Difference between revisions of "Job Arrays"

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== Job Array Introduction ==
+
== Introduction ==
 +
Job Arrays allow you to run the same job on different datasets without having to create an individual job script for each dataset.  Thus you are easily able to submit hundreds, even thousands of jobs for each different datasets.
 +
This is accomplished by using the #SBATCH --array parameter in the '''SBATCH''' script.  Then using the '''$SLURM_ARRAY_TASK_ID''' environmental variable to specify which dataset to use.  The resources (number of processors, memory, etc) you specify in the job script will be identical for each job in the array.  More details on SLURM job arrays can be found at [https://slurm.schedmd.com/job_array.html https://slurm.schedmd.com/job_array.html]
  
−
Making a new copy of the script and then submitting each one for every input data file is time consuming. An alternative is to make a job array using the -t option in your '''QSUB''' '''submission''' '''script'''. The -t option allows many copies of the same script to be queued all at once. You can use the '''$PBS_ARRAYID''' environmental variable to differentiate between the different jobs in the array. The amount of resources you specify in the '''QSUB''' '''submission''' '''script''' is the amount of resources the '''job script''' gets each time it is called.
+
== --array parameter ==
 +
*This will create 10 jobs with the $SLURM_ARRAY_TASK_ID iterating 1 through 10 (1,2,3,4,...,8,9.10)
 +
<pre>#SBATCH --array 1-10</pre>
 +
*This will create 10 jobs with the $SLURM_ARRAY_TASK_ID iterating 1 through 19 with step size 2 (1,3,5,7,...,17,19)
 +
<pre>#SBATCH --array 1-20:2</pre>
 +
*This will create 5 jobs with the $SLURM_ARRAY_TASK_ID set to the 5 specified values (1,5,10,15,20)
 +
<pre>#SBATCH --array 1,5,10,15,20</pre>
 +
*This will create 20 jobs with the $SLURM_ARRAY_TASK_ID iterating 1 through 20 (1,2,3,4...,18,19,20) but only run 4 of the jobs at time.
 +
<pre>#SBATCH --array=1-20%4</pre>
  
−
In this tutorial, we will be using '''three''' files:
+
== Example Script ==
−
<pre>array.sh
+
This script will submit 10 jobs. Each job will do the following
−
job.pl
+
*wait for 10 seconds (sleep 10)
−
job.conf
+
*Output the hostname of the node it ran on (echo "Hostname: `hostname`")
−
</pre>
+
*Output the $SLURM_ARRAY_TASK_ID
−
Lets say you want to run '''16 jobs'''. Instead of submitting 16 different jobs, you can submit one job, but use the ''''-t'''' parameter and the '''PBS_ARRAYID''' variable. You can read more about the&nbsp;&nbsp;''''-t''''&nbsp;&nbsp;parameter at&nbsp;[http://docs.adaptivecomputing.com/torque/4-1-4/Content/topics/commands/qsub.htm#T http://docs.adaptivecomputing.com/torque/4-1-4/Content/topics/commands/qsub.htm]
+
*The output file slurm-%A_%a.out will have that information. '''%A''' is the SLURM job number.  '''%a''' is value of '''$SLURM_ARRAY_TASK_ID'''
−
<pre>#PBS -t 0-15</pre>
+
 
−
The -t parameter sets the range of the '''PBS_ARRAYID''' variable. So setting it to
+
<pre>#!/bin/bash
−
<pre>#PBS -t 0-4</pre>
+
# ----------------SBATCH Parameters----------------- #
−
will cause the qsub script to call the script 5 times, each time updating the '''PBS_ARRAYID''', from 0 to 4 , which results in
+
#SBATCH -p normal
−
<pre>( perl job.pl $PBS_ARRAYID )
+
#SBATCH -n 1
 +
#SBATCH -N 1
 +
#SBATCH --mail-user youremail@illinois.edu
 +
#SBATCH --mail-type BEGIN,END,FAIL
 +
#SBATCH -J example_array
 +
#SBATCH -D /home/a-m/USERNAME
 +
#SBATCH -o /home/a-m/USERNAME/slurm-%A_%a.out
 +
#SBATCH --array 1-10
  
−
perl job.pl 0
+
# ----------------Your Commands------------------- #
−
perl job.pl 1
 
