IllegalArgumentException with Spark 1.6 - apache-spark

I'm running Spark 1.6.0 on CDH 5.7 and I've upgraded my original application from 1.4.1 to 1.6.0. When I try to run my application (which previously worked fine) I get the following error:
Exception in thread "main" java.lang.IllegalArgumentException: requirement failed
at scala.Predef$.require(Predef.scala:221)
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$6$$anonfun$apply$3.apply(Client.scala:473)
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$6$$anonfun$apply$3.apply(Client.scala:471)
at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$6.apply(Client.scala:471)
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$6.apply(Client.scala:469)
at scala.collection.immutable.List.foreach(List.scala:318)
at org.apache.spark.deploy.yarn.Client.prepareLocalResources(Client.scala:469)
at org.apache.spark.deploy.yarn.Client.createContainerLaunchContext(Client.scala:725)
at org.apache.spark.deploy.yarn.Client.submitApplication(Client.scala:143)
at org.apache.spark.deploy.yarn.Client.run(Client.scala:1023)
at org.apache.spark.deploy.yarn.Client$.main(Client.scala:1083)
at org.apache.spark.deploy.yarn.Client.main(Client.scala)
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 org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:731)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:181)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:206)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:121)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
I submit the application with:
--jars is a comma-separated list of jars (with absolute paths)
--files is a comma-separated list of files (with absolute paths)
--driver-class-path is a colon-separated list of resources (without the full path, just the file names)
I have tried it with full paths for the driver (and executor) class paths, but that gives me the same issue. All files and jars submitted with the app exist, I checked.
Could this be related to the issue with duplicates in the distributed cache or is this another issue?
From the source code I see that the only calls to require without a custom message (as in the stack trace) are related to the distribute() method. If so, how can I run applications without upgrading Spark?

This is the exception which results from having the same path/URI appear twice in the argument to the --files option.

Related

Databricks PySpark with PEX: how can I configure a PySpark job on Databricks using PEX for dependencies?

I am attempting to create a PySpark job via the Databricks UI (with spark-submit) using the spark-submit parameters below (dependencies are on the PEX file), but I am getting an exception that the PEX file does not exist. It's my understanding that the --files option puts the file in the working directory of the driver & every executor, so I am confused as to why I am encountering this issue.
Config
[
"--files","s3://some_path/my_pex.pex",
"--conf","spark.pyspark.python=./my_pex.pex",
"s3://some_path/main.py",
"--some_arg","2022-08-01"
]
Standard Error
OpenJDK 64-Bit Server VM warning: ignoring option MaxPermSize=512m; support was removed in 8.0
Warning: Ignoring non-Spark config property: libraryDownload.sleepIntervalSeconds
Warning: Ignoring non-Spark config property: libraryDownload.timeoutSeconds
Warning: Ignoring non-Spark config property: eventLog.rolloverIntervalSeconds
Exception in thread "main" java.io.IOException: Cannot run program "./my_pex.pex": error=2, No such file or directory
at java.lang.ProcessBuilder.start(ProcessBuilder.java:1048)
at org.apache.spark.deploy.PythonRunner$.main(PythonRunner.scala:97)
at org.apache.spark.deploy.PythonRunner.main(PythonRunner.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:951)
at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:180)
at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:203)
at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:90)
at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:1039)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:1048)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.io.IOException: error=2, No such file or directory
at java.lang.UNIXProcess.forkAndExec(Native Method)
at java.lang.UNIXProcess.<init>(UNIXProcess.java:247)
at java.lang.ProcessImpl.start(ProcessImpl.java:134)
at java.lang.ProcessBuilder.start(ProcessBuilder.java:1029)
... 14 more
What I have tried
Given that the PEX file doesn't seem to be visible, I have tried adding it via the following ways:
Adding the PEX via the --files option in Spark submit
Adding the PEX via the the spark.files config when starting up the actual cluster
Putting the PEX in DBFS (as opposed to s3)
Playing around with the configs (e.g. using spark.pyspark.driver.python instead of spark.pyspark.python)
Note: given that instructions at the bottom of this page, I believe PEX should work on Databricks; I'm just not sure as to the right configs: https://www.databricks.com/blog/2020/12/22/how-to-manage-python-dependencies-in-pyspark.html
Note also, the following spark submit command works on AWS EMR:
'HadoopJarStep': {
'Jar': 'command-runner.jar',
'Args': [
"spark-submit",
"--deploy-mode", "cluster",
"--master", "yarn",
"--files", "s3://some_path/my_pex.pex",
"--conf", "spark.pyspark.driver.python=./my_pex.pex",
"--conf", "spark.executorEnv.PEX_ROOT=./tmp",
"--conf", "spark.yarn.appMasterEnv.PEX_ROOT=./tmp",
"s3://some_path/main.py",
"--some_arg", "some-val"
]
Any help would be much appreciated, thanks.

