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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/1.0 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 using 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.

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If you need help connecting to O2, please review the Using Slurm Basic wiki page.

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 -n 1 /bin/bash
mkdir /n/scratch3/users/a/abc123/testRunBashScriptAsSlurmPipeline  
cd /n/scratch3/users/a/abc123/testRunBashScriptAsSlurmPipeline

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Load the pipeline related modules

# This will setup the path and environmental variables for the pipeline
module load rcbio/1.0

Build some testing data in the current folder

echo -e "John Paul\nMike Smith\nNick Will\nJulia Johnson\nTom Jones"  > universityA.txt
cp universityA.txt universityB.txt

Take a look at the example files

# this command shows the content of file universityA.txt
cat universityA.txt

# Below is the content of universityA.txt
John Paul
Mike Smith
Nick Will
Julia Johnson
Tom Jones

# this command shows the content of file universityB.txt
cat universityB.txt

# below is the content of universityB.txt
John Paul
Mike Smith
Nick Will
Julia Johnson
Tom Jones

The original bash script

cp /n/app/rcbio/1.0/bin/bash_script_v1.sh .
cat bash_script_v1.sh

# Below is the conten of bash_script_v1.sh

#!/bin/sh
for i in A B; do            

    u=university$i.txt   

    grep -H John $u >>  John.txt; grep -H Mike $u >>  Mike.txt       
  
    grep -H Nick $u >>  Nick.txt; grep -H Julia $u >>  Julia.txt
done

cat John.txt Mike.txt Nick.txt Julia.txt > all.txt

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The modified bash script

cp /n/app/rcbio/1.0/bin/bash_script_v2.sh .
cat bash_script_v2.sh

# Below is the conten of bash_script_v2.sh
#!/bin/sh

#loopStart,i	
for i in A B; do            
    u=university$i.txt    
            
    #@1,0,find1,u,sbatch -p short -n 1 -t 50:0
    grep -H John $u >>  John.txt; grep -H Mike $u >>  Mike.txt        
     
    #@2,0,find2,u,sbatch -p short -n 1 -t 50:0
    grep -H Nick $u >>  Nick.txt; grep -H Julia $u >>  Julia.txt

#loopEnd                     
done

#@3,1.2,merge     
cat John.txt Mike.txt Nick.txt Julia.txt > all.txt

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Notice that there are a few things added to the script here:

• before the loop starts, #loopStart,i was added (line 7 above). Here the variable i is looping variable, which will be recognized by the pineline runner.

• before the loop ends, #loopEnd was added (line 17 above). This will be recognized by the pineline runner.

• Step 1 is denoted by #@1,0,find1,u,sbatch -p short -n 1 -t 50:0 (line 11 above), which means this is step 1 that depends on no other step, is named find1, and file $u needs to be copied to the /tmp directory. The sbatch command tells the pipeline runner the sbatch command to run this step.  

• Step 2 is denoted by #@2,0,find2,u (line 14 above), which means this is step2 that depends on no other step, is named find2, and file $u needs to be copy to /tmp directory. The sbatch command tells the pipeline runner the sbatch command to run this step.  

• Step 3 is denoted by #@3,1.2,merge, which 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 (see below).   

Notice the format of step annotaion is #@stepID,dependIDs,stepName,reference,sbatchOptions. Reference is optional, which allows the pineline 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).

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Test run the modified bash script as a pipeline

runAsPipeline bash_script_v2.sh "sbatch -p short -t 10:0 -n 1" useTmp

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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.

runAsPipeline bash_script_v2.sh "sbatch -p short -t 10:0 -n 1" useTmp

# Below is the output: 
converting bash_script_v2.sh to flag/slurmPipeLine.201801161424.sh

find loopStart: #loopStart,i	

find job marker:
#@1,0,find1,u:     

find job:
grep -H John $u >>  John.txt; grep -H Mike $u >>  Mike.txt        

find job marker:
#@2,0,find2,u,sbatch -p short -n 1 -t 50:0
sbatch options: sbatch -p short -n 1 -t 50:0

find job:
grep -H Nick $u >>  Nick.txt; grep -H Julia $u >>  Julia.txt
find loopend: #loopEnd                     

find job marker:
#@3,1.2,merge:           

