Livy pyspark Python Session Error in Jypyter with Spark Magic - ERROR repl.PythonInterpreter: Process has died with 1 - apache-spark

Question

I'm running a spark v2.0.0 YARN cluster. I have livy running beside the Spark master.
I have set up a jupyter Python3 notetebook and have Spark Magic installed and have followed the nessesary instructions to connect Spark Magic to Livy although When I create my session I get an error message from the notebook.
Added endpoint http://spark-master:8998
Starting Spark application
ID YARN Application ID Kind State Spark UI Driver log Current session?
0 None pyspark idle ✔
---------------------------------------------------------------------------
LivyUnexpectedStatusException Traceback (most recent call last)
/opt/conda/lib/python3.5/site-packages/hdijupyterutils/ipywidgetfactory.py in submit_clicked(self, button)
63
64 def submit_clicked(self, button):
---> 65 self.parent_widget.run()
/opt/conda/lib/python3.5/site-packages/sparkmagic/controllerwidget/createsessionwidget.py in run(self)
56
57 try:
---> 58 self.spark_controller.add_session(alias, endpoint, skip, properties)
59 except ValueError as e:
60 self.ipython_display.send_error("""Could not add session with
/opt/conda/lib/python3.5/site-packages/sparkmagic/livyclientlib/sparkcontroller.py in add_session(self, name, endpoint, skip_if_exists, properties)
79 session = self._livy_session(http_client, properties, self.ipython_display)
80 self.session_manager.add_session(name, session)
---> 81 session.start()
82
83 def get_session_id_for_client(self, name):
/opt/conda/lib/python3.5/site-packages/sparkmagic/livyclientlib/livysession.py in start(self)
148 else:
149 command = Command("sqlContext")
--> 150 (success, out) = command.execute(self)
151 if success:
152 self.ipython_display.writeln(u"SparkContext available as 'sc'.")
/opt/conda/lib/python3.5/site-packages/sparkmagic/livyclientlib/command.py in execute(self, session)
29 statement_id = -1
30 try:
---> 31 session.wait_for_idle()
32 data = {u"code": self.code}
33 response = session.http_client.post_statement(session.id, data)
/opt/conda/lib/python3.5/site-packages/sparkmagic/livyclientlib/livysession.py in wait_for_idle(self, seconds_to_wait)
238 .format(self.id, self.status)
239 self.logger.error(error)
--> 240 raise LivyUnexpectedStatusException(u'{} See logs:\n{}'.format(error, self.get_logs()))
241
242 if seconds_to_wait <= 0.0:
LivyUnexpectedStatusException: Session 0 unexpectedly reached final status 'error'. See logs:
Error I get from the Livy logs when creating a new session in the manage spark section of jupyter
17/02/10 13:06:08 INFO StateStore$: Using BlackholeStateStore for recovery.
17/02/10 13:06:08 INFO BatchSessionManager: Recovered 0 batch sessions. Next session id: 0
17/02/10 13:06:08 INFO InteractiveSessionManager: Recovered 0 interactive sessions. Next session id: 0
17/02/10 13:06:08 INFO InteractiveSessionManager: Heartbeat watchdog thread started.
17/02/10 13:06:08 INFO WebServer: Starting server on http://spark-master:8998
17/02/10 13:06:34 INFO InteractiveSession$: Creating LivyClient for sessionId: 0
17/02/10 13:06:34 WARN RSCConf: Your hostname, spark-master, resolves to a loopback address, but we couldn't find any external IP address!
17/02/10 13:06:34 WARN RSCConf: Set livy.rsc.rpc.server.address if you need to bind to another address.
17/02/10 13:06:35 INFO InteractiveSessionManager: Registering new session 0
17/02/10 13:06:35 INFO ContextLauncher: 17/02/10 13:06:35 INFO driver.RSCDriver: Starting RPC server...
17/02/10 13:06:35 INFO ContextLauncher: 17/02/10 13:06:35 WARN rsc.RSCConf: Set livy.rsc.rpc.server.address if you need to bind to another address.
17/02/10 13:06:35 INFO ContextLauncher: 17/02/10 13:06:35 INFO driver.RSCDriver: Received job request 3ca8a52b-8dd5-41f0-8151-a8201d72d422
17/02/10 13:06:35 INFO ContextLauncher: 17/02/10 13:06:35 INFO driver.RSCDriver: SparkContext not yet up, queueing job request.
17/02/10 13:06:36 INFO ContextLauncher: Setting default log level to "WARN".
17/02/10 13:06:36 INFO ContextLauncher: To adjust logging level use sc.setLogLevel(newLevel).
17/02/10 13:06:36 INFO ContextLauncher: 17/02/10 13:06:36 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
17/02/10 13:06:37 INFO ContextLauncher: 17/02/10 13:06:37 ERROR repl.PythonInterpreter: Process has died with 1
17/02/10 13:06:37 INFO RSCClient: Received result for 3ca8a52b-8dd5-41f0-8151-a8201d72d422
and get this output in the livy logs
I'm unable to put my finger on what the exact issue/fix is. I'm able to create a successful connection if I set my session to use the Scala language instead of the Python. Although I only get the error if I set the session language to python. If someone knows a solution to connecting a livy-repl pyspark session in Jupyter please let me know!
UPDATE
Livy still fails to create a PySpark session.