−
perl job.pl 2
 
−
perl job.pl 3
 
−
perl job.pl 4
 
−
</pre>
 
−
== array.sh (Example submission script) ==
 
  
−
This submission script changes to the current working directory, submits 16 jobs, and reserves 2 processors and 1gb of ram for each job.
+
sleep 10
 +
echo "Hostname: `hostname`"
 +
echo "Job Array Number: $SLURM_ARRAY_TASK_ID"
  
−
It redirects the stderror and stdout into one file, andemails the job owner on completion or abort.
+
</pre>
 +
*10 different output files will be created.  The output in each one will be like below
 +
<pre>
 +
Hostname: compute-0-16
 +
Job Array Number: 10
 +
</pre>
  
−
For each job , it passes the '-t' parameter to the job.pl script, which in this case is 0 to 15
+
== Example - Ordered List ==
 +
*Say you have a directory with input data files that are numbered sequentially like below.
 +
*You want to run the program FastQC against these files.
 +
*The input data is located in the directory '''input_data'''
 +
*The results will be placed in the directory '''results'''
 +
<pre>yeast_1_50K.fastq
 +
yeast_2_50K.fastq
 +
yeast_3_50K.fastq
 +
yeast_4_50K.fastq
 +
yeast_5_50K.fastq
 +
yeast_6_50K.fastq
 +
</pre>
 +
*The job array script would be like below.
 
<pre>#!/bin/bash
 
<pre>#!/bin/bash
−
# ----------------QSUB Parameters----------------- #
+
# ----------------SBATCH Parameters----------------- #
−
#PBS -q default
+
#SBATCH -p normal
−
#PBS -l nodes=1:ppn=2,mem=1000mb
+
#SBATCH -n 1
−
#PBS -M youremail@illinois.edu
+
#SBATCH -N 1
−
#PBS -m abe
+
#SBATCH --mail-user youremail@illinois.edu
−
#PBS -N array_of_perl_jobs
+
#SBATCH --mail-type BEGIN,END,FAIL
−
#PBS -t 0-15
+
#SBATCH -J example_array
−
#PBS -j oe
+
#SBATCH -D /home/a-m/USERNAME
−
# ----------------Load Modules-------------------- #
+
#SBATCH -o /home/a-m/USERNAME/slurm-%A_%a.out
−
module load perl/5.16.1
+
#SBATCH --array 1-6
 +
# ----------------Load Modules--------------------
 +
module load FastQC/0.11.5-IGB-gcc-4.9.4-Java-1.8.0_152
 
# ----------------Your Commands------------------- #
 
# ----------------Your Commands------------------- #
−
cd $PBS_O_WORKDIR
 
−
perl job.pl $PBS_ARRAYID</pre>
 
−
== job.pl (Example Perl script ) ==
 
−
<pre>#!/usr/bin/env perl
 
−
#This script echos the job array element that has been passed in
 
  
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use strict;
+
echo "Starting FastQC Job"
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my $argument = shift @ARGV;
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fastqc -o results/ input_data/yeast_${SLURM_ARRAY_TASK_ID}_50K.fastq
−
my $experimentID = $argument + 1;
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echo "Finishing FastQC Job"
−
my $experimentName = `head -n $argument job.conf | tail -n1`;
 
−
 
 
−
print "This is job number $argument \n";
 
−
print "About to perform experimentID: $argument experimentName:$experimentName\n";
 
 
</pre>
 
</pre>
  
 +
== Example - Unordered List ==
 +
*This is for a list of data files that do not have sequential numbers in the filename.
 +
*The input data is located in the directory '''input_data'''
 +
*The results will be located in the directory '''results'''
 +
*This grabs a file from the '''input_data''' directory ('''ls input_data/ | sed -n ${SLURM_ARRAY_TASK_ID}p''') , and then puts that in the variable '''$file'''.
 +
*Then runs fastqc using the '''$file''' variable
  
