GNU Parallel Tutorial
Prerequisites
Input sources
Building the command line
Controlling the output
- Saving output into files
Controlling the execution
Remote execution
Saving to an SQL base (advanced)
- Using multiple workers
--pipe
Shebang
- Input data and parallel command in the same file
- Parallelizing existing scripts
Semaphore
Informational
Profiles
Spread the word

GNU Parallel Tutorial

This tutorial shows off much of GNU parallel's functionality. The tutorial is meant to learn the options in GNU parallel. The tutorial is not to show realistic examples from the real world.

Spend an hour walking through the tutorial. Your command line will love you for it.

Prerequisites

To run this tutorial you must have the following:

parallel >= version 20140622

Install the newest version with:

  (wget -O - pi.dk/3 || curl pi.dk/3/ || fetch -o - http://pi.dk/3) | bash

This will also install the newest version of the tutorial:

  man parallel_tutorial

Most of the tutorial will work on older versions, too.

abc-file:

The file can be generated by:

  parallel -k echo ::: A B C > abc-file

def-file:

The file can be generated by:

  parallel -k echo ::: D E F > def-file

abc0-file:

The file can be generated by:

  perl -e 'printf "A\0B\0C\0"' > abc0-file

abc_-file:

The file can be generated by:

  perl -e 'printf "A_B_C_"' > abc_-file

tsv-file.tsv

The file can be generated by:

  perl -e 'printf "f1\tf2\nA\tB\nC\tD\n"' > tsv-file.tsv

num8

The file can be generated by:

  perl -e 'for(1..8){print "$_\n"}' > num8

num128

The file can be generated by:

  perl -e 'for(1..128){print "$_\n"}' > num128

num30000

The file can be generated by:

  perl -e 'for(1..30000){print "$_\n"}' > num30000

num1000000

The file can be generated by:

  perl -e 'for(1..1000000){print "$_\n"}' > num1000000

num_%header

The file can be generated by:

  (echo %head1; echo %head2; perl -e 'for(1..10){print "$_\n"}') > num_%header

For remote running: ssh login on 2 servers with no password in $SERVER1 and $SERVER2

  SERVER1=server.example.com
  SERVER2=server2.example.net

You must be able to:

  ssh $SERVER1 echo works
  ssh $SERVER2 echo works

It can be setup by running 'ssh-keygen -t dsa; ssh-copy-id $SERVER1' and using an empty pass phrase.

Input sources

GNU parallel reads input from input sources. These can be files, the command line, and stdin (standard input or a pipe).

A single input source

Input can be read from the command line:

  parallel echo ::: A B C

Output (the order may be different because the jobs are run in parallel):

  A
  B
  C

The input source can be a file:

  parallel -a abc-file echo

Output: Same as above.

STDIN (standard input) can be the input source:

  cat abc-file | parallel echo

Output: Same as above.

Multiple input sources

GNU parallel can take multiple input sources given on the command line. GNU parallel then generates all combinations of the input sources:

  parallel echo ::: A B C ::: D E F

Output (the order may be different):

  A D
  A E
  A F
  B D
  B E
  B F
  C D
  C E
  C F

The input sources can be files:

  parallel -a abc-file -a def-file echo

Output: Same as above.

STDIN (standard input) can be one of the input sources using -:

  cat abc-file | parallel -a - -a def-file echo

Output: Same as above.

Instead of -a files can be given after :::::

  cat abc-file | parallel echo :::: - def-file

Output: Same as above.

::: and :::: can be mixed:

  parallel echo ::: A B C :::: def-file

Output: Same as above.

Matching arguments from all input sources

With --xapply you can get one argument from each input source:

  parallel --xapply echo ::: A B C ::: D E F

Output (the order may be different):

  A D
  B E
  C F

If one of the input sources is too short, its values will wrap:

  parallel --xapply echo ::: A B C D E ::: F G

Output (the order may be different):

  A F
  B G
  C F
  D G
  E F

Changing the argument separator.

GNU parallel can use other separators than ::: or ::::. This is typically useful if ::: or :::: is used in the command to run:

  parallel --arg-sep ,, echo ,, A B C :::: def-file

Output (the order may be different):

  A D
  A E
  A F
  B D
  B E
  B F
  C D
  C E
  C F

Changing the argument file separator:

  parallel --arg-file-sep // echo ::: A B C // def-file

Output: Same as above.

Changing the argument delimiter

GNU parallel will normally treat a full line as a single argument: It uses \n as argument delimiter. This can be changed with -d:

  parallel -d _ echo :::: abc_-file

Output (the order may be different):

  A
  B
  C

NULL can be given as \0:

  parallel -d '\0' echo :::: abc0-file

Output: Same as above.

A shorthand for -d '\0' is -0 (this will often be used to read files from find ... -print0):

  parallel -0 echo :::: abc0-file

Output: Same as above.

End-of-file value for input source

GNU parallel can stop reading when it encounters a certain value:

  parallel -E stop echo ::: A B stop C D

Output:

  A
  B

Skipping empty lines

Using --no-run-if-empty GNU parallel will skip empty lines.

  (echo 1; echo; echo 2) | parallel --no-run-if-empty echo

Output:

  1
  2

Building the command line

No command means arguments are commands

If no command is given after parallel the arguments themselves are treated as commands:

  parallel ::: ls 'echo foo' pwd

Output (the order may be different):

  [list of files in current dir]
  foo
  [/path/to/current/working/dir]

The command can be a script, a binary or a Bash function if the function is exported using export -f:

  # Only works in Bash
  my_func() {
    echo in my_func $1
  }
  export -f my_func
  parallel my_func ::: 1 2 3

Output (the order may be different):

  in my_func 1
  in my_func 2
  in my_func 3

Replacement strings

The 7 predefined replacement strings

GNU parallel has several replacement strings. If no replacement strings are used the default is to append {}:

  parallel echo ::: A/B.C

Output:

  A/B.C

The default replacement string is {}:

  parallel echo {} ::: A/B.C

Output:

  A/B.C

The replacement string {.} removes the extension:

  parallel echo {.} ::: A/B.C

Output:

A/B

The replacement string {/} removes the path:

  parallel echo {/} ::: A/B.C

Output:

B.C

The replacement string {//} keeps only the path:

  parallel echo {//} ::: A/B.C

Output:

The replacement string {/.} removes the path and the extension:

  parallel echo {/.} ::: A/B.C

Output:

The replacement string {#} gives the job number:

  parallel echo {#} ::: A B C

Output (the order may be different):

  1
  2
  3

The replacement string {%} gives the job slot number (between 1 and number of jobs to run in parallel):

  parallel -j 2 echo {%} ::: A B C

Output (the order may be different and 1 and 2 may be swapped):

  1
  2
  1

Changing the replacement strings

The replacement string {} can be changed with -I:

  parallel -I ,, echo ,, ::: A/B.C

Output:

  A/B.C

The replacement string {.} can be changed with --extensionreplace:

  parallel --extensionreplace ,, echo ,, ::: A/B.C

Output:

A/B

The replacement string {/} can be replaced with --basenamereplace:

  parallel --basenamereplace ,, echo ,, ::: A/B.C

Output:

B.C

The replacement string {//} can be changed with --dirnamereplace:

  parallel --dirnamereplace ,, echo ,, ::: A/B.C

Output:

The replacement string {/.} can be changed with --basenameextensionreplace:

  parallel --basenameextensionreplace ,, echo ,, ::: A/B.C

Output:

The replacement string {#} can be changed with --seqreplace:

  parallel --seqreplace ,, echo ,, ::: A B C

Output (the order may be different):

  1
  2
  3

The replacement string {%} can be changed with --slotreplace:

  parallel -j2 --slotreplace ,, echo ,, ::: A B C

Output (the order may be different and 1 and 2 may be swapped):

  1
  2
  1

Perl expression replacement string

When predefined replacement strings are not flexible enough a perl expression can be used instead. One example is to remove two extensions: foo.tar.gz becomes foo

  parallel echo '{= s:\.[^.]+$::;s:\.[^.]+$::; =}' ::: foo.tar.gz

Output:

foo

In {= =} you can access all of GNU parallel's internal functions and variables. A few are worth mentioning.

total_jobs() returns the total number of jobs:

  parallel echo Job {#} of {= '$_=total_jobs()' =} ::: {1..5}

Output:

  Job 1 of 5
  Job 2 of 5
  Job 3 of 5
  Job 4 of 5
  Job 5 of 5

Q(...) shell quotes the string:

  parallel echo {} shell quoted is {= '$_=Q($_)' =} ::: '*/!#$'

$job->skip() skips the job:

  parallel echo {= 'if($_==3) { $job->skip() }' =} ::: {1..5}

Output:

@arg contains the input source variables:

  parallel echo {= 'if($arg[1]==$arg[2]) { $job->skip() }' =} ::: {1..3} ::: {1..3}

Output:

If the strings {= and =} cause problems they can be replaced with --parens:

  parallel --parens ,,,, echo ',, s:\.[^.]+$::;s:\.[^.]+$::; ,,' ::: foo.tar.gz

Output: Same as above.