curl -v -X POST --data '{"kind": "pyspark"}' -H "Content-Type: application/json" example.com/sessions
The session state will go straight from "starting" to "failed". YARN logs on Resource Manager give the following right before the livy session fails.
To adjust logging level use sc.setLogLevel(newLevel).
17/02/26 05:02:25 WARN rsc.RSCConf: Your hostname, yarn-slave1, resolves to a loopback address, but we couldn't find any external IP address!
17/02/26 05:02:25 WARN rsc.RSCConf: Set livy.rsc.rpc.server.address if you need to bind to another address.
17/02/26 05:02:32 ERROR repl.PythonInterpreter: Process has died with 1
17/02/26 05:02:33 WARN yarn.YarnAllocator: Container marked as failed: container_1488085279373_0001_01_000002 on host: yarn-slave1. Exit status: 1. Diagnostics: Exception from container-launch.
Container id: container_1488085279373_0001_01_000002
Exit code: 1
Stack trace: ExitCodeException exitCode=1:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:582)
at org.apache.hadoop.util.Shell.run(Shell.java:479)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:773)
at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:212)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:302)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:82)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Container exited with a non-zero exit code 1
17/02/26 05:02:33 WARN yarn.ApplicationMaster: Reporter thread fails 1 time(s) in a row.
java.lang.IllegalStateException: RpcEnv already stopped.
at org.apache.spark.rpc.netty.Dispatcher.postMessage(Dispatcher.scala:159)
at org.apache.spark.rpc.netty.Dispatcher.postOneWayMessage(Dispatcher.scala:131)
at org.apache.spark.rpc.netty.NettyRpcEnv.send(NettyRpcEnv.scala:185)
at org.apache.spark.rpc.netty.NettyRpcEndpointRef.send(NettyRpcEnv.scala:508)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1$$anonfun$apply$7.apply(YarnAllocator.scala:531)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1$$anonfun$apply$7.apply(YarnAllocator.scala:512)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1.apply(YarnAllocator.scala:512)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1.apply(YarnAllocator.scala:442)
at scala.collection.Iterator$class.foreach(Iterator.scala:742)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1194)
at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
at org.apache.spark.deploy.yarn.YarnAllocator.processCompletedContainers(YarnAllocator.scala:442)
at org.apache.spark.deploy.yarn.YarnAllocator.allocateResources(YarnAllocator.scala:242)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$1.run(ApplicationMaster.scala:372)
17/02/26 05:02:40 WARN yarn.YarnAllocator: Container marked as failed: container_1488085279373_0001_01_000005 on host: yarn-slave1. Exit status: 1. Diagnostics: Exception from container-launch.
Container id: container_1488085279373_0001_01_000005
Exit code: 1
Stack trace: ExitCodeException exitCode=1:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:582)
at org.apache.hadoop.util.Shell.run(Shell.java:479)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:773)
at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:212)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:302)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:82)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Container exited with a non-zero exit code 1
17/02/26 05:02:40 WARN yarn.ApplicationMaster: Reporter thread fails 1 time(s) in a row.
java.lang.IllegalStateException: RpcEnv already stopped.
at org.apache.spark.rpc.netty.Dispatcher.postMessage(Dispatcher.scala:159)
at org.apache.spark.rpc.netty.Dispatcher.postOneWayMessage(Dispatcher.scala:131)
at org.apache.spark.rpc.netty.NettyRpcEnv.send(NettyRpcEnv.scala:185)
at org.apache.spark.rpc.netty.NettyRpcEndpointRef.send(NettyRpcEnv.scala:508)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1$$anonfun$apply$7.apply(YarnAllocator.scala:531)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1$$anonfun$apply$7.apply(YarnAllocator.scala:512)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1.apply(YarnAllocator.scala:512)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1.apply(YarnAllocator.scala:442)
at scala.collection.Iterator$class.foreach(Iterator.scala:742)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1194)
at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
at org.apache.spark.deploy.yarn.YarnAllocator.processCompletedContainers(YarnAllocator.scala:442)
at org.apache.spark.deploy.yarn.YarnAllocator.allocateResources(YarnAllocator.scala:242)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$1.run(ApplicationMaster.scala:372)
17/02/26 05:02:47 WARN yarn.YarnAllocator: Container marked as failed: container_1488085279373_0001_01_000006 on host: yarn-slave1. Exit status: 1. Diagnostics: Exception from container-launch.
Container id: container_1488085279373_0001_01_000006
