Github user zsxwing commented on the pull request:
https://github.com/apache/spark/pull/11030#issuecomment-182510817
Found the failure cause:
Hadoop FileSystem API will wrap `InterruptedException` as `IOException`...
```
java.io.IOException: java.lang.InterruptedException
at org.apache.hadoop.util.Shell.runCommand(Shell.java:508)
at org.apache.hadoop.util.Shell.run(Shell.java:418)
at
org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:650)
at org.apache.hadoop.util.Shell.execCommand(Shell.java:739)
at org.apache.hadoop.util.Shell.execCommand(Shell.java:722)
at
org.apache.hadoop.fs.RawLocalFileSystem.setPermission(RawLocalFileSystem.java:633)
at
org.apache.hadoop.fs.FilterFileSystem.setPermission(FilterFileSystem.java:467)
at
org.apache.hadoop.fs.ChecksumFileSystem.create(ChecksumFileSystem.java:456)
at
org.apache.hadoop.fs.ChecksumFileSystem.create(ChecksumFileSystem.java:424)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:906)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:887)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:784)
at
org.apache.spark.sql.execution.streaming.FileStreamSource.writeBatch(FileStreamSource.scala:186)
at
org.apache.spark.sql.execution.streaming.FileStreamSource.fetchMaxOffset(FileStreamSource.scala:115)
at
org.apache.spark.sql.execution.streaming.FileStreamSource.getNextBatch(FileStreamSource.scala:139)
at
org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$3.applyOrElse(StreamExecution.scala:182)
at
org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$3.applyOrElse(StreamExecution.scala:179)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:262)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:262)
at
org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:261)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:267)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:267)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:304)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:370)
at scala.collection.Iterator$class.foreach(Iterator.scala:742)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1194)
at
scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
at
scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
at
scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:308)
at scala.collection.AbstractIterator.to(Iterator.scala:1194)
at
scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:300)
at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1194)
at
scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:287)
at scala.collection.AbstractIterator.toArray(Iterator.scala:1194)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformChildren(TreeNode.scala:353)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:267)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:251)
at
org.apache.spark.sql.execution.streaming.StreamExecution.attemptBatch(StreamExecution.scala:179)
at
org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches(StreamExecution.scala:123)
at
org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:74)
```
So if we call `stop()`(interrupt) while a batch is writing some file, we
will get `IOException`...
One workaround is adding `addCheck()` above this line:
https://github.com/apache/spark/blob/master/sql/core/src/test/scala/org/apache/spark/sql/StreamTest.scala#L339
Then we can make sure no batch is writing any file when we call `stop`.
Another one is we should allow exception happens in this test since we
randomly start and stop the stream multiple times.
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