To define a shorthand replacement string use --rpl:

  parallel --rpl '.. s:\.[^.]+$::;s:\.[^.]+$::;' echo '..' ::: foo.tar.gz

Output: Same as above.

If the shorthand starts with { it can be used as a positional replacement string, too:

  parallel --rpl '{..} s:\.[^.]+$::;s:\.[^.]+$::;' echo '{..}' ::: foo.tar.gz

Output: Same as above.

GNU parallel's 7 replacement strings are implemented as this:

  --rpl '{} '
  --rpl '{#} $_=$job->seq()'
  --rpl '{%} $_=$job->slot()'
  --rpl '{/} s:.*/::'
  --rpl '{//} $Global::use{"File::Basename"} ||= eval "use File::Basename; 1;"; $_ = dirname($_);'
  --rpl '{/.} s:.*/::; s:\.[^/.]+$::;'
  --rpl '{.} s:\.[^/.]+$::'

Positional replacement strings

With multiple input sources the argument from the individual input sources can be accessed with {number}:

  parallel echo {1} and {2} ::: A B ::: C D

Output (the order may be different):

  A and C
  A and D
  B and C
  B and D

The positional replacement strings can also be modified using /, //, /., and .:

  parallel echo /={1/} //={1//} /.={1/.} .={1.} ::: A/B.C D/E.F

Output (the order may be different):

  /=B.C //=A /.=B .=A/B
  /=E.F //=D /.=E .=D/E

If a position is negative, it will refer to the input source counted from behind:

  parallel echo 1={1} 2={2} 3={3} -1={-1} -2={-2} -3={-3} ::: A B ::: C D ::: E F

Output (the order may be different):

  1=A 2=C 3=E -1=E -2=C -3=A
  1=A 2=C 3=F -1=F -2=C -3=A
  1=A 2=D 3=E -1=E -2=D -3=A
  1=A 2=D 3=F -1=F -2=D -3=A
  1=B 2=C 3=E -1=E -2=C -3=B
  1=B 2=C 3=F -1=F -2=C -3=B
  1=B 2=D 3=E -1=E -2=D -3=B
  1=B 2=D 3=F -1=F -2=D -3=B

Positional perl expression replacement string

To use a perl expression as a positional replacement string simply prepend the perl expression with number and space:

  parallel echo '{=2 s:\.[^.]+$::;s:\.[^.]+$::; =} {1}' ::: bar ::: foo.tar.gz

Output:

  foo bar

If shorthand defined using --rpl starts with { it can be used as a positional replacement string, too:

  parallel --rpl '{..} s:\.[^.]+$::;s:\.[^.]+$::;' echo '{2..} {1}' ::: bar ::: foo.tar.gz

Output: Same as above.

Input from columns

The columns in a file can be bound to positional replacement strings using --colsep. Here the columns are separated by TAB (\t):

  parallel --colsep '\t' echo 1={1} 2={2} :::: tsv-file.tsv

Output (the order may be different):

  1=f1 2=f2
  1=A 2=B
  1=C 2=D

Header defined replacement strings

With --header GNU parallel will use the first value of the input source as the name of the replacement string. Only the non-modified version {} is supported:

  parallel --header : echo f1={f1} f2={f2} ::: f1 A B ::: f2 C D

Output (the order may be different):

  f1=A f2=C
  f1=A f2=D
  f1=B f2=C
  f1=B f2=D

It is useful with --colsep for processing files with TAB separated values:

  parallel --header : --colsep '\t' echo f1={f1} f2={f2} :::: tsv-file.tsv

Output (the order may be different):

  f1=A f2=B
  f1=C f2=D

More pre-defined replacement strings

--plus adds the replacement strings {+/} {+.} {+..} {+...} {..} {...} {/..} {/...} {##}. The idea being that {+foo} matches the opposite of {foo} and {} = {+/}/{/} = {.}.{+.} = {+/}/{/.}.{+.} = {..}.{+..} = {+/}/{/..}.{+..} = {...}.{+...} = {+/}/{/...}.{+...}.

  parallel --plus echo {} ::: dir/sub/file.ext1.ext2.ext3
  parallel --plus echo {+/}/{/} ::: dir/sub/file.ext1.ext2.ext3
  parallel --plus echo {.}.{+.} ::: dir/sub/file.ext1.ext2.ext3
  parallel --plus echo {+/}/{/.}.{+.} ::: dir/sub/file.ext1.ext2.ext3
  parallel --plus echo {..}.{+..} ::: dir/sub/file.ext1.ext2.ext3
  parallel --plus echo {+/}/{/..}.{+..} ::: dir/sub/file.ext1.ext2.ext3
  parallel --plus echo {...}.{+...} ::: dir/sub/file.ext1.ext2.ext3
  parallel --plus echo {+/}/{/...}.{+...} ::: dir/sub/file.ext1.ext2.ext3

Output:

  dir/sub/file.ext1.ext2.ext3

{##} is simply the number of jobs:

  parallel --plus echo Job {#} of {##} ::: {1..5}

Output:

  Job 1 of 5
  Job 2 of 5
  Job 3 of 5
  Job 4 of 5
  Job 5 of 5

More than one argument

With --xargs GNU parallel will fit as many arguments as possible on a single line:

  cat num30000 | parallel --xargs echo | wc -l

Output (if you run this under Bash on GNU/Linux):

The 30000 arguments fitted on 2 lines.

The maximal length of a single line can be set with -s. With a maximal line length of 10000 chars 17 commands will be run:

  cat num30000 | parallel --xargs -s 10000 echo | wc -l

Output:

For better parallelism GNU parallel can distribute the arguments between all the parallel jobs when end of file is met.

Below GNU parallel reads the last argument when generating the second job. When GNU parallel reads the last argument, it spreads all the arguments for the second job over 4 jobs instead, as 4 parallel jobs are requested.

The first job will be the same as the --xargs example above, but the second job will be split into 4 evenly sized jobs, resulting in a total of 5 jobs:

  cat num30000 | parallel --jobs 4 -m echo | wc -l

Output (if you run this under Bash on GNU/Linux):

This is even more visible when running 4 jobs with 10 arguments. The 10 arguments are being spread over 4 jobs:

  parallel --jobs 4 -m echo ::: 1 2 3 4 5 6 7 8 9 10

Output:

A replacement string can be part of a word. -m will not repeat the context:

  parallel --jobs 4 -m echo pre-{}-post ::: A B C D E F G

Output (the order may be different):

  pre-A B-post
  pre-C D-post
  pre-E F-post
  pre-G-post

To repeat the context use -X which otherwise works like -m:

  parallel --jobs 4 -X echo pre-{}-post ::: A B C D E F G

Output (the order may be different):

  pre-A-post pre-B-post
  pre-C-post pre-D-post
  pre-E-post pre-F-post
  pre-G-post

To limit the number of arguments use -N:

  parallel -N3 echo ::: A B C D E F G H

Output (the order may be different):

  A B C
  D E F
  G H

-N also sets the positional replacement strings:

  parallel -N3 echo 1={1} 2={2} 3={3} ::: A B C D E F G H

Output (the order may be different):

  1=A 2=B 3=C
  1=D 2=E 3=F
  1=G 2=H 3=

-N0 reads 1 argument but inserts none:

  parallel -N0 echo foo ::: 1 2 3

Output:

  foo
  foo
  foo

Quoting

Command lines that contain special characters may need to be protected from the shell.