Spark Submit error when running a JAR from Azure Databricks

I'm trying to issue spark submit from Azure Databricks jobs scheduler, currently stuck with the below error. Error says: File file:/tmp/spark-events does not exist. I need some pointers to understand do we need to create this directory in Azure blob location(which is my storage Layer) or in Azure DBFS location.
As per the below link, not so clear where to create the directory when running the spark-submit from Azure Databricks jobs scheduler.
SparkContext Error - File not found /tmp/spark-events does not exist
Error:
OpenJDK 64-Bit Server VM warning: ignoring option MaxPermSize=512m; support was removed in 8.0
Warning: Ignoring non-Spark config property: eventLog.rolloverIntervalSeconds
Exception in thread "main" java.lang.ExceptionInInitializerError
at com.dta.dl.ct.qm.hbase.reverse.pipeline.HBaseVehicleMasterLoad.main(HBaseVehicleMasterLoad.scala)
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 org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:845)
at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:161)
at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:184)
at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:86)
at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:920)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:929)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.io.FileNotFoundException: File file:/tmp/spark-events does not exist
at org.apache.hadoop.fs.RawLocalFileSystem.deprecatedGetFileStatus(RawLocalFileSystem.java:611)
at org.apache.hadoop.fs.RawLocalFileSystem.getFileLinkStatusInternal(RawLocalFileSystem.java:824)
at org.apache.hadoop.fs.RawLocalFileSystem.getFileStatus(RawLocalFileSystem.java:601)
at org.apache.hadoop.fs.FilterFileSystem.getFileStatus(FilterFileSystem.java:421)
at org.apache.spark.scheduler.EventLoggingListener.start(EventLoggingListener.scala:97)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:580)
at com.dta.dl.ct.qm.hbase.reverse.pipeline.HBaseVehicleMasterLoad$.<init>(HBaseVehicleMasterLoad.scala:32)
at com.dta.dl.ct.qm.hbase.reverse.pipeline.HBaseVehicleMasterLoad$.<clinit>(HBaseVehicleMasterLoad.scala)
... 13 more
You need to create this folder on the driver node before collecting event logs (that's by design).
To do so, one way could be adding the property spark.history.fs.logDirectory (present at the spark-defaults.conf file) on a global init script as described here.
Please make sure that the folder defined on that property exist and can be accessed from the driver node

Directory expansion does not work in standalone deployment mode : Apache Spark

I'm trying to deploy a spark streaming consuming Kafka topic job on a standalone spark cluster using the following command:
./bin/spark-submit --class MaxwellCdc.MaxwellSreaming
~/cdc/cdc_2.11-0.1.jar --jars ~/cdc/kafka_2.11-0.10.0.1.jar,
~/cdc/kafka-clients-0.10.0.1.jar,~/cdc/mysql-connector-java-5.1.12.jar,
~/cdc/spark-streaming-kafka-0-10_2.11-2.2.1.jar
and getting this exception:
Exception in thread "main" java.lang.NoClassDefFoundError:
org/apache/kafka/common/serialization/StringDeserializer
at MaxwellCdc.MaxwellSreaming$.main(MaxwellSreaming.scala:30)
at MaxwellCdc.MaxwellSreaming.main(MaxwellSreaming.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:775)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:180)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:205)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:119)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.ClassNotFoundException:
org.apache.kafka.common.serialization.StringDeserializer
at java.net.URLClassLoader.findClass(URLClassLoader.java:381)
at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
Any help would be appreciated.
Quoting from the documentation:
When using spark-submit, the application jar along with any jars
included with the --jars option will be automatically transferred to
the cluster. URLs supplied after --jars must be separated by commas.
That list is included in the driver and executor classpaths.
Directory expansion does not work with --jars..
What is directory expansion?
Expanding a file name means converting a relative file name to an absolute one. Since this is done relative to a default directory, you must specify the default directory name as well as the file name to be expanded. It also involves expanding abbreviations like ~/.
Therefore, try providing the absolute path for all the jars that are being provided with --jars option. I hope this helps.

