A spark cluster has been launched using the ec2/spark-ec2 script from within the branch-1.4 codebase. I have logged onto it.
I can login to it - and it reflects 1 master, 2 slaves:
11:35:10/sparkup2 $ec2/spark-ec2 -i ~/.ssh/hwspark14.pem login hwspark14
Searching for existing cluster hwspark14 in region us-east-1...
Found 1 master, 2 slaves.
Logging into master ec2-54-83-81-165.compute-1.amazonaws.com...
Warning: Permanently added 'ec2-54-83-81-165.compute-1.amazonaws.com,54.83.81.165' (RSA) to the list of known hosts.
Last login: Tue Jun 23 20:44:05 2015 from c-73-222-32-165.hsd1.ca.comcast.net
__| __|_ )
_| ( / Amazon Linux AMI
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https://aws.amazon.com/amazon-linux-ami/2013.03-release-notes/
Amazon Linux version 2015.03 is available.
But .. where are they?? The only java processes running are:
Hadoop: NameNode and SecondaryNode
Tachyon: Master and Worker
It is a surprise to me that the Spark Master and Workers are not started. When looking for the processes to start them manually it is not at all obvious where they are located.
Hints on
why spark did not start automatically
and
where the launch scripts live
would be appreciated. (In the meantime i will do an exhaustive
find / -name start-all.sh
And .. survey says:
root#ip-10-151-25-94 etc]$ find / -name start-all.sh
/root/persistent-hdfs/bin/start-all.sh
/root/ephemeral-hdfs/bin/start-all.sh
Which means to me that spark were not even installed??
Update I wonder: is this a bug in 1.4.0? I ran same set of commands in 1.3.1 and the spark cluster came up.
There was a bug in spark 1.4.0 provisioning script which is cloned from github repository by spark-ec2 (https://github.com/mesos/spark-ec2/) with similar symptoms - apache spark haven't started. The reason was - provisioning script failed to download spark archive.
Check was spark downloaded and uncompressed on the master host ls -altr /root/spark there should be several directories there. From your description looks like /root/spark/sbin/start-all.sh script is missing - which is missing there.
Also check the contents of the file cat /tmp/spark-ec2_spark.log it should has information about uncompressing step.
Another thing to try is to run spark-ec2 with other provisioning script branch by adding --spark-ec2-git-branch branch-1.4 into the spark-ec2 command line argument.
Also when you run spark-ec2 save all output and check is there something suspicious:
spark-ec2 <...args...> 2>&1 | tee start.log
Related
Ok, it is very strange. I have some init scripts that I would like to run when a cluster starts
cluster has the init script , which is in a file (in dbfs)
basically this
dbfs:/databricks/init-scripts/custom-cert.sh
Now , when I make the init script like this, it works (no ssl errors for my endpoints. Also, the event logs for the cluster shows the duration as 1 second for the init script
dbutils.fs.put("/databricks/init-scripts/custom-cert.sh", """#!/bin/bash
cp /dbfs/orgcertificates/orgcerts.crt /usr/local/share/ca-certificates/
sudo update-ca-certificates
echo "export REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt" >> /databricks/spark/conf/spark-env.sh
""")
However, if I just put the init script in an bash script and upload it to DBFS through a pipeline, the init script does not do anything. It executes , as per the event log but the execution duration is 0 sec.
I have the sh script in a file named
custom-cert.sh
with the same contents as above, i.e.
#!/bin/bash
cp /dbfs/orgcertificates/orgcerts.crt /usr/local/share/ca-certificates/
sudo update-ca-certificates
echo "export REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt"
but when I check /usr/local/share/ca-certificates/ , it does not contain /dbfs/orgcertificates/orgcerts.crt, even though the cluster init script has run.
Also, I have compared the contents of the init script in both cases and it least to the naked eye, I can't figure out any difference
i.e.
%sh
cat /dbfs/databricks/init-scripts/custom-cert.sh
shows the same contents in both the scenarios. What is the problem with the 2nd case?
EDIT: I read a bit more about init scripts and found that the logs of init scripts are written here
%sh
ls /databricks/init_scripts/
Looking at the err file in that location, it seems there is an error
sudo: update-ca-certificates
: command not found
Why is it that update-ca-certificates found in the first case but not when I put the same script in a sh script and upload it to dbfs (instead of executing the dbutils.fs.put within a notebook) ?
EDIT 2: In response to the first answer. After running the command
dbutils.fs.put("/databricks/init-scripts/custom-cert.sh", """#!/bin/bash
cp /dbfs/orgcertificates/orgcerts.crt /usr/local/share/ca-certificates/
sudo update-ca-certificates
echo "export REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt" >> /databricks/spark/conf/spark-env.sh
""")
the output is the file custom-cert.sh and then I restart the cluster with the init script location as dbfs:/databricks/init-scripts/custom-cert.sh and then it works. So, it is essentially the same content that the init script is reading (which is the generated sh script). Why can't it read it if I do not use dbfs put but just put the contents in bash file and upload it during the CI/CD process?