Exit code: 1
Stack trace: ExitCodeException exitCode=1:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:582)
at org.apache.hadoop.util.Shell.run(Shell.java:479)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:773)
at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:212)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:302)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:82)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Container exited with a non-zero exit code 1
17/02/26 05:02:47 WARN yarn.ApplicationMaster: Reporter thread fails 1 time(s) in a row.
java.lang.IllegalStateException: RpcEnv already stopped.
at org.apache.spark.rpc.netty.Dispatcher.postMessage(Dispatcher.scala:159)
at org.apache.spark.rpc.netty.Dispatcher.postOneWayMessage(Dispatcher.scala:131)
at org.apache.spark.rpc.netty.NettyRpcEnv.send(NettyRpcEnv.scala:185)
at org.apache.spark.rpc.netty.NettyRpcEndpointRef.send(NettyRpcEnv.scala:508)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1$$anonfun$apply$7.apply(YarnAllocator.scala:531)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1$$anonfun$apply$7.apply(YarnAllocator.scala:512)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1.apply(YarnAllocator.scala:512)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1.apply(YarnAllocator.scala:442)
at scala.collection.Iterator$class.foreach(Iterator.scala:742)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1194)
at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
at org.apache.spark.deploy.yarn.YarnAllocator.processCompletedContainers(YarnAllocator.scala:442)
at org.apache.spark.deploy.yarn.YarnAllocator.allocateResources(YarnAllocator.scala:242)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$1.run(ApplicationMaster.scala:372)
17/02/26 05:02:53 WARN yarn.YarnAllocator: Container marked as failed: container_1488085279373_0001_01_000007 on host: yarn-slave1. Exit status: 1. Diagnostics: Exception from container-launch.
Container id: container_1488085279373_0001_01_000007
Exit code: 1
Stack trace: ExitCodeException exitCode=1:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:582)
at org.apache.hadoop.util.Shell.run(Shell.java:479)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:773)
at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:212)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:302)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:82)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Container exited with a non-zero exit code 1
17/02/26 05:02:53 WARN yarn.ApplicationMaster: Reporter thread fails 1 time(s) in a row.
java.lang.IllegalStateException: RpcEnv already stopped.
at org.apache.spark.rpc.netty.Dispatcher.postMessage(Dispatcher.scala:159)
at org.apache.spark.rpc.netty.Dispatcher.postOneWayMessage(Dispatcher.scala:131)
at org.apache.spark.rpc.netty.NettyRpcEnv.send(NettyRpcEnv.scala:185)
at org.apache.spark.rpc.netty.NettyRpcEndpointRef.send(NettyRpcEnv.scala:508)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1$$anonfun$apply$7.apply(YarnAllocator.scala:531)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1$$anonfun$apply$7.apply(YarnAllocator.scala:512)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1.apply(YarnAllocator.scala:512)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$processCompletedContainers$1.apply(YarnAllocator.scala:442)
at scala.collection.Iterator$class.foreach(Iterator.scala:742)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1194)
at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
at org.apache.spark.deploy.yarn.YarnAllocator.processCompletedContainers(YarnAllocator.scala:442)
at org.apache.spark.deploy.yarn.YarnAllocator.allocateResources(YarnAllocator.scala:242)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$1.run(ApplicationMaster.scala:372)
spark-defaults.conf
spark.yarn.appMasterEnv.PYSPARK_PYTHON python2
core-site.xml
<property>
<name>hadoop.proxyuser.livy.groups</name>
<value>*</value>
</property>
<property>
<name>hadoop.proxyuser.livy.hosts</name>
<value>*</value>
</property>
livy.conf
livy.server.host = 0.0.0.0
livy.server.port = 8998
livy.spark.master = yarn
livy.spark.deployMode = cluster

Answer 1

I was able to reproduce this issue.
The problem seems to be that spark 2.0.0 and livy have incompatible pyspark versions. If you update spark to the most recent version(currently 2.1.0) the pyspark versions can communicate and the spark session is created without a hitch.

Answer 2

I had faced similar issue even with spark 2.1.1 and livy. Livy-session status went to "error" from "starting". Turned out that I was using Java-7 while Livy and Spark need Java-8. Solved my issue.

Answer 3

I was facing a similar issue. Turns out the culprit was livy version. When replaced cloudera livy with apache livy-0.6.0-incubating version, the problem was solved; and I was able to create pyspark kind session on livy.