The perl program print "@ARGV\n" basically works like echo.

  perl -e 'print "@ARGV\n"' A

Output:

To run that in parallel the command needs to be quoted:

  parallel perl -e 'print "@ARGV\n"' ::: This wont work

Output:

  [Nothing]

To quote the command use -q:

  parallel -q perl -e 'print "@ARGV\n"' ::: This works

Output (the order may be different):

  This
  works

Or you can quote the critical part using \':

  parallel perl -e \''print "@ARGV\n"'\' ::: This works, too

Output (the order may be different):

  This
  works,
  too

GNU parallel can also \-quote full lines. Simply run this:

  parallel --shellquote
  parallel: Warning: Input is read from the terminal. Only experts do this on purpose. Press CTRL-D to exit.
  perl -e 'print "@ARGV\n"'
  [CTRL-D]

Output:

  perl\ -e\ \'print\ \"@ARGV\\n\"\'

This can then be used as the command:

  parallel perl\ -e\ \'print\ \"@ARGV\\n\"\' ::: This also works

Output (the order may be different):

  This
  also
  works

Trimming space

Space can be trimmed on the arguments using --trim:

  parallel --trim r echo pre-{}-post ::: ' A '

Output:

  pre- A-post

To trim on the left side:

  parallel --trim l echo pre-{}-post ::: ' A '

Output:

  pre-A -post

To trim on the both sides:

  parallel --trim lr echo pre-{}-post ::: ' A '

Output:

  pre-A-post

Controlling the output

The output can prefixed with the argument:

  parallel --tag echo foo-{} ::: A B C

Output (the order may be different):

  A       foo-A
  B       foo-B
  C       foo-C

To prefix it with another string use --tagstring:

  parallel --tagstring {}-bar echo foo-{} ::: A B C

Output (the order may be different):

  A-bar   foo-A
  B-bar   foo-B
  C-bar   foo-C

To see what commands will be run without running them use --dryrun:

  parallel --dryrun echo {} ::: A B C

Output (the order may be different):

  echo A
  echo B
  echo C

To print the command before running them use --verbose:

  parallel --verbose echo {} ::: A B C

Output (the order may be different):

  echo A
  echo B
  A
  echo C
  B
  C

GNU parallel will postpone the output until the command completes:

  parallel -j2 'printf "%s-start\n%s" {} {};sleep {};printf "%s\n" -middle;echo {}-end' ::: 4 2 1

Output:

  2-start
  2-middle
  2-end
  1-start
  1-middle
  1-end
  4-start
  4-middle
  4-end

To get the output immediately use --ungroup:

  parallel -j2 --ungroup 'printf "%s-start\n%s" {} {};sleep {};printf "%s\n" -middle;echo {}-end' ::: 4 2 1

Output:

  4-start
  42-start
  2-middle
  2-end
  1-start
  1-middle
  1-end
  -middle
  4-end

--ungroup is fast, but can cause half a line from one job to be mixed with half a line of another job. That has happend in the second line, where the line '4-middle' is mixed with '2-start'.

To avoid this use --linebuffer:

  parallel -j2 --linebuffer 'printf "%s-start\n%s" {} {};sleep {};printf "%s\n" -middle;echo {}-end' ::: 4 2 1

Output:

  4-start
  2-start
  2-middle
  2-end
  1-start
  1-middle
  1-end
  4-middle
  4-end

To force the output in the same order as the arguments use --keep-order/-k:

  parallel -j2 -k 'printf "%s-start\n%s" {} {};sleep {};printf "%s\n" -middle;echo {}-end' ::: 4 2 1

Output:

  4-start
  4-middle
  4-end
  2-start
  2-middle
  2-end
  1-start
  1-middle
  1-end

Saving output into files

GNU parallel can save the output of each job into files:

  parallel --files echo ::: A B C

Output will be similar to this:

  /tmp/pAh6uWuQCg.par
  /tmp/opjhZCzAX4.par
  /tmp/W0AT_Rph2o.par

By default GNU parallel will cache the output in files in /tmp. This can be changed by setting $TMPDIR or --tmpdir:

  parallel --tmpdir /var/tmp --files echo ::: A B C

Output will be similar to this:

  /var/tmp/N_vk7phQRc.par
  /var/tmp/7zA4Ccf3wZ.par
  /var/tmp/LIuKgF_2LP.par

Or:

  TMPDIR=/var/tmp parallel --files echo ::: A B C

Output: Same as above.

The output files can be saved in a structured way using --results:

  parallel --results outdir echo ::: A B C

Output:

  A
  B
  C

These files were also generated containing the standard output (stdout), standard error (stderr), and the sequence number (seq):

  outdir/1/A/seq
  outdir/1/A/stderr
  outdir/1/A/stdout
  outdir/1/B/seq
  outdir/1/B/stderr
  outdir/1/B/stdout
  outdir/1/C/seq
  outdir/1/C/stderr
  outdir/1/C/stdout

--header : will take the first value as name and use that in the directory structure. This is useful if you are using multiple input sources:

  parallel --header : --results outdir echo ::: f1 A B ::: f2 C D

Generated files:

  outdir/f1/A/f2/C/seq
  outdir/f1/A/f2/C/stderr
  outdir/f1/A/f2/C/stdout
  outdir/f1/A/f2/D/seq
  outdir/f1/A/f2/D/stderr
  outdir/f1/A/f2/D/stdout
  outdir/f1/B/f2/C/seq
  outdir/f1/B/f2/C/stderr
  outdir/f1/B/f2/C/stdout
  outdir/f1/B/f2/D/seq
  outdir/f1/B/f2/D/stderr
  outdir/f1/B/f2/D/stdout

The directories are named after the variables and their values.

Controlling the execution

Number of simultaneous jobs

The number of concurrent jobs is given with --jobs/-j:

  /usr/bin/time parallel -N0 -j64 sleep 1 :::: num128

With 64 jobs in parallel the 128 sleeps will take 2-8 seconds to run - depending on how fast your machine is.

By default --jobs is the same as the number of CPU cores. So this:

  /usr/bin/time parallel -N0 sleep 1 :::: num128

should take twice the time of running 2 jobs per CPU core:

  /usr/bin/time parallel -N0 --jobs 200% sleep 1 :::: num128

--jobs 0 will run as many jobs in parallel as possible:

  /usr/bin/time parallel -N0 --jobs 0 sleep 1 :::: num128

which should take 1-7 seconds depending on how fast your machine is.

--jobs can read from a file which is re-read when a job finishes:

  echo 50% > my_jobs
  /usr/bin/time parallel -N0 --jobs my_jobs sleep 1 :::: num128 &
  sleep 1
  echo 0 > my_jobs
  wait

The first second only 50% of the CPU cores will run a job. Then 0 is put into my_jobs and then the rest of the jobs will be started in parallel.

Instead of basing the percentage on the number of CPU cores GNU parallel can base it on the number of CPUs:

  parallel --use-cpus-instead-of-cores -N0 sleep 1 :::: num8

Shuffle job order

If you have many jobs (e.g. by multiple combinations of input sources), it can be handy to shuffle the jobs, so you get different values run. Use --shuf for that:

  parallel --shuf echo ::: 1 2 3 ::: a b c ::: A B C

Output:

  All combinations but different order for each run.

Interactivity

GNU parallel can ask the user if a command should be run using --interactive:

  parallel --interactive echo ::: 1 2 3

Output:

  echo 1 ?...y
  echo 2 ?...n
  1
  echo 3 ?...y
  3

GNU parallel can be used to put arguments on the command line for an interactive command such as emacs to edit one file at a time:

  parallel --tty emacs ::: 1 2 3

Or give multiple argument in one go to open multiple files:

  parallel -X --tty vi ::: 1 2 3

A terminal for every job

Using --tmux GNU parallel can start a terminal for every job run:

  seq 10 20 | parallel --tmux 'echo start {}; sleep {}; echo done {}'

This will tell you to run something similar to:

  tmux -S /tmp/tmsrPrO0 attach

Using normal tmux keystrokes (CTRL-b n or CTRL-b p) you can cycle between windows of the running jobs. When a job is finished it will pause for 10 seconds before closing the window.