−
== job.conf (example configuration file) ==
+
<pre>#!/bin/bash
−
<pre>
+
# ----------------SBATCH Parameters----------------- #
−
dataset0
+
#SBATCH -p normal
−
dataset1
+
#SBATCH -n 1
−
dataset2
+
#SBATCH -N 1
−
dataset3
+
#SBATCH --mail-user youremail@illinois.edu
−
dataset4
+
#SBATCH --mail-type BEGIN,END,FAIL
−
dataset5
+
#SBATCH -J example_array
−
..
+
#SBATCH -D /home/a-m/USERNAME
−
dataset650
+
#SBATCH -o /home/a-m/USERNAME/slurm-%A_%a.out
 +
#SBATCH --array 1-6
 +
# ----------------Load Modules--------------------
 +
module load FastQC/0.11.5-IGB-gcc-4.9.4-Java-1.8.0_152
 +
# ----------------Your Commands------------------- #
 +
echo "Starting FastQC Job"
 +
file=$(ls input_data/ | sed -n ${SLURM_ARRAY_TASK_ID}p)
 +
fastqc -o results input_data/${file}
 +
echo "Finishing FastQC Job"
 
</pre>
 
</pre>
  
−
== Effectively using the Job Array ==
+
== Example - Combining jobs ==
 +
*What if you have 650 datasets you want to analyze, but you can only submit 80 jobs at a time. Instead of submitting 80 jobs, and waiting for them to finish to submit the next batch, submit a single job array job that can handle all of the datasets.
 +
*You need to divide your datasets into groups.  Below is an example bash code that can do it.
 +
*First, all of your input datasets need to be a folder called '''input_data'''
 +
*The variable '''$ITEMS_TO_PROCESS''' specifies the size of each group of jobs should be
 +
*The line '''JOBLIST=$(ls input_data/)''' will store the list of the files in the variable '''$JOB_LIST'''
 +
*Then it will calculate which jobs go into which group using '''$SLURM_ARRAY_TASK_ID''' and '''$ITEMS_TO_PROCESS'' to calculate the '''$START_LINE''' and '''$END_LINE'''
 +
<pre>ITEMS_TO_PROCESS=10
 +
JOBLIST=$(ls input_data/)
 +
START_LINE=$(( ${SLURM_ARRAY_TASK_ID} * ${ITEMS_TO_PROCESS}) +1 )
 +
END_LINE=$(( ${START_LINE] + ${ITEMS_TO_PROCESS} ) -1 )
  
−
You will need to have an additional script or configuration file to use the '''PBS_ARRAYID''' effectively. Otherwise you are simply passing an integer into your tool, which may not have much meaning. Below is an example of a configuration file that specifies an experiment to run for job.pl . As the '''PBS_ARRAYID '''variable increments, the script is instructed to perform its action on the next experiment.
+
</pre>
 +
*Below is the full script
 +
*In order to use the following script, you will need to properly set
 +
*'--array' (the number of array elements you want)
 +
*ITEMS_TO_PROCESS (the size of each group of jobs)
  
−
== Default vs Highthroughput Queue ==
+
<pre>#!/bin/bash
 +
# ----------------SBATCH Parameters----------------- #
 +
#SBATCH -p normal
 +
#SBATCH -n 1
 +
SSBATCH -N 1
 +
#SBATCH --mail-user youremail@illinois.edu
 +
#SBATCH --mail-type BEGIN, END, FAIL
 +
#SBATCH -J array_of_jobs
 +
#SBATCH --array 1-10
 +
#SBATCH -D /home/a-m/USERNAME
  
−
The default queue only allows you to submit 80 jobs, but they do not use a walltime limit.
+
# ----------------Load Modules-------------------- #
 +
module load FastQC/0.11.5-IGB-gcc-4.9.4-Java-1.8.0_152
 +
# ----------------Your Commands------------------- #
  
−
This queue is most appropriate for a lot of jobs that may run a long time.
+
ITEMS_TO_PROCESS=10
 +
JOBLIST=$(ls input_data/)
  
−
The high throughput queue allows you to submit 500 jobs, but they have a walltime limit.
+
START_LINE=$(( ${SLURM_ARRAY_TASK_ID} * ${ITEMS_TO_PROCESS}) + 1)
 +
END_LINE=$(( ${START_LINE] + ${ITEMS_TO_PROCESS} ) -1)
  
−
This queue is most appropriate for a lot of jobs that you want to run in parallel and finish quickly.
 
  
−
== Effectively Using job_array_index ==
+
#Iteration through START_LINE and END_LINE
−
You have 650 datasets you want to analyze, but you can only submit 80 jobs at a time.
+
for line in `seq ${START_LINE} ${END_LINE}`
−
Instead of submitting 80 jobs, and waiting for them to finish, submit a single 80 element array job that can handle all of the datasets.
+
do
−
 
+
    DATA_FILE=$( head -n $line ${JOBLIST} | tail -n 1 )
−
A simple formula for dividing and sending your datasets to your script is as follows:
+
    fastqc -o results input_data/${DATA_FILE}
−
data sets per job = ceiling ( Number of datasets / Number of Job Elements )
+
done
−
data sets per Job = ceiling ( 650 / 80 ) = ceiling(8.12500) = 9
+
</pre>
−
 
 
−
So that means that your 80 jobs are each responsible for handling 9 datasets.
 