adding multiple jars in Oozie-Spark action

I'm using HDP2.6. where is installed oozie 4.2. and Spark2.
After I tracked Hortonworks guide on this site: https://docs.hortonworks.com/HDPDocuments/HDP2/HDP-2.6.1/bk_spark-component-guide/content/ch_oozie-spark-action.html for adding libs for Spark2 in 4.2. version of Oozie.
After I submit the job with this add-on:
oozie.action.sharelib.for.spark=spark2
The error I'm getting is this:
2017-07-19 12:36:53,271 WARN SparkActionExecutor:523 - SERVER[] USER[admin] GROUP[-] TOKEN[] APP[Workflow2] JOB[0000012-170717153234639-oozie-oozi-W] ACTION[0000012-170717153234639-oozie-oozi-W#spark_1] Launcher ERROR, reason: Main class [org.apache.oozie.action.hadoop.SparkMain], main() threw exception, Attempt to add (hdfs://:8020/user/oozie/share/lib/lib_20170613110051/oozie/aws-java-sdk-core-1.10.6.jar) multiple times to the distributed cache.
2017-07-19 12:36:53,275 WARN SparkActionExecutor:523 - SERVER[] USER[admin] GROUP[-] TOKEN[] APP[Workflow2] JOB[0000012-170717153234639-oozie-oozi-W] ACTION[0000012-170717153234639-oozie-oozi-W#spark_1] Launcher exception: Attempt to add (hdfs://:8020/user/oozie/share/lib/lib_20170613110051/oozie/aws-java-sdk-core-1.10.6.jar) multiple times to the distributed cache.
java.lang.IllegalArgumentException: Attempt to add (hdfs://:8020/user/oozie/share/lib/lib_20170613110051/oozie/aws-java-sdk-core-1.10.6.jar) multiple times to the distributed cache.
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$13$$anonfun$apply$8.apply(Client.scala:629)
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$13$$anonfun$apply$8.apply(Client.scala:620)
at scala.collection.mutable.ArraySeq.foreach(ArraySeq.scala:74)
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$13.apply(Client.scala:620)
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$13.apply(Client.scala:619)
at scala.collection.immutable.List.foreach(List.scala:381)
at org.apache.spark.deploy.yarn.Client.prepareLocalResources(Client.scala:619)
at org.apache.spark.deploy.yarn.Client.createContainerLaunchContext(Client.scala:892)
at org.apache.spark.deploy.yarn.Client.submitApplication(Client.scala:171)
at org.apache.spark.deploy.yarn.Client.run(Client.scala:1228)
at org.apache.spark.deploy.yarn.Client$.main(Client.scala:1287)
at org.apache.spark.deploy.yarn.Client.main(Client.scala)
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:497)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:745)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:187)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:212)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:126)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
at org.apache.oozie.action.hadoop.SparkMain.runSpark(SparkMain.java:311)
at org.apache.oozie.action.hadoop.SparkMain.run(SparkMain.java:232)
at org.apache.oozie.action.hadoop.LauncherMain.run(LauncherMain.java:58)
at org.apache.oozie.action.hadoop.SparkMain.main(SparkMain.java:62)
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:497)
at org.apache.oozie.action.hadoop.LauncherMapper.map(LauncherMapper.java:239)
at org.apache.hadoop.mapred.MapRunner.run(MapRunner.java:54)
at org.apache.hadoop.mapred.MapTask.runOldMapper(MapTask.java:453)
at org.apache.hadoop.mapred.MapTask.run(MapTask.java:343)
at org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:170)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1866)
at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:164)
I have read that new Spark2 will not work with Spark 2.1 (via oozie anyway) due to a change in how Spark handles multiple files found in distributed cache, as mentioned here: see here
Keep in mind that I'm using Ambari and HDP2.6. How can I deal with this?
You need to check the content of the oozie directory and spark2 directory into the Oozie sharelib. If there are any jars present into both, just remove them from one place and try again. Also, do execute the oozie admin sharelub update command to update it.
Hope this will help you.

