a unit test for our Spark application:
> {code}
> val df = mySparkSession.read.format("jdbc")
> .options(Map("url" -> url, "dbtable" -> "test_table"))
> .load()
> df.show
> println(df.rdd.collect)
> {code}
> The output shows the DataFrame contents from {{df.show}}. But the {{collect}} fails:
> {noformat}
> org.apache.spark.SparkException: Job aborted due to stage failure: Task serialization failed: java.util.NoSuchElementException: None.get
> java.util.NoSuchElementException: None.get
> at scala.None$.get(Option.scala:347)
> at scala.None$.get(Option.scala:345)
> at org.apache.spark.sql.execution.DataSourceScanExec$class.org$apache$spark$sql$execution$DataSourceScanExec$$redact(DataSourceScanExec.scala:70)
> at org.apache.spark.sql.execution.DataSourceScanExec$$anonfun$4.apply(DataSourceScanExec.scala:54)
> at org.apache.spark.sql.execution.DataSourceScanExec$$anonfun$4.apply(DataSourceScanExec.scala:52)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
> at scala.collection.AbstractTraversable.map(Traversable.scala:104)
> at org.apache.spark.sql.execution.DataSourceScanExec$class.simpleString(DataSourceScanExec.scala:52)
> at org.apache.spark.sql.execution.RowDataSourceScanExec.simpleString(DataSourceScanExec.scala:75)
> at org.apache.spark.sql.catalyst.plans.QueryPlan.verboseString(QueryPlan.scala:349)
> at org.apache.spark.sql.execution.RowDataSourceScanExec.org$apache$spark$sql$execution$DataSourceScanExec$$super$verboseString(DataSourceScanExec.scala:75)
> at org.apache.spark.sql.execution.DataSourceScanExec$class.verboseString(DataSourceScanExec.scala:60)
> at org.apache.spark.sql.execution.RowDataSourceScanExec.verboseString(DataSourceScanExec.scala:75)
> at org.apache.spark.sql.catalyst.trees.TreeNode.generateTreeString(TreeNode.scala:556)
> at org.apache.spark.sql.execution.WholeStageCodegenExec.generateTreeString(WholeStageCodegenExec.scala:451)
> at org.apache.spark.sql.catalyst.trees.TreeNode.generateTreeString(TreeNode.scala:576)
> at org.apache.spark.sql.catalyst.trees.TreeNode.treeString(TreeNode.scala:480)
> at org.apache.spark.sql.catalyst.trees.TreeNode.treeString(TreeNode.scala:477)
> at org.apache.spark.sql.catalyst.trees.TreeNode.toString(TreeNode.scala:474)
> at java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1421)
> at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
> at java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1548)
> at java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1509)
> at java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
> at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
> at java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1548)
> at java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1509)
> at java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
> at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
> at java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1548)
> at java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1509)
> at java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
> at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
> at java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1548)
> at java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1509)
> at java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
> at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
> at java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1548)
> at java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1509)
> at java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
> at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
> at java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:348)
> at scala.collection.immutable.List$SerializationProxy.writeObject(List.scala:468)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:498)
> at java.io.ObjectStreamClass.invokeWriteObject(ObjectStreamClass.java:1028)
> at java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1496)
> at java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
> at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
> at java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1548)
> at java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1509)
> at java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
> at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
> at java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1548)
> at java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1509)
> at java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
> at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
> at java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:348)
> at org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:43)
> at org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:100)
> at org.apache.spark.scheduler.DAGScheduler.submitMissingTasks(DAGScheduler.scala:1003)
> at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitStage(DAGScheduler.scala:930)
> at org.apache.spark.scheduler.DAGScheduler.handleJobSubmitted(DAGScheduler.scala:874)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1677)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1669)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1658)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
> {noformat}
> Looks like this is due to https://github.com/apache/spark/commit/91fa80fe8a2480d64c430bd10f97b3d44c007bcc#diff-2a91a9a59953aa82fa132aaf45bd731bR69 from https://issues.apache.org/jira/browse/SPARK-20070. It tries to redact sensitive information from {{explain}} output. (We are not trying to explain anything here, so I doubt it is meant to be running in this case.) When it needs to access some configuration, it tries to take it from the "current" Spark session, which it just reads from a thread-local variable. We appear to be on a thread where this variable is not set.
> My impression is that SPARK-20070 unintentionally introduced a very hard constraint on multi-threaded Spark applications.
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