−
So each time you call your job script, you need to pass it the position in the list of datasets , which is the $PBS_ARRAY_ID and the data sets per job ( N )
 
−
That way, your job will be able to determine which datasets from the list you need to process.
 
−
 
 
−
Here is some simple pseudo code for this situation
 
−
<pre>
 
−
data sets per job = N
 
−
startLineNumber =  $PBS_ARRAY_ID * datasets per job
 
−
endLineNumber = startLineNumber + data_sets_per_job
 
  
−
open list of data:
+
== Resources ==
−
      go to  startLineNumber
+
[https://slurm.schedmd.com/job_array.html https://slurm.schedmd.com/job_array.html]
−
                get dataset
 
−
                do work with dataset
 
−
                if lineNumber <  endLineNumber
 
−
                go to next line
 
−
</pre>
 

Latest revision as of 12:00, 2 October 2019

Introduction[edit]

Job Arrays allow you to run the same job on different datasets without having to create an individual job script for each dataset. Thus you are easily able to submit hundreds, even thousands of jobs for each different datasets. This is accomplished by using the #SBATCH --array parameter in the SBATCH script. Then using the $SLURM_ARRAY_TASK_ID environmental variable to specify which dataset to use. The resources (number of processors, memory, etc) you specify in the job script will be identical for each job in the array. More details on SLURM job arrays can be found at https://slurm.schedmd.com/job_array.html

--array parameter[edit]

  • This will create 10 jobs with the $SLURM_ARRAY_TASK_ID iterating 1 through 10 (1,2,3,4,...,8,9.10)
#SBATCH --array 1-10
  • This will create 10 jobs with the $SLURM_ARRAY_TASK_ID iterating 1 through 19 with step size 2 (1,3,5,7,...,17,19)
#SBATCH --array 1-20:2
  • This will create 5 jobs with the $SLURM_ARRAY_TASK_ID set to the 5 specified values (1,5,10,15,20)
#SBATCH --array 1,5,10,15,20
  • This will create 20 jobs with the $SLURM_ARRAY_TASK_ID iterating 1 through 20 (1,2,3,4...,18,19,20) but only run 4 of the jobs at time.
#SBATCH --array=1-20%4

Example Script[edit]

This script will submit 10 jobs. Each job will do the following

  • wait for 10 seconds (sleep 10)
  • Output the hostname of the node it ran on (echo "Hostname: `hostname`")
  • Output the $SLURM_ARRAY_TASK_ID
  • The output file slurm-%A_%a.out will have that information. %A is the SLURM job number. %a is value of $SLURM_ARRAY_TASK_ID
#!/bin/bash
# ----------------SBATCH Parameters----------------- #
#SBATCH -p normal
#SBATCH -n 1
#SBATCH -N 1
#SBATCH --mail-user youremail@illinois.edu
#SBATCH --mail-type BEGIN,END,FAIL 
#SBATCH -J example_array
#SBATCH -D /home/a-m/USERNAME
#SBATCH -o /home/a-m/USERNAME/slurm-%A_%a.out
#SBATCH --array 1-10

# ----------------Your Commands------------------- #

sleep 10
echo "Hostname: `hostname`"
echo "Job Array Number: $SLURM_ARRAY_TASK_ID"
  • 10 different output files will be created. The output in each one will be like below
Hostname: compute-0-16
Job Array Number: 10

Example - Ordered List[edit]