find job:
cat John.txt Mike.txt Nick.txt Julia.txt > all.txt
flag/slurmPipeLine.201801161424.sh bash_script_v2.sh is ready to run. Starting to run ...
Running flag/slurmPipeLine.201801161424.sh bash_script_v2.sh
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step: 1, depends on: 0, job name: find1, flag: find1.A reference: .u
depend on no job
sbatch -p short -t 10:0 -n 1 --nodes=1  -J 1.0.find1.A -o /n/scratch2/kmk34/testRunBashScriptAsSlurmPipeline/flag/1.0.find1.A.out -e /n/scratch2/kmk34/testRunBashScriptAsSlurmPipeline/flag/1.0.find1.A.out /n/scratch2/kmk34/testRunBashScriptAsSlurmPipeline/flag/1.0.find1.A.sh 
# Submitted batch job 123

step: 2, depends on: 0, job name: find2, flag: find2.A reference: .u
depend on no job
sbatch -p short -n 1 -t 50:0 --nodes=1  -J 2.0.find2.A -o /n/scratch2/kmk34/testRunBashScriptAsSlurmPipeline/flag/2.0.find2.A.out -e /n/scratch2/kmk34/testRunBashScriptAsSlurmPipeline/flag/2.0.find2.A.out /n/scratch2/kmk34/testRunBashScriptAsSlurmPipeline/flag/2.0.find2.A.sh 
# Submitted batch job 123

step: 1, depends on: 0, job name: find1, flag: find1.B reference: .u
depend on no job
sbatch -p short -t 10:0 -n 1 --nodes=1  -J 1.0.find1.B -o /n/scratch2/kmk34/testRunBashScriptAsSlurmPipeline/flag/1.0.find1.B.out -e /n/scratch2/kmk34/testRunBashScriptAsSlurmPipeline/flag/1.0.find1.B.out /n/scratch2/kmk34/testRunBashScriptAsSlurmPipeline/flag/1.0.find1.B.sh 
# Submitted batch job 123

step: 2, depends on: 0, job name: find2, flag: find2.B reference: .u
depend on no job
sbatch -p short -n 1 -t 50:0 --nodes=1  -J 2.0.find2.B -o /n/scratch2/kmk34/testRunBashScriptAsSlurmPipeline/flag/2.0.find2.B.out -e /n/scratch2/kmk34/testRunBashScriptAsSlurmPipeline/flag/2.0.find2.B.out /n/scratch2/kmk34/testRunBashScriptAsSlurmPipeline/flag/2.0.find2.B.sh 
# Submitted batch job 123

step: 3, depends on: 1.2, job name: merge, flag: merge reference:
depend on multiple jobs
sbatch -p short -t 10:0 -n 1 --nodes=1 --dependency=afterok:123:123:123:123 -J 3.1.2.merge -o /n/scratch2/kmk34/testRunBashScriptAsSlurmPipeline/flag/3.1.2.merge.out -e /n/scratch2/kmk34/testRunBashScriptAsSlurmPipeline/flag/3.1.2.merge.out /n/scratch2/kmk34/testRunBashScriptAsSlurmPipeline/flag/3.1.2.merge.sh 
# Submitted batch job 123

all submitted jobs:
job_id       depend_on              job_flag  
123         null                  1.0.find1.A
123         null                  2.0.find2.A
123         null                  1.0.find1.B
123         null                  2.0.find2.B
123         ..123.123..123.123    3.1.2.merge
---------------------------------------------------------

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You can use the command:

squeue -u $USER

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.

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You can use the command:

ls -l flag

This command list all the logs created by the pipeline runner. *.sh files are the slurm scripts for eash 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.

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You can rerun this command in the same folder

runAsPipeline bash_script_v2.sh "sbatch -p short -t 10:0 -n 1" useTmp run

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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 runAsPipeline with your modified bash script, as  as detailed above. 

How does it work

In case you wonder how it works, here is a simple example to expain:

For each step per loop, the pipeline runner reates a file looks like this (here it is named flag.sh): 

#!/bin/bash 
srun -n 1 bash -c "{ echo I am running...; hostname; otherCommands; } && touch flag.success" 
sleep 5 
export SLURM_TIME_FORMAT=relative 
echo Job done. Summary: 
sacct --format=JobID,Submit,Start,End,State,Partition,ReqTRES%30,CPUTime,MaxRSS,NodeList%30 --units=M -j $SLURM_JOBID 
sendJobFinishEmail.sh flag 
[ -f flag.success ] && exit 0 || exit 1 

Then submit with: 

sbatch -p short -t 10:0 -o flag.out -e flag.out flag.sh

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