ERROR JupyterSparkMonitorListener: Exception creating socket: java.lang.NumberFormatException: For input string: "ERRORNOTFOUND"

[tikr7]

Hi there!

I installed the sparkmonitor extension into a dockerimage that is based on jupyterhub:

FROM jupyterhub/k8s-singleuser-sample:1.2.0 

RUN pip install pyspark==3.2.0
RUN pip install delta-spark==1.1.0

USER root
RUN apt update
RUN apt install default-jdk -y
RUN apt install nodejs -y
#USER ${NB_UID}
RUN java --version

RUN pip install sparkmonitor # install the extension

# set up an ipython profile and add our kernel extension to it
#ipython profile create # if it does not exist
RUN echo "c.InteractiveShellApp.extensions.append('sparkmonitor.kernelextension')" >>  $(ipython profile locate default)/ipython_kernel_config.py

# For use with jupyter notebook install and enable the nbextension
RUN jupyter nbextension install sparkmonitor --py
RUN jupyter nbextension enable  sparkmonitor --py

# The jupyterlab extension is automatically enabled

USER ${NB_UID}

When I opened the SparkSessions with:

from pyspark.sql import SparkSession
spark = SparkSession.builder\
        .config("spark.extraListeners", "sparkmonitor.listener.JupyterSparkMonitorListener") \
        .config("spark.driver.extraClassPath", "/opt/conda/lib/python3.9/site-packages/sparkmonitor/listener_2.12.jar") \
        .getOrCreate()

I get the following error:

WARNING: An illegal reflective access operation has occurred
WARNING: Illegal reflective access by org.apache.spark.unsafe.Platform (file:/opt/conda/lib/python3.9/site-packages/pyspark/jars/spark-unsafe_2.12-3.2.0.jar) to constructor java.nio.DirectByteBuffer(long,int)
WARNING: Please consider reporting this to the maintainers of org.apache.spark.unsafe.Platform
WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations
WARNING: All illegal access operations will be denied in a future release
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
22/04/01 11:14:22 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
22/04/01 11:14:25 ERROR JupyterSparkMonitorListener: Exception creating socket: 
java.lang.NumberFormatException: For input string: "ERRORNOTFOUND"
	at java.base/java.lang.NumberFormatException.forInputString(NumberFormatException.java:65)
	at java.base/java.lang.Integer.parseInt(Integer.java:652)
	at java.base/java.lang.Integer.parseInt(Integer.java:770)
	at scala.collection.immutable.StringLike.toInt(StringLike.scala:304)
	at scala.collection.immutable.StringLike.toInt$(StringLike.scala:304)
	at scala.collection.immutable.StringOps.toInt(StringOps.scala:33)
	at sparkmonitor.listener.JupyterSparkMonitorListener.startConnection(CustomListener.scala:63)
	at sparkmonitor.listener.JupyterSparkMonitorListener.<init>(CustomListener.scala:48)
	at java.base/jdk.internal.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
	at java.base/jdk.internal.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
	at java.base/jdk.internal.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
	at java.base/java.lang.reflect.Constructor.newInstance(Constructor.java:490)
	at org.apache.spark.util.Utils$.$anonfun$loadExtensions$1(Utils.scala:2876)
	at scala.collection.TraversableLike.$anonfun$flatMap$1(TraversableLike.scala:293)
	at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
	at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
	at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
	at scala.collection.TraversableLike.flatMap(TraversableLike.scala:293)
	at scala.collection.TraversableLike.flatMap$(TraversableLike.scala:290)
	at scala.collection.AbstractTraversable.flatMap(Traversable.scala:108)
	at org.apache.spark.util.Utils$.loadExtensions(Utils.scala:2868)
	at org.apache.spark.SparkContext.$anonfun$setupAndStartListenerBus$1(SparkContext.scala:2538)
	at org.apache.spark.SparkContext.$anonfun$setupAndStartListenerBus$1$adapted(SparkContext.scala:2537)
	at scala.Option.foreach(Option.scala:407)
	at org.apache.spark.SparkContext.setupAndStartListenerBus(SparkContext.scala:2537)
	at org.apache.spark.SparkContext.<init>(SparkContext.scala:641)
	at org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:58)
	at java.base/jdk.internal.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
	at java.base/jdk.internal.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
	at java.base/jdk.internal.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
	at java.base/java.lang.reflect.Constructor.newInstance(Constructor.java:490)
	at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:247)
	at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
	at py4j.Gateway.invoke(Gateway.java:238)
	at py4j.commands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:80)
	at py4j.commands.ConstructorCommand.execute(ConstructorCommand.java:69)
	at py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)
	at py4j.ClientServerConnection.run(ClientServerConnection.java:106)
	at java.base/java.lang.Thread.run(Thread.java:829)
22/04/01 11:14:25 ERROR JupyterSparkMonitorListener: Exception sending socket message: 
java.lang.NullPointerException
	at sparkmonitor.listener.JupyterSparkMonitorListener.send(CustomListener.scala:53)
	at sparkmonitor.listener.JupyterSparkMonitorListener.onExecutorAdded(CustomListener.scala:652)
	at org.apache.spark.scheduler.SparkListenerBus.doPostEvent(SparkListenerBus.scala:63)
	at org.apache.spark.scheduler.SparkListenerBus.doPostEvent$(SparkListenerBus.scala:28)
	at org.apache.spark.scheduler.AsyncEventQueue.doPostEvent(AsyncEventQueue.scala:37)
	at org.apache.spark.scheduler.AsyncEventQueue.doPostEvent(AsyncEventQueue.scala:37)
	at org.apache.spark.util.ListenerBus.postToAll(ListenerBus.scala:117)
	at org.apache.spark.util.ListenerBus.postToAll$(ListenerBus.scala:101)
	at org.apache.spark.scheduler.AsyncEventQueue.super$postToAll(AsyncEventQueue.scala:105)
	at org.apache.spark.scheduler.AsyncEventQueue.$anonfun$dispatch$1(AsyncEventQueue.scala:105)
	at scala.runtime.java8.JFunction0$mcJ$sp.apply(JFunction0$mcJ$sp.java:23)
	at scala.util.DynamicVariable.withValue(DynamicVariable.scala:62)
	at org.apache.spark.scheduler.AsyncEventQueue.org$apache$spark$scheduler$AsyncEventQueue$$dispatch(AsyncEventQueue.scala:100)
	at org.apache.spark.scheduler.AsyncEventQueue$$anon$2.$anonfun$run$1(AsyncEventQueue.scala:96)
	at org.apache.spark.util.Utils$.tryOrStopSparkContext(Utils.scala:1404)
	at org.apache.spark.scheduler.AsyncEventQueue$$anon$2.run(AsyncEventQueue.scala:96)
22/04/01 11:14:26 ERROR JupyterSparkMonitorListener: Exception sending socket message: 
java.lang.NullPointerException
	at sparkmonitor.listener.JupyterSparkMonitorListener.send(CustomListener.scala:53)
	at sparkmonitor.listener.JupyterSparkMonitorListener.onApplicationStart(CustomListener.scala:147)
	at org.apache.spark.scheduler.SparkListenerBus.doPostEvent(SparkListenerBus.scala:55)
	at org.apache.spark.scheduler.SparkListenerBus.doPostEvent$(SparkListenerBus.scala:28)
	at org.apache.spark.scheduler.AsyncEventQueue.doPostEvent(AsyncEventQueue.scala:37)
	at org.apache.spark.scheduler.AsyncEventQueue.doPostEvent(AsyncEventQueue.scala:37)
	at org.apache.spark.util.ListenerBus.postToAll(ListenerBus.scala:117)
	at org.apache.spark.util.ListenerBus.postToAll$(ListenerBus.scala:101)
	at org.apache.spark.scheduler.AsyncEventQueue.super$postToAll(AsyncEventQueue.scala:105)
	at org.apache.spark.scheduler.AsyncEventQueue.$anonfun$dispatch$1(AsyncEventQueue.scala:105)
	at scala.runtime.java8.JFunction0$mcJ$sp.apply(JFunction0$mcJ$sp.java:23)
	at scala.util.DynamicVariable.withValue(DynamicVariable.scala:62)
	at org.apache.spark.scheduler.AsyncEventQueue.org$apache$spark$scheduler$AsyncEventQueue$$dispatch(AsyncEventQueue.scala:100)
	at org.apache.spark.scheduler.AsyncEventQueue$$anon$2.$anonfun$run$1(AsyncEventQueue.scala:96)
	at org.apache.spark.util.Utils$.tryOrStopSparkContext(Utils.scala:1404)
	at org.apache.spark.scheduler.AsyncEventQueue$$anon$2.run(AsyncEventQueue.scala:96)

Does somebody have any hints how I can fix that?

[krishnan-r]

This happens because the kernel extension also sets an environment variable with the socket port number that the sparklistener connects to, from the JVM. (here)

You need to call the configure method on the module, or install it as a kernelextension to set this environment variable.

[tikr7]

thanks for the tip, @krishnan-r

How could it look like?

[nvkvc996]

Hey @krishnan-r, I am facing the same issue when using the sparkmonitor in our jupyter docker image with spark installed on it, can you please be more specific on how we can resolve this issue?