Timing

Some jobs do heavy I/O when they start. To avoid a thundering herd GNU parallel can delay starting new jobs. --delay X will make sure there is at least X seconds between each start:

  parallel --delay 2.5 echo Starting {}\;date ::: 1 2 3

Output:

  Starting 1
  Thu Aug 15 16:24:33 CEST 2013
  Starting 2
  Thu Aug 15 16:24:35 CEST 2013
  Starting 3
  Thu Aug 15 16:24:38 CEST 2013

If jobs taking more than a certain amount of time are known to fail, they can be stopped with --timeout. The accuracy of --timeout is 2 seconds:

  parallel --timeout 4.1 sleep {}\; echo {} ::: 2 4 6 8

Output:

  2
  4

GNU parallel can compute the median runtime for jobs and kill those that take more than 200% of the median runtime:

  parallel --timeout 200% sleep {}\; echo {} ::: 2.1 2.2 3 7 2.3

Output:

Progress information

Based on the runtime of completed jobs GNU parallel can estimate the total runtime:

  parallel --eta sleep ::: 1 3 2 2 1 3 3 2 1

Output:

  Computers / CPU cores / Max jobs to run
  1:local / 2 / 2

  Computer:jobs running/jobs completed/%of started jobs/Average seconds to complete
  ETA: 2s 0left 1.11avg  local:0/9/100%/1.1s

GNU parallel can give progress information with --progress:

  parallel --progress sleep ::: 1 3 2 2 1 3 3 2 1

Output:

  Computers / CPU cores / Max jobs to run
  1:local / 2 / 2

  Computer:jobs running/jobs completed/%of started jobs/Average seconds to complete
  local:0/9/100%/1.1s

A progress bar can be shown with --bar:

  parallel --bar sleep ::: 1 3 2 2 1 3 3 2 1

And a graphic bar can be shown with --bar and zenity:

  seq 1000 | parallel -j10 --bar '(echo -n {};sleep 0.1)' 2> >(zenity --progress --auto-kill)

A logfile of the jobs completed so far can be generated with --joblog:

  parallel --joblog /tmp/log exit  ::: 1 2 3 0 
  cat /tmp/log

Output:

  Seq     Host    Starttime       Runtime Send    Receive Exitval Signal  Command
  1       :       1376577364.974  0.008   0       0       1       0       exit 1
  2       :       1376577364.982  0.013   0       0       2       0       exit 2
  3       :       1376577364.990  0.013   0       0       3       0       exit 3
  4       :       1376577365.003  0.003   0       0       0       0       exit 0

The log contains the job sequence, which host the job was run on, the start time and run time, how much data was transferred, the exit value, the signal that killed the job, and finally the command being run.

With a joblog GNU parallel can be stopped and later pickup where it left off. It it important that the input of the completed jobs is unchanged.

  parallel --joblog /tmp/log exit  ::: 1 2 3 0 
  cat /tmp/log
  parallel --resume --joblog /tmp/log exit  ::: 1 2 3 0 0 0
  cat /tmp/log

Output:

  Seq     Host    Starttime       Runtime Send    Receive Exitval Signal  Command
  1       :       1376580069.544  0.008   0       0       1       0       exit 1
  2       :       1376580069.552  0.009   0       0       2       0       exit 2
  3       :       1376580069.560  0.012   0       0       3       0       exit 3
  4       :       1376580069.571  0.005   0       0       0       0       exit 0

  Seq     Host    Starttime       Runtime Send    Receive Exitval Signal  Command
  1       :       1376580069.544  0.008   0       0       1       0       exit 1
  2       :       1376580069.552  0.009   0       0       2       0       exit 2
  3       :       1376580069.560  0.012   0       0       3       0       exit 3
  4       :       1376580069.571  0.005   0       0       0       0       exit 0
  5       :       1376580070.028  0.009   0       0       0       0       exit 0
  6       :       1376580070.038  0.007   0       0       0       0       exit 0

Note how the start time of the last 2 jobs is clearly different from the second run.

With --resume-failed GNU parallel will re-run the jobs that failed:

  parallel --resume-failed --joblog /tmp/log exit  ::: 1 2 3 0 0 0
  cat /tmp/log

Output:

  Seq     Host    Starttime       Runtime Send    Receive Exitval Signal  Command
  1       :       1376580069.544  0.008   0       0       1       0       exit 1
  2       :       1376580069.552  0.009   0       0       2       0       exit 2
  3       :       1376580069.560  0.012   0       0       3       0       exit 3
  4       :       1376580069.571  0.005   0       0       0       0       exit 0
  5       :       1376580070.028  0.009   0       0       0       0       exit 0
  6       :       1376580070.038  0.007   0       0       0       0       exit 0
  1       :       1376580154.433  0.010   0       0       1       0       exit 1
  2       :       1376580154.444  0.022   0       0       2       0       exit 2
  3       :       1376580154.466  0.005   0       0       3       0       exit 3

Note how seq 1 2 3 have been repeated because they had exit value different from 0.

--retry-failed does almost the same as --resume-failed. Where --resume-failed reads the commands from the command line (and ignores the commands in the joblog), --retry-failed ignores the command line and reruns the commands mentioned in the joblog.

  parallel --resume-failed --joblog /tmp/log
  cat /tmp/log

Output:

  Seq     Host    Starttime       Runtime Send    Receive Exitval Signal  Command
  1       :       1376580069.544  0.008   0       0       1       0       exit 1
  2       :       1376580069.552  0.009   0       0       2       0       exit 2
  3       :       1376580069.560  0.012   0       0       3       0       exit 3
  4       :       1376580069.571  0.005   0       0       0       0       exit 0
  5       :       1376580070.028  0.009   0       0       0       0       exit 0
  6       :       1376580070.038  0.007   0       0       0       0       exit 0
  1       :       1376580154.433  0.010   0       0       1       0       exit 1
  2       :       1376580154.444  0.022   0       0       2       0       exit 2
  3       :       1376580154.466  0.005   0       0       3       0       exit 3
  1       :       1376580164.633  0.010   0       0       1       0       exit 1
  2       :       1376580164.644  0.022   0       0       2       0       exit 2
  3       :       1376580164.666  0.005   0       0       3       0       exit 3

Termination

For certain jobs there is no need to continue if one of the jobs fails and has an exit code different from 0. GNU parallel will stop spawning new jobs with --halt soon,fail=1:

  parallel -j2 --halt soon,fail=1 echo {}\; exit {} ::: 0 0 1 2 3

Output:

  0
  0
  1
  parallel: Starting no more jobs. Waiting for 2 jobs to finish. This job failed:
  echo 1; exit 1
  2
  parallel: Starting no more jobs. Waiting for 1 jobs to finish. This job failed:
  echo 2; exit 2

With --halt now,fail=1 the running jobs will be killed immediately:

  parallel -j2 --halt now,fail=1 echo {}\; exit {} ::: 0 0 1 2 3

Output:

  0
  0
  1
  parallel: This job failed:
  echo 1; exit 1

If --halt is given a percentage this percentage of the jobs must fail before GNU parallel stops spawning more jobs:

  parallel -j2 --halt soon,fail=20% echo {}\; exit {} ::: 0 1 2 3 4 5 6 7 8 9

Output:

  0
  1
  parallel: This job failed:
  echo 1; exit 1
  2
  parallel: This job failed:
  echo 2; exit 2
  parallel: Starting no more jobs. Waiting for 1 jobs to finish.
  3
  parallel: This job failed:
  echo 3; exit 3

If you are looking for success instead of failures, you can use success. This will finish as soon as the first job succeeds:

  parallel -j2 --halt now,success=1 echo {}\; exit {} ::: 1 2 3 0 4 5 6

Output:

  1
  2
  3
  0
  parallel: This job succeeded:
  echo 0; exit 0

GNU parallel can retry the command with --retries. This is useful if a command fails for unknown reasons now and then.

  parallel -k --retries 3 'echo tried {} >>/tmp/runs; echo completed {}; exit {}' ::: 1 2 0
  cat /tmp/runs

Output:

  completed 1
  completed 2
  completed 0

  tried 1
  tried 2
  tried 1
  tried 2
  tried 1
  tried 2
  tried 0

Note how job 1 and 2 were tried 3 times, but 0 was not retried because it had exit code 0.

