- Login to OSG Connect
- Tutorial jobs
- Job 2: Passing arguments to executables
- Job 3: Submitting jobs concurrently
- Removing jobs
- What's next?
Login to OSG Connect
If you have not already registered for OSG Connect, go to the registration site and follow the instructions there. Once registered, you will be assigned a login node which you can use for the rest of this tutorial.
To save some typing, you can install the tutorial into your home directory on the login node. This is highly recommended to ensure that you don't encounter transcription errors during the tutorials.
$ tutorial usage: tutorial name-of-tutorial tutorial info name-of-tutorial Available tutorials: quickstart ..... How to run your first OSG job
Now, run the quickstart tutorial:
$ tutorial quickstart $ cd tutorial-quickstart
Alternatively, if you want the full manual experience, create a new directory for the tutorial work:
$ mkdir tutorial-quickstart $ cd tutorial-quickstart
Job 1: A simple, nonparallel job
Inside the tutorial directory that you created or installed previously,
let's create a test script to execute as your job. For pretyped setup, this is
#!/bin/bash # short.sh: a short discovery job printf "Start time: "; /bin/date printf "Job is running on node: "; /bin/hostname printf "Job running as user: "; /usr/bin/id printf "Job is running in directory: "; /bin/pwd echo echo "Working hard..." sleep 20 echo "Science complete!"
Now, make the script executable.
chmod +x short.sh
Run the job locally
When setting up a new job submission, it's important to test your job outside of HTCondor before submitting into the grid.
$ ./short.sh Start time: Wed Aug 21 09:21:35 CDT 2013 Job is running on node: loginNN.osgconnect.net Job running as user: uid=54161(netid) gid=1000(users) groups=1000(users),0(root),1001(osg-connect),1002(osg-staff),1003(osg-connect-test),9948(staff),19012(osgconnect) Job is running in directory: /home/netid/quickstart Working hard... Science complete!
Create an HTCondor submit file
So far, so good! Let's create a simple (if verbose) HTCondor submit file. This can be found in
# Our executable is the main program or script that we've created # to do the 'work' of a single job. executable = short.sh # We need to name the files that HTCondor should create to save the # terminal output (stdout) and error (stderr) created by our job. # Similarly, we need to name the log file where HTCondor will save # information about job execution steps. error = short.error output = short.output log = short.log # We need to request the resources that this job will need: request_cpus = 1 request_memory = 1 MB request_disk = 1 MB # The last line of a submit file indicates how many jobs of the above # description should be queued. We'll start with one job. queue 1
More about projects
You can join projects after you login at https://osgconnect.net/
. Within minutes of joining and being approved for a project, you will
have access via
condor_submit as well. For more information on creating
a project, please see this page
You have two ways to set the project name for your jobs:
- Add the
+ProjectName = "MyProject"line to the HTCondor submit file. Remember to quote the project name!
- Set the default project with the command
If you do not set a project name, or you use a project that you're not a member of, then your job submission will fail.
Submit the job
Submit the job using
$ condor_submit tutorial01.submit Submitting job(s). 1 job(s) submitted to cluster 144121.
Check the job status
condor_q command tells the status of currently running jobs.
Generally you will want to limit it to your own jobs:
$ condor_q netid -- Schedd: loginNN.osgconnect.net : <188.8.131.52:9618?... @ 12/10/18 14:19:08 OWNER BATCH_NAME SUBMITTED DONE RUN IDLE TOTAL JOB_IDS netid ID: 1441271 12/10 14:18 _ 1 _ 1 1441271.0 Total for query: 1 jobs; 0 completed, 0 removed, 0 idle, 1 running, 0 held, 0 suspended Total for netid: 1 jobs; 0 completed, 0 removed, 0 idle, 1 running, 0 held, 0 suspended Total for all users: 3001 jobs; 0 completed, 0 removed, 2189 idle, 754 running, 58 held, 0 suspended
You can also get status on a specific job cluster:
$ condor_q 1441271 -- Schedd: loginNN.osgconnect.net : <184.108.40.206:9618?... @ 12/10/18 14:19:08 OWNER BATCH_NAME SUBMITTED DONE RUN IDLE TOTAL JOB_IDS netid ID: 1441271 12/10 14:18 _ 1 _ 1 1441271.0 Total for query: 1 jobs; 0 completed, 0 removed, 0 idle, 1 running, 0 held, 0 suspended Total for netid: 1 jobs; 0 completed, 0 removed, 0 idle, 1 running, 0 held, 0 suspended Total for all users: 3001 jobs; 0 completed, 0 removed, 2189 idle, 754 running, 58 held, 0 suspended
IDLE columns. Your job will be listed in the
IDLE column if
it hasn't started yet. If it's currently scheduled and running, it will
appear in the
RUN column. As it finishes up, it will then show in the
Once the job completes completely, it will not appear in
Let's wait for your job to finish – that is, for
condor_q not to show
the job in its output. A useful tool for this is watch – it runs a
program repeatedly, letting you see how the output differs at fixed
time intervals. Let's submit the job again, and watch
at two-second intervals:
$ condor_submit tutorial01.submit Submitting job(s). 1 job(s) submitted to cluster 1441272 $ watch -n2 condor_q netid ...
