"Can't get Kerberos realm" on yarn cluster - kerberos

The situation is as follows:
I'm doing this on Windows 7, with MIT Kerberos client kfw 4.0.1. I'm connecting to a YARN cluster, via OpenVPN, that is secured with Kerberos 5. This cluster has been around for a while and it's been in use by other people, so the error is not likely to be on that side of things.
I can get a ticket via kinit (returns without error). However, once I try to do any of the following commands:
hdfs dfs -ls
spark-shell --master yarn
spark-submit anything --master yarn --deploy-mode cluster
essentially any spark or hadoop command on the cluster
I get the error: Can't get Kerberos realm (or Unable to locate Kerberos realm).
My krb5.ini file is in C:\ProgramData\MIT\Kerberos5
How can I further troubleshoot this?

Your JVM can not locate the krb5.conf file. You have several options:
set JVM property: -Djava.security.krb5.conf=/path/to/krb5.conf
or put the krb5.conf file into the <jdk-home>/jre/lib/security folder
or put the krb5.conf file into the c:\winnt\ folder
More information about locating the krb5.conf file are placed here: https://docs.oracle.com/javase/7/docs/technotes/guides/security/jgss/tutorials/KerberosReq.html

Related

Connection to remote Hadoop Cluster (CDP) through Linux server

I'm new to PySpark and I want to connect remote Hadoop Cluster (CDP) through Linux server by using spark-submit command.
Any help would be appreciated.
I need spark-submit command to connect remote CDP.
You can use Apache Livy to submit remote jobs to a CDP cluster. Here is detailed info on how to install and use Livy to submit jobs :
After downloading and unzipping Livy you should add following lines in livy.conf file. Then start livy service.
livy.spark.master = yarn
livy.spark.deploy-mode = cluster
You can find examples of how to create a spark submit script on following links:
https://community.cloudera.com/t5/Community-Articles/Submit-a-Spark-Job-to-CDP-Data-Hub-using-the-Livy-REST-API/ta-p/322481
https://livy.apache.org/examples/

Change Python version Livy uses in an EMR cluster

I am aware of Change Apache Livy's Python Version and How do i setup Pyspark in Python 3 with spark-env.sh.template.
I also have seen the Livy documentation
However, none of that works. Livy keeps using Python 2.7 no matter what.
This is running Livy 0.6.0 on an EMR cluster.
I have changed the PYSPARK_PYTHON environment variable to /usr/bin/python3 in the hadoop user, my user, the root, and ec2-user. Logging into the EMR master node via ssh and running pyspark starts python3 as expected. But, Livy keeps using python2.7.
I added export PYSPARK_PYTHON=/usr/bin/python3 to the /etc/spark/conf/spark-env.sh file. Livy keeps using python2.7.
I added "spark.yarn.appMasterEnv.PYSPARK_PYTHON":"/usr/bin/python3" and "spark.executorEnv.PYSPARK_PYTHON":"/usr/bin/python3" to the items listed below and in every case . Livy keeps using python2.7.
sparkmagic config.json and config_other_settings.json files before starting a PySpark kernel Jupyter
Session Properties in the sparkmagic %manage_spark Jupyter widget. Livy keeps using python2.7.
%%spark config cell-magic before the line-magic %spark add --session test --url http://X.X.X.X:8998 --auth None --language python
Note: This works without any issues in another EMR cluster running Livy 0.7.0 I have gone over all of the settings on the other cluster and cannot find what is different. I did not have to do any of this on the other cluster, Livy just used python3 by default.
How exactly do I get Livy to use python3 instead of python2?
Finally just found an answer after posting.
I ran the following in a PySpark kernel Jupyter session cell before running any code to start the PySpark session on the remote EMR cluster via Livy.
%%configure -f
{ "conf":{
"spark.pyspark.python": "python3"
}
}
Simply adding "spark.pyspark.python": "python3"  to the .sparkmagic config.json or config_other_settings.json also worked.
Confusing that this does not match the official Livy documentation.