Termination signals (advanced)

Using --termseq you can control which signals are sent when killing children. Normally children will be killed by sending them SIGTERM, waiting 200 ms, then another SIGTERM, waiting 100 ms, then another SIGTERM, waiting 50 ms, then a SIGKILL, finally waiting 25 ms before giving up. It looks like this:

  show_signals() {
    perl -e 'for(keys %SIG) { $SIG{$_} = eval "sub { print \"Got $_\\n\"; }";} while(1){sleep 1}' 
  }
  export -f show_signals
  echo | parallel --termseq TERM,200,TERM,100,TERM,50,KILL,25 -u --timeout 1 show_signals

Output:

  Got TERM
  Got TERM
  Got TERM

Or just:

  echo | parallel -u --timeout 1 show_signals

Output: Same as above.

You can change this to SIGINT, SIGTERM, SIGKILL:

  echo | parallel --termseq INT,200,TERM,100,KILL,25 -u --timeout 1 show_signals

Output:

  Got INT
  Got TERM

The SIGKILL does not show because it cannot be caught, and thus the child dies.

Limiting the resources

To avoid overloading systems GNU parallel can look at the system load before starting another job:

  parallel --load 100% echo load is less than {} job per cpu ::: 1

Output:

  [when then load is less than the number of cpu cores]
  load is less than 1 job per cpu

GNU parallel can also check if the system is swapping.

  parallel --noswap echo the system is not swapping ::: now

Output:

  [when then system is not swapping]
  the system is not swapping now

Some jobs need a lot of memory, and should only be started when there is enough memory free. Using --memfree GNU parallel can check if there is enough memory free. Additionally, GNU parallel will kill off the youngest job if the memory free falls below 50% of the size. The killed job will put back on the queue and retried later.

  parallel --memfree 1G echo will run if more than 1 GB is ::: free

GNU parallel can run the jobs with a nice value. This will work both locally and remotely.

  parallel --nice 17 echo this is being run with nice -n ::: 17

Output:

  this is being run with nice -n 17

Remote execution

GNU parallel can run jobs on remote servers. It uses ssh to communicate with the remote machines.

Sshlogin

The most basic sshlogin is -S host:

  parallel -S $SERVER1 echo running on ::: $SERVER1

Output:

  running on [$SERVER1]

To use a different username prepend the server with username@:

  parallel -S username@$SERVER1 echo running on ::: username@$SERVER1

Output:

  running on [username@$SERVER1]

The special sshlogin : is the local machine:

  parallel -S : echo running on ::: the_local_machine

Output:

  running on the_local_machine

If ssh is not in $PATH it can be prepended to $SERVER1:

  parallel -S '/usr/bin/ssh '$SERVER1 echo custom ::: ssh

Output:

  custom ssh

The ssh command can also be given using --ssh:

  parallel --ssh /usr/bin/ssh -S $SERVER1 echo custom ::: ssh

or by setting $PARALLEL_SSH:

  export PARALLEL_SSH=/usr/bin/ssh
  parallel -S $SERVER1 echo custom ::: ssh

Several servers can be given using multiple -S:

  parallel -S $SERVER1 -S $SERVER2 echo ::: running on more hosts

Output (the order may be different):

  running
  on
  more
  hosts

Or they can be separated by ,:

  parallel -S $SERVER1,$SERVER2 echo ::: running on more hosts

Output: Same as above.

Or newline:

  # This gives a \n between $SERVER1 and $SERVER2
  SERVERS="`echo $SERVER1; echo $SERVER2`"
  parallel -S "$SERVERS" echo ::: running on more hosts

They can also be read from a file (replace user@ with the user on $SERVER2):

  echo $SERVER1 > nodefile
  # Force 4 cores, special ssh-command, username
  echo 4//usr/bin/ssh user@$SERVER2 >> nodefile
  parallel --sshloginfile nodefile echo ::: running on more hosts

Output: Same as above.

Every time a job finished, the --sshloginfile will be re-read, so it is possible to both add and remove hosts while running.

The special --sshloginfile .. reads from ~/.parallel/sshloginfile.

To force GNU parallel to treat a server having a given number of CPU cores prepend the number of core followed by / to the sshlogin:

  parallel -S 4/$SERVER1 echo force {} cpus on server ::: 4

Output:

  force 4 cpus on server

Servers can be put into groups by prepending @groupname to the server and the group can then be selected by appending @groupname to the argument if using --hostgroup:

  parallel --hostgroup -S @grp1/$SERVER1 -S @grp2/$SERVER2 echo {} ::: \
    run_on_grp1@grp1 run_on_grp2@grp2

Output:

  run_on_grp1
  run_on_grp2

A host can be in multiple groups by separating the groups with +, and you can force GNU parallel to limit the groups on which the command can be run with -S @groupname:

  parallel -S @grp1 -S @grp1+grp2/$SERVER1 -S @grp2/SERVER2 echo {} ::: \
    run_on_grp1 also_grp1

Output:

  run_on_grp1
  also_grp1

Transferring files

GNU parallel can transfer the files to be processed to the remote host. It does that using rsync.

  echo This is input_file > input_file
  parallel -S $SERVER1 --transferfile {} cat ::: input_file

Output:

  This is input_file

If the files are processed into another file, the resulting file can be transferred back:

  echo This is input_file > input_file
  parallel -S $SERVER1 --transferfile {} --return {}.out cat {} ">"{}.out ::: input_file 
  cat input_file.out

Output: Same as above.

To remove the input and output file on the remote server use --cleanup:

  echo This is input_file > input_file
  parallel -S $SERVER1 --transferfile {} --return {}.out --cleanup cat {} ">"{}.out ::: input_file 
  cat input_file.out

Output: Same as above.

There is a shorthand for --transferfile {} --return --cleanup called --trc:

  echo This is input_file > input_file
  parallel -S $SERVER1 --trc {}.out cat {} ">"{}.out ::: input_file 
  cat input_file.out

Output: Same as above.

Some jobs need a common database for all jobs. GNU parallel can transfer that using --basefile which will transfer the file before the first job:

  echo common data > common_file
  parallel --basefile common_file -S $SERVER1 cat common_file\; echo {} ::: foo

Output:

  common data
  foo

To remove it from the remote host after the last job use --cleanup.

Working dir

The default working dir on the remote machines is the login dir. This can be changed with --workdir mydir.

Files transferred using --transferfile and --return will be relative to mydir on remote computers, and the command will be executed in the dir mydir.

The special mydir value ... will create working dirs under ~/.parallel/tmp on the remote computers. If --cleanup is given these dirs will be removed.

The special mydir value . uses the current working dir. If the current working dir is beneath your home dir, the value . is treated as the relative path to your home dir. This means that if your home dir is different on remote computers (e.g. if your login is different) the relative path will still be relative to your home dir.

  parallel -S $SERVER1 pwd ::: ""
  parallel --workdir . -S $SERVER1 pwd ::: ""
  parallel --workdir ... -S $SERVER1 pwd ::: ""

Output:

  [the login dir on $SERVER1]
  [current dir relative on $SERVER1]
  [a dir in ~/.parallel/tmp/...]

Avoid overloading sshd

If many jobs are started on the same server, sshd can be overloaded. GNU parallel can insert a delay between each job run on the same server:

  parallel -S $SERVER1 --sshdelay 0.2 echo ::: 1 2 3

Output (the order may be different):

  1
  2
  3

sshd will be less overloaded if using --controlmaster, which will multiplex ssh connections:

  parallel --controlmaster -S $SERVER1 echo ::: 1 2 3

Output: Same as above.

Ignore hosts that are down

In clusters with many hosts a few of them are often down. GNU parallel can ignore those hosts. In this case the host 173.194.32.46 is down:

  parallel --filter-hosts -S 173.194.32.46,$SERVER1 echo ::: bar

Output:

bar

Running the same commands on all hosts

GNU parallel can run the same command on all the hosts:

  parallel --onall -S $SERVER1,$SERVER2 echo ::: foo bar

Output (the order may be different):

  foo
  bar
  foo
  bar

Often you will just want to run a single command on all hosts with out arguments. --nonall is a no argument --onall:

  parallel --nonall -S $SERVER1,$SERVER2 echo foo bar

Output:

  foo bar
  foo bar

When --tag is used with --nonall and --onall the --tagstring is the host:

  parallel --nonall --tag -S $SERVER1,$SERVER2 echo foo bar

Output (the order may be different):

  $SERVER1 foo bar
  $SERVER2 foo bar

--jobs sets the number of servers to log in to in parallel.