As we aware, An init script is a shell script that runs during startup of each cluster node before the Apache Spark driver or worker JVM start. case-2 When you run bash
command by using of %sh magic command means you are trying to execute this command in Local driver node. So that workers nodes is not able to access . But based on
case-1 , By using of %fs magic command you are trying run copy command (dbutils.fs.put )from root . So that along with driver node , other workers node also can access path .
Ref : https://docs.databricks.com/data/databricks-file-system.html#summary-table-and-diagram
It seems that my observations I made in the comments section of my question is the way to go.
I now create the init script using a databricks job that I run during the CI/CD pipeline from Azure DevOps.
The notebook has the commands
dbutils.fs.rm("/databricks/init-scripts/custom-cert.sh")
dbutils.fs.put("/databricks/init-scripts/custom-cert.sh", """#!/bin/bash
cp /dbfs/internal-certificates/certs.crt /usr/local/share/ca-certificates/
sudo update-ca-certificates
echo "export REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt" >> /databricks/spark/conf/spark-env.sh
""")
I then create a Databricks job (pointing to this notebook), the cluster is a job cluster which is just temporary . Of course , in my case , even this job creation is automated using a powershell script.
I then call this Databricks job in the release pipeline using again a Powershell script.
This creates the file
/databricks/init-scripts/custom-cert.sh
I then use this file in any other cluster that accesses my org's endpoints (without certificate errors).
I do not know (or still understand), why can't the same script file be just part of a repo and uploaded during the release process (instead of it being this Databricks job calling a notebook). I would love to know the reason . The other answer on this question does not hold true as you can see, that the cluster script is created by a job cluster and then accessed from another cluster as part of its init script.
It simply boils down to how the init script gets created.
But I get my job done. Just if it helps someone get their job done too.
I have raised a support case though to understand the reason.
Spark job executed by Dataproc cluster on Google Cloud gets stuck on a task PythonRDD.scala:446
The error log says Could not find valid SPARK_HOME while searching ... paths under /hadoop/yarn/nm-local-dir/usercache/root/
The thing is, SPARK_HOME should be set by default on a dataproc cluster.
Other spark jobs that don't use RDDs work just fine.
During the initialization of the cluster I do not reinstall spark (but I have tried to, which I previously thought caused the issue).
I also found out that all my executors were removed after a minute of running the task.
And yes, I have tried to run the following initialization action and it didn't help:
#!/bin/bash
cat << EOF | tee -a /etc/profile.d/custom_env.sh /etc/*bashrc >/dev/null
export SPARK_HOME=/usr/lib/spark/
EOF
Any help?
I was using a custom mapping function. When I put the function to a separate file the problem disappeared.
I recently created a Grid Engine cluster on Compute Engine using Elasticluster (http://googlegenomics.readthedocs.org/en/latest/use_cases/setup_gridengine_cluster_on_compute_engine/index.html).
I was wondering what is the appropriate command to run shared-memory multithreaded batch jobs on a cluster of Compute Engine virtual machine running Grid Engine.
In other words, what is the name (i.e. pe_name) of the Grid Engine parallel environment.
Let's say I want to run a job requesting 4 cpus on 1 node, what would be the right qsub command.
So far I tried the following command:
qsub -cwd -l h_vmem=800G -pe smp 6 run.sh
Unable to run job: job rejected: the requested parallel environment "smp" does not exist.
qsub -cwd -l h_vmem=800G -pe omp 6 run.sh
Unable to run job: job rejected: the requested parallel environment "omp" does not exist.
Thank you for your help!
I don't believe that Elasticluster's Ansible playbook includes a parallel environment. You can see the main configuration run on the master here:
https://github.com/gc3-uzh-ch/elasticluster/blob/master/elasticluster/providers/ansible-playbooks/roles/gridengine/tasks/master.yml
I believe you can simply connect to the master and issue the "add parallele environment" command:
$ qconf -ap smp
and write a configuration file like:
pe_name smp
slots 9999
user_lists NONE
xuser_lists NONE
start_proc_args /bin/true
stop_proc_args /bin/true
allocation_rule $fill_up
control_slaves FALSE
job_is_first_task FALSE
urgency_slots min
accounting_summary FALSE
and then modify the queue configuration for all.q:
$ qconf -mq all.q
...
pe_list make smp
...
I would also suggest filing an issue with Elasticluster here:
https://github.com/gc3-uzh-ch/elasticluster/issues
I would expect that someone has already done this in a fork of Elasticluster and may be able to provide a pull request to the master fork.
Hope that helps.
-Matt
I'm working on integration between Mesos & Spark. For now, I can start SlaveMesosDispatcher in a docker; and I like to also run Spark executor in Mesos docker. I do the following configuration for it, but I got an error; any suggestion?