How to read files uploaded by spark-submit on Kubernetes

I have Spark Jobs running on Yarn. These days I'm moving to Spark on Kubernetes.
On Kubernetes I'm having an issue: files uploaded via --files can't be read by Spark Driver.
On Yarn, as described in many answers I can read those files using Source.fromFile(filename).
But I can't read files in Spark on Kubernetes.
Spark version: 3.0.1
Scala version: 2.12.6
deploy-mode: cluster
submit commands
$ spark-submit --class <className> \
--name=<jobName> \
--master=k8s://https://api-hostname:6443 \
...
--deploy-mode=cluster \
--files app.conf \
--conf spark.kubernetes.file.upload.path=hdfs://<nameservice>/path/to/sparkUploads/ \
app.jar
After executing above command, app.conf is uploaded to hdfs://<nameservice>/path/to/sparkUploads/spark-upload-xxxxxxx/,
And in Driver's pod, I found app.conf in /tmp/spark-******/ directory, app.jar as well.
But Driver can't read app.conf, Source.fromFile(filename) returns null, there was no permission problems.
Update 1
In Spark Web UI->"Environment" Tab, spark://<pod-name>-svc.ni.svc:7078/files/app.conf in "Classpath Entries" menu. Does this mean app.conf is available in classpath?
On the other hand, in Spark on Yarn user.dir property was included in System classpath.
I found SPARK-31726: Make spark.files available in driver with cluster deploy mode on kubernetes
Update 2
I found that driver pod's /opt/spark/work-dir/ dir was included in classpath.
but /opt/spark/work-dir/ is empty on driver pod whereas on executor pod it contains app.conf and app.jar.
I think that is the problem and SPARK-31726 describes this.
Update 3
After reading Jacek's answer, I tested org.apache.spark.SparkFiles.getRootDirectory().
It returns /var/data/spark-357eb33e-1c17-4ad4-b1e8-6f878b1d8253/spark-e07d7e84-0fa7-410e-b0da-7219c412afa3/userFiles-59084588-f7f6-4ba2-a3a3-9997a780af24
Update 4 - work around
First, I make ConfigMaps to save files that I want to read driver/executors
Next, The ConfigMaps are mounted on driver/executors. To mount ConfigMap, use Pod Template or Spark Operator
--files files should be accessed using SparkFiles.get utility:
get(filename: String): String
Get the absolute path of a file added through SparkContext.addFile().
I found the another temporary solution in spark 3.3.0
We can use flag --archives. The files without tar, tar.gz, zip are ignored unpacking step and after that they are placed on working dir of driver and executor.
Although the docs of --archive don't mention executor, I tested and it's working.

scala spark to read file from hdfs cluster

I am learning to develop spark applications using Scala. And I am in my very first steps.
I have my scala IDE on windows. configured and runs smoothly if reading files from local drive. However, I have access to a remote hdfs cluster and Hive database, and I want to develop, try, and test my applications against that Hadoop cluster... but I don't know how :(
If I try
val rdd=sc.textFile("hdfs://masternode:9000/user/hive/warehouse/dwh_db_jrtf.db/discipline")
I will get an error that contains:
Exception in thread "main" java.io.IOException: Failed on local exception: com.google.protobuf.InvalidProtocolBufferException: Protocol message end-group tag did not match expected tag.; Host Details : local host is: "MyLap/11.22.33.44"; destination host is: "masternode":9000;
Can anyone guide me please ?
You can use SBT to package your code in a .jar file. scp your file on your Node then try to submit it by doing a spark-submit.
spark-submit \
--class <main-class> \
--master <master-url> \
--deploy-mode <deploy-mode> \
--conf <key>=<value> \
... # other options
<application-jar> \
[application-arguments]
You can't access to your Cluster from your Windows Machine in that way.

How to pass external configuration file to pyspark(Spark 2.x) program?

When I am running pyspark program interactive shell able to fetch the configuration file(config.ini) inside pyspark script,
But when I am trying to run same script using Spark submit command with master yarn and cluster deployment mode is cluster it giving me error as config file not exists, I have checked yarn log and able to see same, below is command for running the pyspark job.
spark2-submit --master yarn --deploy-mode cluster test.py /home/sys_user/ask/conf/config.ini
With spark2-sumbmit command there is parameter provided properties-file, you can use that to get this properties file available in spark-submit command.
e.g. spark2-submit --master yarn --deploy-mode cluster --properties-file $CONF_FILE_NAME pyspark_script.py
Pass the ini file in spark.files parameter
.config('spark.files', 'config/local/config.ini') \
Read in pyspark:
with open(SparkFiles.get('config.ini')) as config_file:
print(config_file.read())
It works for me.