Transferring environment variables and functions

Using --env GNU parallel can transfer an environment variable to the remote system.

  MYVAR='foo bar'
  export MYVAR
  parallel --env MYVAR -S $SERVER1 echo '$MYVAR' ::: baz

Output:

  foo bar baz

This works for functions, too, if your shell is Bash:

  # This only works in Bash
  my_func() {
    echo in my_func $1
  }
  export -f my_func
  parallel --env my_func -S $SERVER1 my_func ::: baz

Output:

  in my_func baz

GNU parallel can copy all defined variables and functions to the remote system. It just needs to record which ones to ignore in ~/.parallel/ignored_vars. Do that by running this once:

  parallel --record-env
  cat ~/.parallel/ignored_vars

Output:

  [list of variables to ignore - including $PATH and $HOME]

Now all new variables and functions defined will be copied when using --env _:

  # The function is only copied if using Bash
  my_func2() {
    echo in my_func2 $VAR $1
  }
  export -f my_func2
  VAR=foo
  export VAR

  parallel --env _ -S $SERVER1 'echo $VAR; my_func2' ::: bar

Output:

  foo
  in my_func2 foo bar

Showing what is actually run

--verbose will show the command that would be run on the local machine. When a job is run on a remote machine, this is wrapped with ssh and possibly transferring files and environment variables, setting the workdir, and setting --nice value. -vv shows all of this.

  parallel -vv -S $SERVER1 echo ::: bar

Output:

  ssh lo -- exec perl -e \''@GNU_Parallel=("use","IPC::Open3;","use","MIME::Base64");
  eval"@GNU_Parallel";my$eval;$eval=decode_base64(join"",@ARGV);eval$eval;'\' 
  JEVOVnsiUEFSQUxMRUxfUElEIn09IjI3MzQiOyRFTlZ7IlBBUkFMTEVMX1NFUSJ9PSIx
  IjskYmFzaGZ1bmMgPSAiIjtAQVJHVj0iZWNobyBiYXIiOyRzaGVsbD0iJEVOVntTSEVM
  TH0iOyR0bXBkaXI9Ii90bXAiOyRuaWNlPTA7ZG97JEVOVntQQVJBTExFTF9UTVB9PSR0
  bXBkaXIuIi9wYXIiLmpvaW4iIixtYXB7KDAuLjksImEiLi4ieiIsIkEiLi4iWiIpW3Jh
  bmQoNjIpXX0oMS4uNSk7fXdoaWxlKC1lJEVOVntQQVJBTExFTF9UTVB9KTskU0lHe0NI
  TER9PXN1YnskZG9uZT0xO307JHBpZD1mb3JrO3VubGVzcygkcGlkKXtzZXRwZ3JwO2V2
  YWx7c2V0cHJpb3JpdHkoMCwwLCRuaWNlKX07ZXhlYyRzaGVsbCwiLWMiLCgkYmFzaGZ1
  bmMuIkBBUkdWIik7ZGllImV4ZWM6JCFcbiI7fWRveyRzPSRzPDE/MC4wMDErJHMqMS4w
  MzokcztzZWxlY3QodW5kZWYsdW5kZWYsdW5kZWYsJHMpO311bnRpbCgkZG9uZXx8Z2V0
  cHBpZD09MSk7a2lsbChTSUdIVVAsLSR7cGlkfSl1bmxlc3MkZG9uZTt3YWl0O2V4aXQo
  JD8mMTI3PzEyOCsoJD8mMTI3KToxKyQ/Pj44KQ==;
  bar

When the command gets more complex, the output is so hard to read, that it is only useful for debugging:

  my_func3() {
    echo in my_func $1 > $1.out
  }
  export -f my_func3
  parallel -vv --workdir ... --nice 17 --env _ --trc {}.out -S $SERVER1 my_func3 {} ::: abc-file

Output will be similar to:

  ( ssh lo -- mkdir -p ./.parallel/tmp/hk-3492-1;rsync --protocol 30
  -rlDzR -essh ./abc-file lo:./.parallel/tmp/hk-3492-1 );ssh lo --
  exec perl -e \''@GNU_Parallel=("use","IPC::Open3;","use","MIME::Base64");
  eval"@GNU_Parallel";my$eval;$eval=decode_base64(join"",@ARGV);eval$eval;'\'
  c3lzdGVtKCJta2RpciIsIi1wIiwiLS0iLCIucGFyYWxsZWwvdG1wL2hrLTM0OTItMSIp
  OyBjaGRpciAiLnBhcmFsbGVsL3RtcC9oay0zNDkyLTEiIHx8cHJpbnQoU1RERVJSICJw
  YXJhbGxlbDogQ2Fubm90IGNoZGlyIHRvIC5wYXJhbGxlbC90bXAvaGstMzQ5Mi0xXG4i
  KSAmJiBleGl0IDI1NTskRU5WeyJHUEdfQUdFTlRfSU5GTyJ9PSIvdG1wL2dwZy10WjVI
  U0QvUy5ncGctYWdlbnQ6MjM5NzoxIjskRU5WeyJQQVJBTExFTF9TRVEifT0iMSI7JEVO
  VnsiU1FMSVRFVEJMIn09InNxbGl0ZTM6Ly8vJTJGdG1wJTJGcGFyYWxsZWwuZGIyL3Bh
  cnNxbDIiOyRFTlZ7IlBBUkFMTEVMX1BJRCJ9PSIzNDkyIjskRU5WeyJTUUxJVEUifT0i
  c3FsaXRlMzovLy8lMkZ0bXAlMkZwYXJhbGxlbC5kYjIiOyRFTlZ7IlBBUkFMTEVMX1BJ
  RCJ9PSIzNDkyIjskRU5WeyJQQVJBTExFTF9TRVEifT0iMSI7QGJhc2hfZnVuY3Rpb25z
  PXF3KG15X2Z1bmMzKTsgaWYoJEVOVnsiU0hFTEwifT1+L2NzaC8pIHsgcHJpbnQgU1RE
  RVJSICJDU0gvVENTSCBETyBOT1QgU1VQUE9SVCBuZXdsaW5lcyBJTiBWQVJJQUJMRVMv
  RlVOQ1RJT05TLiBVbnNldCBAYmFzaF9mdW5jdGlvbnNcbiI7IGV4ZWMgImZhbHNlIjsg
  fSAKJGJhc2hmdW5jID0gIm15X2Z1bmMzKCkgeyAgZWNobyBpbiBteV9mdW5jIFwkMSA+
  IFwkMS5vdXQKfTtleHBvcnQgLWYgbXlfZnVuYzMgPi9kZXYvbnVsbDsiO0BBUkdWPSJt
  eV9mdW5jMyBhYmMtZmlsZSI7JHNoZWxsPSIkRU5We1NIRUxM
  fSI7JHRtcGRpcj0iL3RtcCI7JG5pY2U9MTc7ZG97JEVOVntQQVJBTExFTF9UTVB9PSR0
  bXBkaXIuIi9wYXIiLmpvaW4iIixtYXB7KDAuLjksImEiLi4ieiIsIkEiLi4iWiIpW3Jh
  bmQoNjIpXX0oMS4uNSk7fXdoaWxlKC1lJEVOVntQQVJBTExFTF9UTVB9KTskU0lHe0NI
  TER9PXN1YnskZG9uZT0xO307JHBpZD1mb3JrO3VubGVzcygkcGlkKXtzZXRwZ3JwO2V2
  YWx7c2V0cHJpb3JpdHkoMCwwLCRuaWNlKX07ZXhlYyRzaGVsbCwiLWMiLCgkYmFzaGZ1
  bmMuIkBBUkdWIik7ZGllImV4ZWM6JCFcbiI7fWRveyRzPSRzPDE/MC4wMDErJHMqMS4w
  MzokcztzZWxlY3QodW5kZWYsdW5kZWYsdW5kZWYsJHMpO311bnRpbCgkZG9uZXx8Z2V0
  cHBpZD09MSk7a2lsbChTSUdIVVAsLSR7cGlkfSl1bmxlc3MkZG9uZTt3YWl0O2V4aXQo
  JD8mMTI3PzEyOCsoJD8mMTI3KToxKyQ/Pj44KQ==;_EXIT_status=$?;
  mkdir -p ./.; rsync --protocol 30 --rsync-path=cd\
  ./.parallel/tmp/hk-3492-1/./.\;\ rsync -rlDzR -essh
  lo:./abc-file.out ./.;ssh lo -- \(rm\ -f\
  ./.parallel/tmp/hk-3492-1/abc-file\;\ sh\ -c\ \'rmdir\
  ./.parallel/tmp/hk-3492-1/\ ./.parallel/tmp/\ ./.parallel/\
  2\>/dev/null\'\;rm\ -rf\ ./.parallel/tmp/hk-3492-1\;\);ssh lo --
  \(rm\ -f\ ./.parallel/tmp/hk-3492-1/abc-file.out\;\ sh\ -c\ \'rmdir\
  ./.parallel/tmp/hk-3492-1/\ ./.parallel/tmp/\ ./.parallel/\
  2\>/dev/null\'\;rm\ -rf\ ./.parallel/tmp/hk-3492-1\;\);ssh lo -- rm
  -rf .parallel/tmp/hk-3492-1; exit $_EXIT_status;