  • Say you have a directory with input data files that are numbered sequentially like below.
  • You want to run the program FastQC against these files.
  • The input data is located in the directory input_data
  • The results will be placed in the directory results
yeast_1_50K.fastq
yeast_2_50K.fastq
yeast_3_50K.fastq
yeast_4_50K.fastq
yeast_5_50K.fastq
yeast_6_50K.fastq
  • The job array script would be like below.
#!/bin/bash
# ----------------SBATCH Parameters----------------- #
#SBATCH -p normal
#SBATCH -n 1
#SBATCH -N 1
#SBATCH --mail-user youremail@illinois.edu
#SBATCH --mail-type BEGIN,END,FAIL 
#SBATCH -J example_array
#SBATCH -D /home/a-m/USERNAME
#SBATCH -o /home/a-m/USERNAME/slurm-%A_%a.out
#SBATCH --array 1-6
# ----------------Load Modules--------------------
module load FastQC/0.11.5-IGB-gcc-4.9.4-Java-1.8.0_152
# ----------------Your Commands------------------- #

echo "Starting FastQC Job"
fastqc -o results/ input_data/yeast_${SLURM_ARRAY_TASK_ID}_50K.fastq
echo "Finishing FastQC Job"

Example - Unordered List[edit]

  • This is for a list of data files that do not have sequential numbers in the filename.
  • The input data is located in the directory input_data
  • The results will be located in the directory results
  • This grabs a file from the input_data directory (ls input_data/ | sed -n ${SLURM_ARRAY_TASK_ID}p) , and then puts that in the variable $file.
  • Then runs fastqc using the $file variable
#!/bin/bash
# ----------------SBATCH Parameters----------------- #
#SBATCH -p normal
#SBATCH -n 1
#SBATCH -N 1
#SBATCH --mail-user youremail@illinois.edu
#SBATCH --mail-type BEGIN,END,FAIL 
#SBATCH -J example_array
#SBATCH -D /home/a-m/USERNAME
#SBATCH -o /home/a-m/USERNAME/slurm-%A_%a.out
#SBATCH --array 1-6
# ----------------Load Modules--------------------
module load FastQC/0.11.5-IGB-gcc-4.9.4-Java-1.8.0_152
# ----------------Your Commands------------------- #
echo "Starting FastQC Job"
file=$(ls input_data/ | sed -n ${SLURM_ARRAY_TASK_ID}p)
fastqc -o results input_data/${file}
echo "Finishing FastQC Job"

Example - Combining jobs[edit]

  • What if you have 650 datasets you want to analyze, but you can only submit 80 jobs at a time. Instead of submitting 80 jobs, and waiting for them to finish to submit the next batch, submit a single job array job that can handle all of the datasets.
  • You need to divide your datasets into groups. Below is an example bash code that can do it.
  • First, all of your input datasets need to be a folder called input_data
  • The variable $ITEMS_TO_PROCESS specifies the size of each group of jobs should be
  • The line JOBLIST=$(ls input_data/) will store the list of the files in the variable $JOB_LIST
  • Then it will calculate which jobs go into which group using $SLURM_ARRAY_TASK_ID' and $ITEMS_TO_PROCESS to calculate the $START_LINE and $END_LINE
ITEMS_TO_PROCESS=10
JOBLIST=$(ls input_data/)
START_LINE=$(( ${SLURM_ARRAY_TASK_ID} * ${ITEMS_TO_PROCESS}) +1 )
END_LINE=$(( ${START_LINE] + ${ITEMS_TO_PROCESS} ) -1 )
  • Below is the full script
  • In order to use the following script, you will need to properly set
  • '--array' (the number of array elements you want)
  • ITEMS_TO_PROCESS (the size of each group of jobs)
#!/bin/bash
# ----------------SBATCH Parameters----------------- #
#SBATCH -p normal
#SBATCH -n 1
SSBATCH -N 1
#SBATCH --mail-user  youremail@illinois.edu
#SBATCH --mail-type BEGIN, END, FAIL 
#SBATCH -J array_of_jobs
#SBATCH --array 1-10
#SBATCH -D /home/a-m/USERNAME

# ----------------Load Modules-------------------- #
module load FastQC/0.11.5-IGB-gcc-4.9.4-Java-1.8.0_152
# ----------------Your Commands------------------- #

ITEMS_TO_PROCESS=10
JOBLIST=$(ls input_data/)

START_LINE=$(( ${SLURM_ARRAY_TASK_ID} * ${ITEMS_TO_PROCESS}) + 1)
END_LINE=$(( ${START_LINE] + ${ITEMS_TO_PROCESS} ) -1)


#Iteration through START_LINE and END_LINE
for line in `seq ${START_LINE} ${END_LINE}`
do
    DATA_FILE=$( head -n $line ${JOBLIST} | tail -n 1 )
    fastqc -o results input_data/${DATA_FILE}
done

Resources[edit]

https://slurm.schedmd.com/job_array.html

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