Wing Yew Poon created SPARK-22403:
-------------------------------------
Summary: StructuredKafkaWordCount example fails in YARN cluster
mode
Key: SPARK-22403
URL: https://issues.apache.org/jira/browse/SPARK-22403
Project: Spark
Issue Type: Bug
Components: Structured Streaming
Affects Versions: 2.2.0
Reporter: Wing Yew Poon
When I run the StructuredKafkaWordCount example in YARN client mode, it runs
fine. However, when I run it in YARN cluster mode, the application errors
during initialization, and dies after the default number of YARN application
attempts. In the AM log, I see
{noformat}
17/10/30 11:34:52 INFO execution.SparkSqlParser: Parsing command: CAST(value AS
STRING)
17/10/30 11:34:53 ERROR streaming.StreamMetadata: Error writing stream metadata
StreamMetadata(b71ca714-a7a1-467f-96aa-023375964429) to
/data/yarn/nm/usercache/systest/appcache/application_1508800814252_0047/container_1508800814252_0047_01_000001/tmp/temporary-b5ced4ae-32e0-4725-b905-aad679aec9b5/metadata
org.apache.hadoop.security.AccessControlException: Permission denied:
user=systest, access=WRITE, inode="/":hdfs:supergroup:drwxr-xr-x
at
org.apache.hadoop.hdfs.server.namenode.FSPermissionChecker.check(FSPermissionChecker.java:397)
at
org.apache.hadoop.hdfs.server.namenode.FSPermissionChecker.checkPermission(FSPermissionChecker.java:256)
at
org.apache.hadoop.hdfs.server.namenode.FSPermissionChecker.checkPermission(FSPermissionChecker.java:194)
at
org.apache.hadoop.hdfs.server.namenode.FSDirectory.checkPermission(FSDirectory.java:1842)
at
org.apache.hadoop.hdfs.server.namenode.FSDirectory.checkPermission(FSDirectory.java:1826)
at
org.apache.hadoop.hdfs.server.namenode.FSDirectory.checkAncestorAccess(FSDirectory.java:1785)
at
org.apache.hadoop.hdfs.server.namenode.FSDirWriteFileOp.resolvePathForStartFile(FSDirWriteFileOp.java:315)
at
org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFileInt(FSNamesystem.java:2313)
at
org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFile(FSNamesystem.java:2257)
...
at
org.apache.hadoop.hdfs.DFSOutputStream.newStreamForCreate(DFSOutputStream.java:280)
at org.apache.hadoop.hdfs.DFSClient.create(DFSClient.java:1235)
at org.apache.hadoop.hdfs.DFSClient.create(DFSClient.java:1214)
at org.apache.hadoop.hdfs.DFSClient.create(DFSClient.java:1152)
at
org.apache.hadoop.hdfs.DistributedFileSystem$8.doCall(DistributedFileSystem.java:458)
at
org.apache.hadoop.hdfs.DistributedFileSystem$8.doCall(DistributedFileSystem.java:455)
at
org.apache.hadoop.fs.FileSystemLinkResolver.resolve(FileSystemLinkResolver.java:81)
at
org.apache.hadoop.hdfs.DistributedFileSystem.create(DistributedFileSystem.java:469)
at
org.apache.hadoop.hdfs.DistributedFileSystem.create(DistributedFileSystem.java:396)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:1103)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:1083)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:972)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:960)
at
org.apache.spark.sql.execution.streaming.StreamMetadata$.write(StreamMetadata.scala:76)
at
org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$6.apply(StreamExecution.scala:116)
at
org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$6.apply(StreamExecution.scala:114)
at scala.Option.getOrElse(Option.scala:121)
at
org.apache.spark.sql.execution.streaming.StreamExecution.<init>(StreamExecution.scala:114)
at
org.apache.spark.sql.streaming.StreamingQueryManager.createQuery(StreamingQueryManager.scala:240)
at
org.apache.spark.sql.streaming.StreamingQueryManager.startQuery(StreamingQueryManager.scala:278)
at
org.apache.spark.sql.streaming.DataStreamWriter.start(DataStreamWriter.scala:282)
at
org.apache.spark.examples.sql.streaming.StructuredKafkaWordCount$.main(StructuredKafkaWordCount.scala:79)
at
org.apache.spark.examples.sql.streaming.StructuredKafkaWordCount.main(StructuredKafkaWordCount.scala)
{noformat}
Looking at StreamingQueryManager#createQuery, we have
https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/streaming/StreamingQueryManager.scala#L198
{code}
val checkpointLocation = userSpecifiedCheckpointLocation.map { ...
...
}.orElse {
...
}.getOrElse {
if (useTempCheckpointLocation) {
// Delete the temp checkpoint when a query is being stopped without
errors.
deleteCheckpointOnStop = true
Utils.createTempDir(namePrefix = s"temporary").getCanonicalPath
} else {
...
}
}
{code}
And Utils.createTempDir has
{code}
def createTempDir(
root: String = System.getProperty("java.io.tmpdir"),
namePrefix: String = "spark"): File = {
val dir = createDirectory(root, namePrefix)
ShutdownHookManager.registerShutdownDeleteDir(dir)
dir
}
{code}
In client mode, java.io.tmpdir is set to "/tmp", which also exists in HDFS and
has permissions 1777. In cluster mode, java.io.tmpdir is set in the YARN AM to
"$PWD/tmp", where PWD is "/yarn/nm/usercache/<user>/appcache/<app
id>/<container id>".
The problem is that Spark is using java.io.tmpdir, which is a path in the local
filesystem, as a path in HDFS. When that path is "/tmp", which happens to exist
in HDFS, no problem arises, but that is just by coincidence.
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