Saving to an SQL base (advanced)

GNU parallel can save into an SQL base. Point GNU parallel to a table and it will put the joblog there together with the variables and the outout each in their own column.

GNU parallel uses a DBURL to address the table. A DBURL has this format:

  vendor://[[user][:password]@][host][:port]/[database[/table]

Example:

  mysql://scott:tiger@my.example.com/mydatabase/mytable
  postgresql://scott:tiger@pg.example.com/mydatabase/mytable
  sqlite3:///%2Ftmp%2Fmydatabase/mytable

To refer to /tmp/mydatabase with sqlite you need to encode the / as %2F.

Run a job using sqlite on mytable in /tmp/mydatabase:

  DBURL=sqlite3:///%2Ftmp%2Fmydatabase
  DBURLTABLE=$DBURL/mytable
  parallel --sqlandworker $DBURLTABLE echo ::: foo bar ::: baz quuz

To see the result:

  sql $DBURL 'SELECT * FROM mytable ORDER BY Seq;'

Output will be similar to:

  Seq|Host|Starttime|JobRuntime|Send|Receive|Exitval|_Signal|Command|V1|V2|Stdout|Stderr
  1|:|1451619638.903|0.806||8|0|0|echo foo baz|foo|baz|foo baz
  |
  2|:|1451619639.265|1.54||9|0|0|echo foo quuz|foo|quuz|foo quuz
  |
  3|:|1451619640.378|1.43||8|0|0|echo bar baz|bar|baz|bar baz
  |
  4|:|1451619641.473|0.958||9|0|0|echo bar quuz|bar|quuz|bar quuz
  |

The first columns are well known from --joblog. V1 and V2 are data from the input sources. Stdout and Stderr are standard output and standard error, respectively.

Using multiple workers

Using an SQL base as storage costs a lot of performance.

One of the situations where it makes sense is if you have multiple workers.

You can then have a single master machine that submits jobs to the SQL base (but does not do any of the work):

  parallel --sql $DBURLTABLE echo ::: foo bar ::: baz quuz

On the worker machines you run exactly the same command except you replace --sql with --sqlworker.

  parallel --sqlworker $DBURLTABLE echo ::: foo bar ::: baz quuz

To run a master and a worker on the same machine use --sqlandworker as shown earlier.

--pipe

The --pipe functionality puts GNU parallel in a different mode: Instead of treating the data on stdin (standard input) as arguments for a command to run, the data will be sent to stdin (standard input) of the command.

The typical situation is:

  command_A | command_B | command_C

where command_B is slow, and you want to speed up command_B.

Chunk size

By default GNU parallel will start an instance of command_B, read a chunk of 1 MB, and pass that to the instance. Then start another instance, read another chunk, and pass that to the second instance.

  cat num1000000 | parallel --pipe wc

Output (the order may be different):

  165668  165668 1048571
  149797  149797 1048579
  149796  149796 1048572
  149797  149797 1048579
  149797  149797 1048579
  149796  149796 1048572
   85349   85349  597444

The size of the chunk is not exactly 1 MB because GNU parallel only passes full lines - never half a line, thus the blocksize is only average 1 MB. You can change the block size to 2 MB with --block:

  cat num1000000 | parallel --pipe --block 2M wc

Output (the order may be different):

  315465  315465 2097150
  299593  299593 2097151
  299593  299593 2097151
   85349   85349  597444

GNU parallel treats each line as a record. If the order of record is unimportant (e.g. you need all lines processed, but you do not care which is processed first), then you can use --round-robin. Without --round-robin GNU parallel will start a command per block; with --round-robin only the requested number of jobs will be started (--jobs). The records will then be distributed between the running jobs:

  cat num1000000 | parallel --pipe -j4 --round-robin wc

Output will be similar to:

  149797  149797 1048579
  299593  299593 2097151
  315465  315465 2097150
  235145  235145 1646016

One of the 4 instances got a single record, 2 instances got 2 full records each, and one instance got 1 full and 1 partial record.

Records

GNU parallel sees the input as records. The default record is a single line.

Using -N140000 GNU parallel will read 140000 records at a time:

  cat num1000000 | parallel --pipe -N140000 wc

Output (the order may be different):

  140000  140000  868895
  140000  140000  980000
  140000  140000  980000
  140000  140000  980000
  140000  140000  980000
  140000  140000  980000
  140000  140000  980000
   20000   20000  140001

Notice that the last job could not get the full 140000 lines, but only 20000 lines.

If a record is 75 lines -L can be used:

  cat num1000000 | parallel --pipe -L75 wc

Output (the order may be different):

  165600  165600 1048095
  149850  149850 1048950
  149775  149775 1048425
  149775  149775 1048425
  149850  149850 1048950
  149775  149775 1048425
   85350   85350  597450
      25      25     176

Notice GNU parallel still reads a block of around 1 MB; but instead of passing full lines to wc it passes full 75 lines at a time. This of course does not hold for the last job (which in this case got 25 lines).

Record separators

GNU parallel uses separators to determine where two records split.

--recstart gives the string that starts a record; --recend gives the string that ends a record. The default is --recend '\n' (newline).

If both --recend and --recstart are given, then the record will only split if the recend string is immediately followed by the recstart string.

Here the --recend is set to ', ':

  echo /foo, bar/, /baz, qux/, | parallel -kN1 --recend ', ' --pipe echo JOB{#}\;cat\;echo END

Output:

  JOB1
  /foo, END
  JOB2
  bar/, END
  JOB3
  /baz, END
  JOB4
  qux/,
  END

Here the --recstart is set to /:

  echo /foo, bar/, /baz, qux/, | parallel -kN1 --recstart / --pipe echo JOB{#}\;cat\;echo END

Output:

  JOB1
  /foo, barEND
  JOB2
  /, END
  JOB3
  /baz, quxEND
  JOB4
  /,
  END

Here both --recend and --recstart are set:

  echo /foo, bar/, /baz, qux/, | parallel -kN1 --recend ', ' --recstart / --pipe echo JOB{#}\;cat\;echo END

Output:

  JOB1
  /foo, bar/, END
  JOB2
  /baz, qux/,
  END

Note the difference between setting one string and setting both strings.

With --regexp the --recend and --recstart will be treated as a regular expression:

  echo foo,bar,_baz,__qux, | parallel -kN1 --regexp --recend ,_+ --pipe echo JOB{#}\;cat\;echo END

Output:

  JOB1
  foo,bar,_END
  JOB2
  baz,__END
  JOB3
  qux,
  END

GNU parallel can remove the record separators with --remove-rec-sep/--rrs:

  echo foo,bar,_baz,__qux, | parallel -kN1 --rrs --regexp --recend ,_+ --pipe echo JOB{#}\;cat\;echo END

Output:

  JOB1
  foo,barEND
  JOB2
  bazEND
  JOB3
  qux,
  END

If the input data has a header, the header can be repeated for each job by matching the header with --header. If headers start with % you can do this:

  cat num_%header | parallel --header '(%.*\n)*' --pipe -N3 echo JOB{#}\;cat

Output (the order may be different):

  JOB1
  %head1
  %head2
  1
  2
  3
  JOB2
  %head1
  %head2
  4
  5
  6
  JOB3
  %head1
  %head2
  7
  8
  9
  JOB4
  %head1
  %head2
  10

If the header is 2 lines, --header 2 will work:

  cat num_%header | parallel --header 2 --pipe -N3 echo JOB{#}\;cat

Output: Same as above.

