I am running a spark job on hadoop yarn (hadoop 2.7.0 but also tried 2.4.0, all on my box using the downloads from apache-hadoop web site and spark 1.3.1). My spark job is in scala but contains classes compiled with jdk8.
When I run hadoop on jdk8, I get
INFO yarn.Client:
client token: N/A
diagnostics: Shutdown hook called before final status was reported.
ApplicationMaster host: kostas-pc
ApplicationMaster RPC port: 0
queue: default
start time: 1431513335001
final status: SUCCEEDED
Even if the job is marked as SUCCEEDED, it actually didn't do anything due to "Shutdown hook called before final status was reported.". In fact no logging is visible from my spark job.
When I switch the jdk that I run hadoop, to jdk7, my job starts running and I can see log entries from my scala code, but when it gets to the code compiled with jdk8 it fails with incompatible class error (as expected).
So it seems running hadoop+spark with jdk8 is not compatible. Are there any solutions to this?
Thanks
Seems spark 1.4.0 is ok with jdk8
Related
Disclaimer: I am new to both Hadoop and Apache Ignite. sorry for the lengthy background info.
Setup:
I have installed and configured Apache Ignite Hadoop Accelerator. Start-All.sh brings up the below services. I can submit Hadoop jobs. They complete and I can see results as expected. The start all uses traditional core-site, hdfs-site, mapred-site, and yarn-site configuration files.
28336 NodeManager
28035 ResourceManager
27780 SecondaryNameNode
27429 NameNode
28552 Jps
27547 DataNode
I also have installed Apache Ignite 2.6.0. I am able to start ignite nodes, connect to it using web console. I was able to load the cache from MySQL and run SQL queries and java programs against this cache.
For running Hadoop jobs using ignited Hadoop, I created a separate ignite-config directory, in which I have customized core-site and mapred-site configurations as per the instructions in the Apache ignite web site.
Issue:
When I run a Hadoop job using the command:
hadoop --config ~/ignite-conf jar $HADOOP_HOME/share/hadoop/mapreduce/hadoop-mapreduce-examples-3.1.0.jar wordcount input output1
I get the below error (Note, the same job ran successfully against the Hadoop/without ignite):
java.io.IOException: Failed to get new job ID.
...
...
Caused by: class org.apache.ignite.internal.client.GridClientDisconnectedException: Latest topology update failed.
...
...
Caused by: class org.apache.ignite.internal.client.GridServerUnreachableException: Failed to connect to any of the servers in list: [/:13500]
...
...
It looks like, there was attempt made to lookup the jobtracker (13500) and it was not able to find. From the service list above, it's obvious that job tracker is not running. However, the job ran just fine on non-ignited hadoop over YARN.
Can you help please?
This is resolved in my case.
The job tracker here meant the Apache Ignite memory cache services listening on port 11211.
After making this change in mapred-site.xml, the job ran!
The job that I've submitted to spark cluster is not finishing. I see it is pending forever, however logs say that even spark jetty connector is shut down:
17/05/23 11:53:39 INFO org.spark_project.jetty.server.ServerConnector: Stopped ServerConnector#4f67e3df{HTTP/1.1}{0.0.0.0:4041}
I run latest cloud dataproc v1.1 (spark 2.0.2) on yarn. I submit spark job via gcloud api:
gcloud dataproc jobs submit spark --project stage --cluster datasys-stg \
--async --jar hdfs:///apps/jdbc-job/jdbc-job.jar --labels name=jdbc-job -- --dbType=test
The same spark pi stuff is finished correctly:
gcloud dataproc jobs submit spark --project stage --cluster datasys-stg --async \
--class org.apache.spark.examples.SparkPi --jars file:///usr/lib/spark/examples/jars/spark-examples.jar -- 100
While visiting hadoop application manager interface I see it is finished with Successful result:
Google cloud console and job list is showing it is still running until killed (see job run for 20 hours before killed, while hadoop says it ran for 19 seconds):
Is there something I can monitor to see what is preventing gcloud to finish the job?
I couldn't find anything that I can monitor my application is not finishing, but I've found the actual problem and fixed it. Turns out I had abandoned threads in my application - I had connection to RabbitMQ and that seemed to create some threads that prevented application from being finally stoped by gcloud.
I am running Spark 1.1.0, HDP 2.1, on a kerberized cluster. I can successfully run spark-submit using --master yarn-client and the results are properly written to HDFS, however, the job doesn't show up on the Hadoop All Applications page. I want to run spark-submit using --master yarn-cluster but I continue to get this error:
appDiagnostics: Application application_1417686359838_0012 failed 2 times due to AM Container
for appattempt_1417686359838_0012_000002 exited with exitCode: -1000 due to: File does not
exist: hdfs://<HOST>/user/<username>/.sparkStaging/application_<numbers>_<more numbers>/spark-assembly-1.1.0-hadoop2.4.0.jar
.Failing this attempt.. Failing the application.
I've provisioned my account with access to the cluster. I've configured yarn-site.xml. I've cleared .sparkStaging. I've tried including --jars [path to my spark assembly in spark/lib]. I've found this question that is very similar, yet unanswered. I can't tell if this is a 2.1 issue, spark 1.1.0, kerberized cluster, configurations, or what. Any help would be much appreciated.
This is probably because you left sparkConf.setMaster("local[n]") in the code.
I installed hadoop 2.5.2, and I can run the wordcount sample successfully. However, when I want to see the application running on yarn (job running), I cannot as all applictaions interface is always empty (shown in the following screen).
Is there anyway to make the jobs visible?
Please try localhost:19888 or check value of the the property for web url for job history (mapreduce.jobhistory.webapp.address) configured in you yarn config file.
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.