I need help, I have installed hadoop-2.6 on Ubuntu 14.04 with HIPI configuration and all services are up and running.However while running jar file and using the following command doesnt execute a map-reduce job: hadoop jar faceCount.jar /project/input.hib and project/output
The job is planned but nothing is happening...
This is http://macvaio-vpceh28fn:8088/cluster
Related
I was running Spark job which make use of other files that is passed in through --archives flag of spark
spark-submit .... --archives hdfs:///user/{USER}/{some_folder}.zip .... {file_to_run}.py
Spark is currently running on YARN and when I tried it with spark version 1.5.1 it was fine.
However, when I ran the same commands with spark 2.0.1, I got
ERROR yarn.ApplicationMaster: User class threw exception: java.io.IOException: Cannot run program "/home/{USER}/{some_folder}/.....": error=2, No such file or directory
Since the resource is managed by YARN, it is challenging to manually check if the file gets successfully decompressed and exist when the job runs.
I wonder if anyone has experienced similar issue.
Is it possible to run Spark Jobs e.g. Spark-sql jobs via Oozie?
In the past we have used Oozie with Hadoop. Since we are now using Spark-Sql on top of YARN, looking for a way to use Oozie to schedule jobs.
Thanks.
Yup its possible ... The procedure is also same, that you have to provide Oozia a directory structure having coordinator.xml, workflow.xml and a lib directory containing your Jar files.
But remember Oozie starts the job with java -cp command, not with spark-submit, so if you have to run it with Oozie, Here is a trick.
Run your jar with spark-submit in background.
Look for that process in process list. It will be running under java -cp command but with some additional Jars, that are added by spark-submit. Add those Jars in CLASS_PATH. and that's it. Now you can run your Spark applications through Oozie.
1. nohup spark-submit --class package.to.MainClass /path/to/App.jar &
2. ps aux | grep '/path/to/App.jar'
EDITED: You can also use latest Oozie, which has Spark Action also.
To run Spark SQL by Oozie you need to use Oozie Spark Action.
You can locate oozie.gz on your distribution. Usually in cloudera you can find this oozie examples directory at below path.
]$ locate oozie.gz
/usr/share/doc/oozie-4.1.0+cdh5.7.0+267/oozie-examples.tar.gz
Spark SQL need hive-site.xml file for execution which you need to provide in workflow.xml
< spark-opts>--file /hive-site.xml < /spark-opts>
I am trying to run a hadoop job using following command
hadoop -jar myjob.jar
In this case i can not see the jar submitted and its status using web page(at port 50030)
but if i do
hadoop jar myjob.jar
I can see the progress on the same port(50030)
What is the difference between these two commands ,I searched a bit and found
hadoop -jar to submit pipe jobs
hadoop jar to submit streaming jobs
Any insight will be of a great help.
There is no hadoop -jar
From the docs:
Usage: hadoop jar <jar> [mainClass] args...
The streaming jobs are run via this command.
I am new to the spark, After installing the spark using parcels available in the cloudera manager.
I have configured the files as shown in the below link from cloudera enterprise:
http://www.cloudera.com/content/cloudera-content/cloudera-docs/CM4Ent/4.8.1/Cloudera-Manager-Installation-Guide/cmig_spark_installation_standalone.html
After this setup, I have started all the nodes in the spark by running /opt/cloudera/parcels/SPARK/lib/spark/sbin/start-all.sh. But I couldn't run the worker nodes as I got the specified error below.
[root#localhost sbin]# sh start-all.sh
org.apache.spark.deploy.master.Master running as process 32405. Stop it first.
root#localhost.localdomain's password:
localhost.localdomain: starting org.apache.spark.deploy.worker.Worker, logging to /var/log/spark/spark-root-org.apache.spark.deploy.worker.Worker-1-localhost.localdomain.out
localhost.localdomain: failed to launch org.apache.spark.deploy.worker.Worker:
localhost.localdomain: at java.lang.ClassLoader.loadClass(libgcj.so.10)
localhost.localdomain: at gnu.java.lang.MainThread.run(libgcj.so.10)
localhost.localdomain: full log in /var/log/spark/spark-root-org.apache.spark.deploy.worker.Worker-1-localhost.localdomain.out
localhost.localdomain:starting org.apac
When I run jps command, I got:
23367 Jps
28053 QuorumPeerMain
28218 SecondaryNameNode
32405 Master
28148 DataNode
7852 Main
28159 NameNode
I couldn't run the worker node properly. Actually I thought to install a standalone spark where the master and worker work on a single machine. In slaves file of spark directory, I given the address as "localhost.localdomin" which is my host name. I am not aware of this settings file. Please any one cloud help me out with this installation process. Actually I couldn't run the worker nodes. But I can start the master node.
Thanks & Regards,
bips
Please notice error info below:
localhost.localdomain: at java.lang.ClassLoader.loadClass(libgcj.so.10)
I met the same error when I installed and started Spark master/workers on CentOS 6.2 x86_64 after making sure that libgcj.x86_64 and libgcj.i686 had been installed on my server, finally I solved it. Below is my solution, wish it can help you.
It seem as if your JAVA_HOME environment parameter didn't set correctly.
Maybe, your JAVA_HOME links to system embedded java, e.g. java version "1.5.0".
Spark needs java version >= 1.6.0. If you are using java 1.5.0 to start Spark, you will see this error info.
Try to export JAVA_HOME="your java home path", then start Spark again.
I'm working on a hadoop cluster with CDH4.2.0 installed and ran into this error. It's been fixed in later versions of hadoop but I don't have access to update the cluster. Is there a way to tell hadoop to use this jar when running my job through the command line arguments like
hadoop jar MyJob.jar -D hadoop.mapreduce.client=hadoop-mapreduce-client-core-2.0.0-cdh4.2.0.jar
where the new mapreduce-client-core.jar file is the patched jar from the ticket. Or must hadoop be completely recompiled with this new jar? I'm new to hadoop so I don't know all the command line options that are possible.
I'm not sure how that would work as when you're executing the hadoop command you're actually executing code in the client jar.
Can you not use MR1? The issue says this issue only occurs when you're using MR2, so unless you really need Yarn you're probably better using the MR1 library to run your map/reduce.