Run Bash Script As Slurm Pipeline through rcbio/1.2
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This page shows you how to run a regular bash script as a pipeline. The runAsPipeline
 script, accessible through the rcbio/1.2
 module, converts an input bash script to a pipeline that easily submits jobs to the Slurm scheduler for you.
Features of the new pipeline:
Submit each step as a cluster job usingÂ
sbatch
.Automatically arrange dependencies among jobs.
Email notifications are sent when each job fails or succeeds.
If a job fails, all its downstream jobs automatically are killed.
When re-running the pipeline on the same data folder, if there are any unfinished jobs, the user is asked to kill them or not.
When re-running the pipeline on the same data folder, the user is asked to confirm to re-run or not if a step was done successfully earlier.
Please read below for an example.
Log on to O2
If you need help connecting to O2, please review the Using Slurm Basic and the How to Login to O2 wiki pages.
From Windows, use the graphical PuTTY program to connect to o2.hms.harvard.edu
 and make sure the port is set to the default value of 22.
From a Mac Terminal, use the ssh
 command, inserting your eCommons ID instead of user123:
ssh user123@o2.hms.harvard.edu
Start interactive job, and create working folder
For example, for user abc123, the working directory will be
srun --pty -p interactive -t 0-12:0:0 --mem 2000MB -c 1 /bin/bash
mkdir /n/scratch/users/a/abc123/testRunBashScriptAsSlurmPipeline
cd /n/scratch/users/a/abc123/testRunBashScriptAsSlurmPipeline
Load the pipeline related modules
# This will setup the path and environmental variables for the pipeline
module load rcbio/1.2
Build some testing data in the current folder
Take a look at the example files
The original bash script
How does this bash script work?
There is a loop that goes through the two university text files (for loop in line 6 above) to search for John and Mike (line 10 above), and then searches for Nick and Julia (line 12 above).  After all searching is finished (line 13 above), then the results are merged into a single text file (line 15 above) . This means that the merge step (line 15 above) has to wait until the earlier two steps (line 10 and 12 above) are finished. However, the runAsPipelineÂ
workflow builder can't read this script directly. We will need to create a modified bash script that adds parts that explicitly tell the workflow builder the order in which the jobs need to run, among other things.Â
The modified bash script
Notice that there are a few things added to the script here:
Step 1 is denoted byÂ
#@1,0,find1,u,sbatch -p short -c 1 -t 50:0 (line 10 above), which
 means this is step 1 that depends on no other step, is named find1, and file $u
 needs to be copied to theÂ/tmp
 directory. The sbatch command tells the pipeline runner the sbatch command to run this step. ÂStep 2 is denoted byÂ
#@2,0,find2,u (line 13 above),
 which means this is step2 that depends on no other step, is named find2, and file $u needs to be copy toÂ/tmp
 directory. The sbatch command tells the pipeline runner the sbatch command to run this step. ÂStep 3 is denoted byÂ
#@3,1.2,merge, (line 18), whichÂ
means that this is step3 that depends on step1 and step2, and the step is named merge. Notice, there is no sbatch here,  so the pipeline runner will use default sbatch command from command line (see below). Â
Notice the format of step annotation is #@stepID,dependIDs,stepName,reference,sbatchOptions. Reference is optional, which allows the pipeline runner to copy data (file or folder) to local /tmp folder on the computing node to speed up the software. sbatchOptions is also optional, and when it is missing, the pipeline runner will use the default sbatch command given from command line (see below).
Here are two more examples:
#@4,1.3,map,,sbatch -p short -c 1 -t 50:0
  Means step4 depends on step1 and step3, named map, no reference data to copy, with sbatch -p short -c 1 -t 50:0
#@3,1.2,align,db1.db2Â
 Means step3 depends on step1 and step2, named align, $db1 and $db2 as reference data to be copied to /tmp , with default sbatch command (see below).
Test run the modified bash script as a pipeline
This command will generate new bash script named slurmPipeLine.201801100946.sh
 in flag folder (201801100946
 is the timestamp that runAsPipeline
 was invoked at). Then test run it, meaning does not really submit jobs, but only create a fake job id, 123
 for each step. If you were to append runÂ
at the end of the command, the pipeline would actually be submitted to the Slurm scheduler.
Ideally, with 'useTmp', the software should run faster using local /tmp
 disk space for database/reference than the network storage. For this small query, the difference is small, or even slower if you use local /tmp
. If you don't need /tmp,
you can use noTmp.
With useTmp, the pipeline runner copy related data to /tmp
and all file paths will be automatically updated to reflect a file's location in /tmp when using the useTmp option.Â
Sample output from the test run
Note that only step 2 used -t 50:0
, and all other steps used the default -t 10:0
. The default walltime limit was set in the runAsPipeline
 command, and the walltime parameter for step 2 was set in the bash_script_v2.sh
 script.
Run the modified bash script as a pipeline
Thus far in the example, we have not actually submitted any jobs to the scheduler. To submit the pipeline, you will need to append the run
 parameter to the command. If run
 is not specified, test
 mode will be used, which does not submit jobs and gives theplaceholder of 123Â
for jobids in the command's output.Â
Monitoring the jobs
You can use the command:
To see the job status (running, pending, etc.). You also get two emails for each step, one at the start of the step, one at the end of the step.
Check job logs
You can use the command:
This command list all the logs created by the pipeline runner. *.sh files are the slurm scripts for each step, *.out files are output files for each step, *.success files means job successfully finished for each step and *.failed means job failed for each steps.
You also get two emails for each step, one at the start of the step, one at the end of the step.
Cancel all jobs
You can use the command to cancel running and pending jobs:
Re-run the pipeline
You can rerun this command in the same folder
This command will check if the earlier run is finished or not. If not, ask user to kill the running jobs or not, then ask user to rerun the successfully finished steps or not. Click 'y', it will rerun, directly press 'enter' key, it will not rerun.Â
Re-run a single job manually
For details about the second option:Â Get more informative slurm email notification and logs through rcbio/1.2Â
To run your own script as Slurm pipeline
If you have a bash script with multiple steps and you wish to run it as Slurm pipeline, modify your old script and add the notation to mark the start and end of any loops, and the start of any step for which you want to submit as an sbatch
 job. Then you can use runAsPipelineÂ
with your modified bash script, as detailed above.Â
How does it work?
In case you wonder how it works, here is a simple example to explain:
For each step per loop, the pipeline runner creates a file looks like this (here it is named flag.sh):Â
Then submit with:Â
sendJobFinishEmail.sh
is in /n/app/rcbio/1.2/bin/
Let us know if you have any questions by emailing rchelp@hms.harvard.edu. Please include your working folder and the commands used in your email. Any comments and suggestions are welcome!
We have additional example ready-to-run workflows available, which may be of interest to you.