I am getting the below error while trying to execute spark submit using oozie on emr

I am running on cluster mode. The apacheds-kerberos-codec-2.0.0-M15.jar is present in multiple places in oozie/share/lib/lib*/spark and oozie/share/lib/lib*/oozie. Is this an environmental issue ?
ava.lang.IllegalArgumentException: Attempt to add (hdfs://ip-172-20-10-53.ec2.internal:8020/user/oozie/share/lib/lib_20170208121307/oozie/apacheds-kerberos-codec-2.0.0-M15.jar) multiple times to the distributed cache.
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$11$$anonfun$apply$8.apply(Client.scala:608)
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$11$$anonfun$apply$8.apply(Client.scala:599)
at scala.collection.mutable.ArraySeq.foreach(ArraySeq.scala:74)
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$11.apply(Client.scala:599)
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$11.apply(Client.scala:598)
at scala.collection.immutable.List.foreach(List.scala:381)
at org.apache.spark.deploy.yarn.Client.prepareLocalResources(Client.scala:598)
at org.apache.spark.deploy.yarn.Client.createContainerLaunchContext(Client.scala:868)
at org.apache.spark.deploy.yarn.Client.submitApplication(Client.scala:170)
at org.apache.spark.deploy.yarn.Client.run(Client.scala:1154)
at org.apache.spark.deploy.yarn.Client$.main(Client.scala:1213)
at org.apache.spark.deploy.yarn.Client.main(Client.scala)
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 org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:738)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:187)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:212)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:126)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
at org.apache.oozie.action.hadoop.SparkMain.runSpark(SparkMain.java:338)
at org.apache.oozie.action.hadoop.SparkMain.run(SparkMain.java:257)
at org.apache.oozie.action.hadoop.LauncherMain.run(LauncherMain.java:60)
at org.apache.oozie.action.hadoop.SparkMain.main(SparkMain.java:78)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.oozie.action.hadoop.LauncherMapper.map(LauncherMapper.java:232)
at org.apache.hadoop.mapred.MapRunner.run(MapRunner.java:54)
at org.apache.hadoop.mapred.MapTask.runOldMapper(MapTask.java:455)
at org.apache.hadoop.mapred.MapTask.run(MapTask.java:344)
at org.apache.hadoop.mapred.LocalContainerLauncher$EventHandler.runSubtask(LocalContainerLauncher.java:380)
at org.apache.hadoop.mapred.LocalContainerLauncher$EventHandler.runTask(LocalContainerLauncher.java:301)
at org.apache.hadoop.mapred.LocalContainerLauncher$EventHandler.access$200(LocalContainerLauncher.java:187)
at org.apache.hadoop.mapred.LocalContainerLauncher$EventHandler$1.run(LocalContainerLauncher.java:230)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
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)
It appears that the oozie sharelib and the spark sharelib directory share the same jars, and running a spark workflow imports both directories, which hadoop-3 code base doesn't like.
I've had to reorganize the oozie sharelib directory to only have oozie specific jars such that there are no duplicates between both oozie and spark sharelib dirs:
export HADOOP_USER_NAME=oozie
hdfs dfs -mv /user/oozie/share/lib/lib_20170222143042/oozie /user/oozie/share/lib/lib_20170222143042/oozie.old
hdfs dfs -mkdir /user/oozie/share/lib/lib_20170222143042/oozie
hdfs dfs -cp /user/oozie/share/lib/lib_20170222143042/oozie.old/oozie-hadoop-utils-hadoop-2-4.3.0.jar /user/oozie/share/lib/lib_20170222143042/oozie
hdfs dfs -cp /user/oozie/share/lib/lib_20170222143042/oozie.old/oozie-sharelib-oozie-4.3.0.jar /user/oozie/share/lib/lib_20170222143042/oozie
This fixes the immediate issue of being able to run spark workflows from oozie, but I'm not sure if this affects non-spark workflows.
I have an oozie job that starts a spark job, running in Amazon EMR. I got the same error when the EMR Hadoop setup has one instance for the master and one instance for the slaves. When I increased the amount of instances for the slaves to two, everything worked as expected.

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