Configuration:
Spark: conf/spark-defaults.conf
spark.mesos.executor.docker.image ubuntu
spark.mesos.executor.docker.volumes /usr/bin:/usr/bin,/usr/local/lib:/usr/local/lib,/usr/lib:/usr/lib,/lib:/lib,/home/test/workshop/spark:/root/spark
spark.mesos.executor.home /root/spark
#spark.executorEnv.SPARK_HOME /root/spark
spark.executorEnv.MESOS_NATIVE_LIBRARY /usr/local/lib
NOTE: The spark are installed in /home/test/workshop/spark, and all dependencies are installed.
After submit SparkPi to the dispatcher, the driver job is started but failed. The error messes is:
I1015 11:10:29.488456 18697 exec.cpp:134] Version: 0.26.0
I1015 11:10:29.506619 18699 exec.cpp:208] Executor registered on slave b7e24114-7585-40bc-879b-6a1188cb65b6-S1
WARNING: Your kernel does not support swap limit capabilities, memory limited without swap.
/bin/sh: 1: ./bin/spark-submit: not found
Does any know how to map/set spark home in docker for this case?
I think the issue you're seeing here is a result of the current working directory of the container isn't where Spark is installed. When you specify a docker image for Spark to use with Mesos, it expects the default working directory of the container to be inside $SPARK_HOME where it can find ./bin/spark-submit.
You can see that logic here.
It doesn't look like you're able to configure the working directory through Spark configuration itself, which means you'll need to build a custom image on top of ubuntu that simply does a WORKDIR /root/spark.
This question is related to Hadoop on Azure environment.
I am trying to use Runtime.exec() to execute a batch script in the reduce function. I could not get this running in Hadoop on Azure environment while it runs fine in the Hadoop on Linux. I tested the Runtime.exec() code snippet in my desktop (windows 7) environment and it runs fine there. I have made sure that I consume the output and error streams of the sub-process after Runtime.exec().
The batch script contains the below ( a single command):
c:\hdfs\mapred\local\taskTracker\nabeel\jobcache\job_201207121317_0024\attempt_201207121317_0024_r_000001_0\work\tool.exe
-f c:\hdfs\mapred\local\taskTracker\nabeel\jobcache\job_201207121317_0024\work\11_task_201207121317_0024_r_000001.out
-i c:\hdfs\mapred\local\taskTracker\nabeel\jobcache\job_201207121317_0024\attempt_201207121317_0024_r_000001_0\work\input.txt
I distribute the tool.exe and input.txt files using Distributed cache and it creates a symlink from the working directory. tool.exe and input.txt points to the actual files in the jobcache directory.
2012-07-16 04:31:51,613 INFO org.apache.hadoop.mapred.TaskRunner: Creating symlink: /hdfs/mapred/local/taskTracker/distcache/-978619214658189372_-1497645545_209290723/10.73.50.78tool.exe <- \hdfs\mapred\local\taskTracker\nabeel\jobcache\job_201207121317_0024\attempt_201207121317_0024_r_000001_0\work\tool.exe
2012-07-16 04:31:51,644 INFO org.apache.hadoop.mapred.TaskRunner: Creating symlink: /hdfs/mapred/local/taskTracker/distcache/-4944695173898834237_1545037473_2085004342/10.73.50.78input.txt <- \hdfs\mapred\local\taskTracker\nabeel\jobcache\job_201207121317_0024\attempt_201207121317_0024_r_000001_0\work\input.txt
The reducer gives the below error when it runs.
Command Execution Error: Cannot run program
"cmd /q /c c:\hdfs\mapred\local\taskTracker\nabeel\jobcache\job_201207121317_0024\work\11_task_201207121317_0024_r_0000011513543720767963399.bat":
CreateProcess error=2, The system cannot find the file specified
In another case, I tried running the same but without using the absolute paths.. The output stream from the sub-process is shown below:
c:\hdfs\mapred\local\taskTracker\nabeel\jobcache\job_201207121317_0022\attempt_201207121317_0022_r_000000_0\work>tool.exe -f /hdfs/mapred/local/taskTracker/nabeel/jobcache/job_201207121317_0022/work/1_task_201207121317_0022_r_000000.out
-i input.txt
I do not know how the job working directory paths and distributed cache works in Hadoop on Azure environment. Could you please let me know if I am missing something here (or) there is something I need to take care of while using Runtime.exec() in Hadoop on Azure environment.
Thanks,
.,._
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I am not familiar with Hadoop. But the error message seems to be obvious. It would be better if you can check whether the file exists.
c:\hdfs\mapred\local\taskTracker\nabeel\jobcache\job_201207121317_0024\work\11_task_201207121317_0024_r_0000011513543720767963399.bat
Best Regards,
Ming Xu