I am trying to adapt some code from Apache Zeppelin for a personal project. The idea is to pass Scala source code to be executed in Spark. Everything is working fine, until when I try to use an external jar. For this, I call
SparkConf#setJars(externalJars);
And I can see in the logs that my jar was added:
Added JAR file:/Users/.../lsa.jar at spark://192.168.0.16:60376/jars/lsa.jar with timestamp 1470532825125
And when I check the UI of Spark http://192.168.0.16:4040/environment/ I can see my jar was added with an entry under Classpath Entries:
spark://192.168.0.16:60376/jars/lsa.jar
But when I try to import a class from the JAR I get:
<console>:25: error: object cloudera is not a member of package com
import com.cloudera.datascience.lsa._
^
Does anyone have an idea about what I am missing ?
Edit: I also tried to add the JAR via the spark-defaults.conf:
spark.driver.extraClassPath /Users/.../lsa.jar
but no luck.
I can see here the doc says:
Instead, please set this through the --driver-class-path command line option or in your default properties file.
I don't know where to pass this option, should I do it for the master only or for each slave ?
Thanks in advance
Related
I am trying to run the spark-submit command on my Hadoop cluster Here is a summary of my Hadoop Cluster:
The cluster is built using 5 VirtualBox VM's connected on an internal network
There is 1 namenode and 4 datanodes created.
All the VM's were built from the Bitnami Hadoop Stack VirtualBox image
I am trying to run one of the spark examples using the following spark-submit command
spark-submit --class org.apache.spark.examples.SparkPi $SPARK_HOME/examples/jars/spark-examples_2.12-3.0.3.jar 10
I get the following error:
[2022-07-25 13:32:39.253]Container exited with a non-zero exit code 1. Error file: prelaunch.err.
Last 4096 bytes of prelaunch.err :
Last 4096 bytes of stderr :
Error: Could not find or load main class org.apache.spark.deploy.yarn.ExecutorLauncher
I get the same error when trying to run a script with PySpark.
I have tried/verified the following:
environment variables: HADOOP_HOME, SPARK_HOME and HADOOP_CONF_DIR have been set in my .bashrc file
SPARK_DIST_CLASSPATH and HADOOP_CONF_DIR have been defined in spark-env.sh
Added spark.master yarn, spark.yarn.stagingDir hdfs://hadoop-namenode:8020/user/bitnami/sparkStaging and spark.yarn.jars hdfs://hadoop-namenode:8020/user/bitnami/spark/jars/ in spark-defaults.conf
I have uploaded the jars into hdfs (i.e. hadoop fs -put $SPARK_HOME/jars/* hdfs://hadoop-namenode:8020/user/bitnami/spark/jars/ )
The logs accessible via the web interface (i.e. http://hadoop-namenode:8042 ) do not provide any further details about the error.
This section of the Spark documentation seems relevant to the error since the YARN libraries should be included, by default, but only if you've installed the appropriate Spark version
For with-hadoop Spark distribution, since it contains a built-in Hadoop runtime already, by default, when a job is submitted to Hadoop Yarn cluster, to prevent jar conflict, it will not populate Yarn’s classpath into Spark. To override this behavior, you can set spark.yarn.populateHadoopClasspath=true. For no-hadoop Spark distribution, Spark will populate Yarn’s classpath by default in order to get Hadoop runtime. For with-hadoop Spark distribution, if your application depends on certain library that is only available in the cluster, you can try to populate the Yarn classpath by setting the property mentioned above. If you run into jar conflict issue by doing so, you will need to turn it off and include this library in your application jar.
https://spark.apache.org/docs/latest/running-on-yarn.html#preparations
Otherwise, yarn.application.classpath in yarn-site.xml refers to local filesystem paths in each of ResourceManager servers where JARs are available for all YARN applications (spark.yarn.jars or extra packages should get layered onto this)
Another problem could be file permissions. You probably shouldn't put Spark jars into an HDFS user folder if they're meant to be used by all users. Typically, I'd put it under hdfs:///apps/spark/<version>, then give that 744 HDFS permissions
In the Spark / YARN UI, it should show the complete classpath of the application for further debugging
I figured out why I was getting this error. It turns out that I made an error while specifying spark.yarn.jars in spark-defaults.conf
The value of this property must be
hdfs://hadoop-namenode:8020/user/bitnami/spark/jars/*
instead of
hdfs://hadoop-namenode:8020/user/bitnami/spark/jars/
i.e. Basically, we need to specify the jar files as the value to this property and not the folder containing the jar files.
I am running spark-submit to run on Kubernetes (Spark 2.3). My problem is that the InitContainer does not download my jar file if it's specified as an s3a:// path but does work if I put my jar on an HTTP server and use http://. The spark driver fails, of course, because it can't find my Class (and the jar file in fact is not in the image).
I have tried two approaches:
specifying the s3a path to jar as the argument to spark-submit and
using --jars to specify the jar file's location on s3a, but both fail in the same way.
edit: also, using local:///home/myuser/app.jar does not work with the same symptoms.