When your job has completed, it will disappear from the list.
Note: To close watch, hold down Ctrl and press C.
Once your job has finished, you can get information about its execution
$ condor_history 1441272 ID OWNER SUBMITTED RUN_TIME ST COMPLETED CMD 1441272.0 netid 12/10 14:18 0+00:00:29 C 12/10 14:19 /home/netid/tutorial-quickstart/short.sh
Note: You can see much more information about your job's final status
Check the job output
Once your job has finished, you can look at the files that HTCondor has returned to the working directory. The names of these files were specified in our submit file. If everything was successful, it should have returned:
- a log file from HTCondor for the job cluster: short.log
- an output file for each job's output: short.output
- an error file for each job's errors: short.error
Read the output file. It should be something like this:
$ cat short.output Start time: Mon Dec 10 20:18:56 UTC 2018 Job is running on node: osg-84086-0-cmswn2030.fnal.gov Job running as user: uid=12740(osg) gid=9652(osg) groups=9652(osg) Job is running in directory: /srv Working hard... Science complete!
Job 2: Passing arguments to executables
Sometimes it's useful to pass arguments to your executable from your submit file. For example, you might want to use the same job script for more than one run, varying only the parameters. You can do that by adding Arguments to your submission file.
First, let's edit our existing
short.sh script to accept arguments. To avoid losing our original script, we make a copy of the file under the name
$ cp short.sh short_transfer.sh
Now, edit the file to include the added lines below:
#!/bin/bash # short.sh: a short discovery job printf "Start time: "; /bin/date printf "Job is running on node: "; /bin/hostname printf "Job running as user: "; /usr/bin/id printf "Job is running in directory: "; /bin/pwd printf "The command line argument is: "; $1 printf "Contents of $1 is "; cat $1 cat $1 > output.txt printf "Working hard..." ls -l $PWD sleep 20 echo "Science complete!"
We need to make our new script executable just as we did before:
$ chmod +x short_transfer.sh
Notice that with our changes, the new script will now print out the contents of whatever file we specify in our arguments, specified by the
$1. It will also copy the contents of that file into another file called
Make a simple text file called
input.txt that we can pass to our script:
Once again, before submitting our job we should test it locally to ensure it runs as we expect:
$ ./short_transfer.sh input.txt Start time: Tue Dec 11 10:19:12 CST 2018 Job is running on node: loginNN.osgconnect.net Job running as user: uid=100279(netid) gid=1000(users) groups=1000(users),5532(connect),5782(osg),7021(osg.ConnectTrain) Job is running in directory: /home/netid/tutorial-quickstart The command line argument is: Contents of input.txt is "Hello World"Working hard...total 28 drwxrwxr-x 2 netid users 34 Oct 15 09:37 Images -rw-rw-r-- 1 netid users 13 Oct 15 09:37 input.txt drwxrwxr-x 2 netid users 114 Dec 11 09:50 log -rw-r--r-- 1 netid users 13 Dec 11 10:19 output.txt -rwxrwxr-x 1 netid users 291 Oct 15 09:37 short.sh -rwxrwxr-x 1 netid users 390 Dec 11 10:18 short_transfer.sh -rw-rw-r-- 1 netid users 806 Oct 15 09:37 tutorial01.submit -rw-rw-r-- 1 netid users 547 Dec 11 09:49 tutorial02.submit -rw-rw-r-- 1 netid users 1321 Oct 15 09:37 tutorial03.submit Science complete!
Now, let's edit our submit file to properly handle these new arguments and output files and save this as
# We need the job to run our executable script, with the # input.txt filename as an argument, and to transfer the # relevant input and output files: executable = short_transfer.sh arguments = input.txt transfer_input_files = input.txt transfer_output_files = output.txt error = job.error output = job.output log = job.log # The below are good base requirements for first testing jobs on OSG, # if you don't have a good idea of memory and disk usage. request_cpus = 1 request_memory = 1 GB request_disk = 1 GB # Queue one job with the above specifications. queue 1
Notice the added
arguments = input.txt information. The
arguements option specifies what arguments should be passed to the executable.
transfer_output_files options need to be included as well. When jobs are deployed on the Open Science Grid, they are sent only with files that are specified. Additionally, only the specified output files are returned with the job. Any output not transferred back, with the exception of our
log files, are discarded at the end of the job.
Submit the new submit file using
condor_submit. Be sure to check your output files once the job completes.
$ condor_submit tutorial02.submit Submitting job(s). 1 job(s) submitted to cluster 1444781.
