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https://issues.apache.org/jira/browse/SPARK-21418?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Herman van Hovell resolved SPARK-21418.
---------------------------------------
Resolution: Fixed
Assignee: Sean Owen
Fix Version/s: 2.3.0
2.2.1
> 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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