I have a dse cluster base on docker. Now I want to use Mesos to manage my dse cluster for running spark job. So I installed Mesos master, Mesos slave docker container. What should I do next to connect dse to mesos?
Related
When I run the above spark application with zeppelin in Yarn cluster with cluster mode, I get the following error:
Where may be the problem? Thanks
I'm trying to set up a remote Spark 2.4.5 cluster on Ubuntu 18. After I start ./sbin/stat-master.sh WebUI is available at <INSTANCE-IP>:8080 but it shows "Spark Master at spark://spark-master:7077" where spark-master is my hostname on the remote machine.
I'm able to start a worker with ./sbin/start-slave.sh spark://spark-master:7077 only, but <INSTANCE-IP>:4040 doesn't work. When I try ./sbin/start-slave.sh spark://<INSTANCE-IP>:7077 I can see the process but the worker is not visible in WebUI.
As a result, I can not connect to the cluster from my local machine with spark-shell --master spark://<INSTANCE-IP>:7077. The error is:
StandaloneAppClient$ClientEndpoint: Failed to connect to master <INSTANCE-IP>:7077
We have all 6 machine, hdfs and yarn service on all node, 1 master and 6 slaves.
And we install Spark on 3 machine, 1 master, 3 workers ( 1 node master + worker) .
We know when --master spark://[host]:[port], the job will run only 3 node use standalone mode.
And when use spark-submit --master yarn submit a jar, it's would use all 6 server cpu and memory or just use 3 spark worker node machine ?
And if can run all 6 node, How left 3 server can know it's the Spark job?
Spark: 2.3.1
Hadoop: 2.7.3
In yarn mode, spark-submit send resource allocation resource to yarn and the containers will be launched on different node managers based on resource availability.
I am unable to view Spark history through Yarn UI(yarn web address 8088 in yarn-site.ml). Spark job completed successfully
Spark application was run in datanode shell with cluster-mode as cluster
When clicked on history it is redirecting to http://namenode:18088/history/application_1472647811761_0001/1 and it says page cannot be displayed
Hadoop Version: 2.7.0
Spark Version: 2.0.0
Cluster: one namenode and one datanode
spark-default.xml
spark.eventLog.dir=hdfs://namenode:9000/user/spark/applicationHistory
spark.eventLog.enabled=true
spark.yarn.historyServer.address=namenode:18088
spark.history.fs.logDirectory=hdfs://namenode:9000/shared/spark-logs
I'm trying to run Spark applications with Mesos cluster mode. (I've got client mode working but still would like to try cluster mode)
I have launched spark-mesos-dispatcher on the Mesos master node.
When I submit the assembly at local path /tmp/assembly.jar using the following command,
bin/spark-submit --master mesos://dispatcher:7077 --deploy-mode cluster --class com.example.Example /tmp/assembly.jar
It fails because the file /tmp/assembly.jar does not exist on the mesos slave nodes.
I1129 10:47:43.839771 5884 fetcher.cpp:414] Fetcher Info: {"cache_directory":"\/tmp\/mesos\/fetch\/slaves\/9d725348-931a-48fb-96f7-d29a4b09f3e8-S9\/deploy","items":[{"action":"BYPASS_CACHE","uri":{"extract":true,"value":"\/tmp\/assembly.jar"}}],"sandbox_directory":"\/var\/lib\/mesos\/slaves\/9d725348-931a-48fb-96f7-d29a4b09f3e8-S9\/frameworks\/9d725348-931a-48fb-96f7-d29a4b09f3e8-0291\/executors\/driver-20151129104742-0008\/runs\/31bf5840-226e-4b87-ae76-d14bd2f17950","user":"user"}
I1129 10:47:43.840710 5884 fetcher.cpp:369] Fetching URI '/tmp/assembly.jar'
I1129 10:47:43.840721 5884 fetcher.cpp:243] Fetching directly into the sandbox directory
I1129 10:47:43.840731 5884 fetcher.cpp:180] Fetching URI '/tmp/assembly.jar'
I1129 10:47:43.840737 5884 fetcher.cpp:160] Copying resource with command:cp '/tmp/assembly.jar' '/var/lib/mesos/slaves/9d725348-931a-48fb-96f7-d29a4b09f3e8-S9/frameworks/9d725348-931a-48fb-96f7-d29a4b09f3e8-0291/executors/driver-20151129104742-0008/runs/31bf5840-226e-4b87-ae76-d14bd2f17950/assembly.jar'
cp: cannot stat `/tmp/assembly.jar': No such file or directory
Failed to fetch '/tmp/assembly.jar': Failed to copy with command 'cp '/tmp/assembly.jar' '/var/lib/mesos/slaves/9d725348-931a-48fb-96f7-d29a4b09f3e8-S9/frameworks/9d725348-931a-48fb-96f7-d29a4b09f3e8-0291/executors/driver-20151129104742-0008/runs/31bf5840-226e-4b87-ae76-d14bd2f17950/assembly.jar'', exit status: 256
Failed to synchronize with slave (it's probably exited)
In case of YARN cluster mode, Spark's YARN client implementation will upload the application jar to HDFS so that the driver and all executors have access to the jar, but I could not find such code in RestSubmissionClient, which is used by Mesos or Standalond cluster mode.
Who does the uploading in this case? or do I need to manually put the application assembly somewhere accessible via an HTTP URI?
From my understanding you could use the SparkContext addJar() method to add a local (to the driver application) JAR file path, which will then be distributed to the executor nodes (in client mode).
As you state that you want to use cluster mode, I'd suggest that you have a look at the Spark Jobserver project, which should make the running of Spark applications on Mesos easier than with the built-in tools.