Job 3: Submitting jobs concurrently
What do we need to do to submit several jobs simultaneously? In the
first example, Condor returned three files: out, error, and log. If we
want to submit several jobs, we need to track these three files for each
job. An easy way to do this is to add the
macros to the HTCondor submit file. Since this can make our working
directory really messy with a large number of jobs, let's tell HTCondor
to put the files in a directory called log. Here's what the third submit file looks like, called
# We need the job to run our executable script, arguments and files. # Also, we'll specify unique filenames for each job by using # the job's 'cluster' value. executable = short_transfer.sh arguments = input.txt transfer_input_files = input.txt transfer_output_files = output.txt error = log/job.$(Cluster).$(Process)error output = log/job.$(Cluster).$(Process).output log = log/job.$(Cluster).$(Process).log request_cpus = 1 request_memory = 1 GB request_disk = 1 GB # Let's queue ten jobs with the above specifications queue 10
Before submitting, we also need to make sure the log directory exists.
$ mkdir -p log
You'll see something like the following upon submission:
$ condor_submit tutorial03.submit Submitting job(s).......... 10 job(s) submitted to cluster 1444786.
Look at the output files in the log directory and notice how each job received its own separate output file:
$ ls ./log job.1444786.0.error job.1444786.1.error job.1444786.2.error job.1444786.3.error job.1444786.4.error job.1444786.5.error job.1444786.6.error job.1444786.7.error job.1444786.8.error job.1444786.9.error job.1444786.0.log job.1444786.1.log job.1444786.2.log job.1444786.3.log job.1444786.4.log job.1444786.5.log job.1444786.6.log job.1444786.7.log job.1444786.8.log job.1444786.9.log job.1444786.0.output job.1444786.1.output job.1444786.2.output job.1444786.3.output job.1444786.4.output job.1444786.5.output job.1444786.6.output job.1444786.7.output job.1444786.8.output job.1444786.9.output
Where did jobs run?
When we start submitting a lot of simultaneous jobs into the queue, it might
be worth looking at where they run. To get that information, we'll use a
condor_history commands. First, run
condor_history -long jobid
for your first job. Again the output is quite long:
$ condor_history -long 1444786 BlockWriteKbytes = 0 BlockReads = 0 DiskUsage_RAW = 36 ...
Looking through here for a hostname, we can see that the parameter
that we want to know is
LastRemoteHost. That's what job slot our job
ran on. With that detail, we can construct a shell command to get
the execution node for each of our 100 jobs, and we can plot the
spread. LastRemoteHost normally combines a slot name and a host name,
separated by an @ symbol, so we'll use the UNIX cut command to slice off
the slot name and look only at hostnames. We'll cut again on the period
in the hostname to grab the domain where the job ran.
For illustration, the author has submitted a thousand jobs for a more interesting distribution output.
$ condor_history -format '%s\n' LastRemoteHost 942 | cut -d@ -f2 | distribution --height=100 Val |Ct (Pct) Histogram [netid@loginNN log]$ condor_history -format '%s\n' LastRemoteHost 959 | cut -d@ -f2 | cut -d. -f2,3 | distribution --height=100 Val |Ct (Pct) Histogram mwt2.org |456 (46.77%) +++++++++++++++++++++++++++++++++++++++++++++++++++++ uchicago.edu |422 (43.28%) +++++++++++++++++++++++++++++++++++++++++++++++++ local |28 (2.87%) ++++ t2.ucsd |23 (2.36%) +++ phys.uconn |12 (1.23%) ++ tusker.hcc |10 (1.03%) ++ ...
The distribution program reduces a list of hostnames to a set of
hostnames with no duplication (much like
sort | uniq -c), but
additionally plots a distribution histogram on your terminal
window. This is nice for seeing how Condor selected your execution
There is also
condor_plot a command that plots similar information in a
HTML page. You can have bar plots, pie charts and more.
On occasion, jobs will need to be removed for a variety of reasons
(incorrect parameters, errors in submission, etc.). In these instances,
condor_rm command can be used to remove an entire job submission
or just particular jobs in a submission. The
condor_rm command accepts
a cluster id, a job id, or username and will remove an entire cluster
of jobs, a single job, or all the jobs belonging to a given user
respectively. E.g. if a job submission generates 100 jobs and is
assigned a cluster id of 103, then
condor_rm 103.0 will remove the
first job in the cluster. Likewise,
condor_rm 103 will remove all
the jobs in the job submission and
condor_rm [username] will remove
all jobs belonging to the user. The
condor_rm documenation has more
details on using
condor_rm including ways to remove jobs based on other
We recommend you read about how to steer your jobs with HTCondor job requirements - this will allow you to select good resources for your workload. Please see this page
This page was updated on Mar 31, 2020 at 13:45 from tutorials/tutorial-quickstart/README.md.