On a failed run (dependency on s3a), I logged into the container and found the directory /var/spark-data/spark-jars/ to be empty. The init-container logs don't indicate any type of error.
Questions:
What is the correct way to specify remote dependencies on S3A?
Is S3A not supported yet? Only http(s)?
Any suggestions on how to further debug the InitContainer to determine why the download doesn't happen?
I want to do some ip to location computation on spark, after exploring the net ,find IPLocator https://github.com/miraclesu/IPLocator,
the IP to location need to use a file which contains the mapping information.
After packaging the jar, I can run it through on using local java, the package just runs with the IPLocator.jar and qqwry.dat in the same directory.
But I want to use this jar using spark , I tryed to use --jars IPLocator.jar qqwry.dat when starting spark-shell, but when launching , the functions still can not read get the file .
the file reading code is like
QQWryFile.class.getClassLoader().getResource("qqwry.dat")
I also tried to package qqwry.dat file into the jar, and It did not work.
You need to use --files and then SparkFiles.get inside of your program
Try to use comma delimitor and check if IPLocator.jar and qqwry.dat are distributed to spark staging folder(.sparkStaging/application_xxx).
--jars IPLocator.jar,qqwry.dat
I have been following this tutorial in order to set up Zeppelin on a Spark cluster (version 1.5.2) in HDInsight, on Linux. Everything worked fine, I have managed to successfully connect to the Zeppelin notebook through the SSH tunnel. However, when I try to run any kind of paragraph, the first time I get the following error:
java.io.IOException: No FileSystem for scheme: wasb
After getting this error, if I try to rerun the paragraph, I get another error:
java.net.SocketException: Broken pipe
at java.net.SocketOutputStream.socketWrite0(Native Method)
These errors occur regardless of the code I enter, even if there is no reference to the hdfs. What I'm saying is that I get the "No FileSystem" error even for a trivial scala expression, such as parallelize.
Is there a missing configuration step?
I am download the tar ball that the script that you pointed to as I type. But want I am guessing is that your zeppelin install and spark install are not complete to work with wasb. In order to get spark to work with wasb you need to add some jars to the Class path. To do this you need to add something like this to your spark-defaults.conf (the paths might be different in HDInsights, this is from HDP on IaaS)
spark.driver.extraClassPath /usr/hdp/2.3.0.0-2557/hadoop/lib/azure-storage-2.2.0.jar:/usr/hdp/2.3.0.0-2557/hadoop/lib/microsoft-windowsazure-storage-sdk-0.6.0.jar:/usr/hdp/2.3.0.0-2557/hadoop/hadoop-azure-2.7.1.2.3.0.0-2557.jar
spark.executor.extraClassPath /usr/hdp/2.3.0.0-2557/hadoop/lib/azure-storage-2.2.0.jar:/usr/hdp/2.3.0.0-2557/hadoop/lib/microsoft-windowsazure-storage-sdk-0.6.0.jar:/usr/hdp/2.3.0.0-2557/hadoop/hadoop-azure-2.7.1.2.3.0.0-2557.jar
Once you have spark working with wasb, or next step is make those sames jar in zeppelin class path. A good way to test your setup is make a notebook that prints your env vars and class path.
sys.env.foreach(println(_))
val cl = ClassLoader.getSystemClassLoader
cl.asInstanceOf[java.net.URLClassLoader].getURLs.foreach(println)
Also looking at the install script, it trying to pull the zeppelin jar from wasb, you might want to change that config to somewhere else while you try some of these changes out. (zeppelin.sh)
export SPARK_YARN_JAR=wasb:///apps/zeppelin/zeppelin-spark-0.5.5-SNAPSHOT.jar
I hope this helps, if you are still have problems I have some other ideas, but would start with these first.
I have a problem when i try to submit my application with spark submit command:
/bin/spark-submit --class MyClass myjar.jar
I set master url programmatically.
I get following error:
Exception in thread "main" java.lang.NoSuchMethodError: org.apache.commons.configuration.XMLConfiguration.setEntityResolver(Lorg/xml/sax/EntityResolver;)V
when i run my program on IDE all work correctly. This problem does not arise.
It looks like the jar you are submitting may not have all of the dependencies it requires in it. The solution to this is to build an assembly jar, see https://maven.apache.org/plugins/maven-assembly-plugin/usage.html (for maven), or https://github.com/sbt/sbt-assembly (for sbt).
I have finally found the cause of the problem.
Spark use hadoop-client-2.2.0 that use hadoop-common that use common-configuration-1.6.
In my application I used common-configuration-v1.10 where XMLConfiguration.setEntityResolver is implemented. Instead in version 1.6 of the library that method is not present.
When i run:
/bin/spark-submit --class MyClass myjar.jar
XMLConfiguration.class of common-configuration-v1.6 is loaded and the JVM does not find the method setEntityResolver
I have resolved using common-configuration-v2.0-beta1 in my application.