--pipepart

--pipe is not very efficient. It maxes out at around 500 MB/s. --pipepart can easily deliver 5 GB/s. But there are a few limitations. The input has to be a normal file (not a pipe) given by -a or :::: and -L/-l/-N do not work.

  parallel --pipepart -a num1000000 --block 3m wc

Output (the order may be different):

 444443  444444 3000002
 428572  428572 3000004
 126985  126984  888890

Shebang

Input data and parallel command in the same file

GNU parallel is often called as this:

  cat input_file | parallel command

With --shebang the input_file and parallel can be combined into the same script.

UNIX shell scripts start with a shebang line like this:

  #!/bin/bash

GNU parallel can do that, too. With --shebang the arguments can be listed in the file. The parallel command is the first line of the script:

  #!/usr/bin/parallel --shebang -r echo

  foo
  bar
  baz

Output (the order may be different):

  foo
  bar
  baz

Parallelizing existing scripts

GNU parallel is often called as this:

  cat input_file | parallel command
  parallel command ::: foo bar

If command is a script, parallel can be combined into a single file so this will run the script in parallel:

  cat input_file | command
  command foo bar

This perl script perl_echo works like echo:

  #!/usr/bin/perl

  print "@ARGV\n"

It can be called as this:

  parallel perl_echo ::: foo bar

By changing the #!-line it can be run in parallel:

  #!/usr/bin/parallel --shebang-wrap /usr/bin/perl

  print "@ARGV\n"

Thus this will work:

  perl_echo foo bar

Output (the order may be different):

  foo
  bar

This technique can be used for:

Perl:

  #!/usr/bin/parallel --shebang-wrap /usr/bin/perl
  
  print "Arguments @ARGV\n";

Python:

  #!/usr/bin/parallel --shebang-wrap /usr/bin/python
  
  import sys
  print 'Arguments', str(sys.argv)

Bash/sh/zsh/Korn shell:

  #!/usr/bin/parallel --shebang-wrap /bin/bash
  
  echo Arguments "$@"

csh:

  #!/usr/bin/parallel --shebang-wrap /bin/csh
  
  echo Arguments "$argv"

Tcl:

  #!/usr/bin/parallel --shebang-wrap /usr/bin/tclsh
  
  puts "Arguments $argv"

R:

  #!/usr/bin/parallel --shebang-wrap /usr/bin/Rscript --vanilla --slave
  
  args <- commandArgs(trailingOnly = TRUE)
  print(paste("Arguments ",args))

GNUplot:

  #!/usr/bin/parallel --shebang-wrap ARG={} /usr/bin/gnuplot
  
  print "Arguments ", system('echo $ARG')

Ruby:

  #!/usr/bin/parallel --shebang-wrap /usr/bin/ruby
  
  print "Arguments "
  puts ARGV

Octave:

  #!/usr/bin/parallel --shebang-wrap /usr/bin/octave
  
  printf ("Arguments");
  arg_list = argv ();
  for i = 1:nargin
    printf (" %s", arg_list{i});
  endfor
  printf ("\n");

Common LISP:

  #!/usr/bin/parallel --shebang-wrap /usr/bin/clisp
  
  (format t "~&~S~&" 'Arguments)
  (format t "~&~S~&" *args*)

PHP:

  #!/usr/bin/parallel --shebang-wrap /usr/bin/php
  <?php
  echo "Arguments";
  foreach(array_slice($argv,1) as $v)
  {
    echo " $v";
  }
  echo "\n";
  ?>

Node.js:

  #!/usr/bin/parallel --shebang-wrap /usr/bin/node

  var myArgs = process.argv.slice(2);
  console.log('Arguments ', myArgs);

LUA:

  #!/usr/bin/parallel --shebang-wrap /usr/bin/lua
  
  io.write "Arguments"
  for a = 1, #arg do
    io.write(" ")
    io.write(arg[a])
  end
  print("")

C#:

  #!/usr/bin/parallel --shebang-wrap ARGV={} /usr/bin/csharp
  
  var argv = Environment.GetEnvironmentVariable("ARGV");
  print("Arguments "+argv);

Semaphore

GNU parallel can work as a counting semaphore. This is slower and less efficient than its normal mode.

A counting semaphore is like a row of toilets. People needing a toilet can use any toilet, but if there are more people than toilets, they will have to wait for one of the toilets to be available.

An alias for parallel --semaphore is sem.

sem will follow a person to the toilets, wait until a toilet is available, leave the person in the toilet and exit.

sem --fg will follow a person to the toilets, wait until a toilet is available, stay with the person in the toilet and exit when the person exits.

sem --wait will wait for all persons to leave the toilets.

sem does not have a queue discipline, so the next person is chosen randomly.

-j sets the number of toilets.

Mutex

The default is to have only one toilet (this is called a mutex). The program is started in the background and sem exits immediately. Use --wait to wait for all sems to finish:

  sem 'sleep 1; echo The first finished' &&
    echo The first is now running in the background &&
    sem 'sleep 1; echo The second finished' &&
    echo The second is now running in the background
  sem --wait

Output:

  The first is now running in the background
  The first finished
  The second is now running in the background
  The second finished

The command can be run in the foreground with --fg, which will only exit when the command completes:

  sem --fg 'sleep 1; echo The first finished' &&
    echo The first finished running in the foreground &&
    sem --fg 'sleep 1; echo The second finished' &&
    echo The second finished running in the foreground
  sem --wait

The difference between this and just running the command, is that a mutex is set, so if other sems were running in the background only one would run at a time.

To tell the difference between which semaphore is used, use --semaphorename/--id. Run this in one terminal:

  sem --id my_id -u 'echo First started; sleep 10; echo The first finished'

and simultaneously this in another terminal:

  sem --id my_id -u 'echo Second started; sleep 10; echo The second finished'

Note how the second will only be started when the first has finished.

Counting semaphore

A mutex is like having a single toilet: When it is in use everyone else will have to wait. A counting semaphore is like having multiple toilets: Several people can use the toilets, but when they all are in use, everyone else will have to wait.

sem can emulate a counting semaphore. Use --jobs to set the number of toilets like this:

  sem --jobs 3 --id my_id -u 'echo First started; sleep 5; echo The first finished' &&
  sem --jobs 3 --id my_id -u 'echo Second started; sleep 6; echo The second finished' &&
  sem --jobs 3 --id my_id -u 'echo Third started; sleep 7; echo The third finished' &&
  sem --jobs 3 --id my_id -u 'echo Fourth started; sleep 8; echo The fourth finished' &&
  sem --wait --id my_id

Output:

  First started
  Second started
  Third started
  The first finished
  Fourth started
  The second finished
  The third finished
  The fourth finished

Timeout

With --semaphoretimeout you can force running the command anyway after a period (postive number) or give up (negative number):

  sem --id foo -u 'echo Slow started; sleep 5; echo Slow ended' &&
  sem --id foo --semaphoretimeout 1 'echo Force this running after 1 sec' &&
  sem --id foo --semaphoretimeout -2 'echo Give up after 1 sec'
  sem --id foo --wait

Output:

  Slow started
  parallel: Warning: Semaphore timed out. Stealing the semaphore.
  Force this running after 1 sec
  Slow ended
  parallel: Warning: Semaphore timed out. Exiting.

Note how the 'Give up' was not run.

Informational

GNU parallel has some options to give short information about the configuration.

--help will print a summary of the most important options:

  parallel --help

Output:

  Usage:
  parallel [options] [command [arguments]] < list_of_arguments
  parallel [options] [command [arguments]] (::: arguments|:::: argfile(s))...
  cat ... | parallel --pipe [options] [command [arguments]]
  
  -j n           Run n jobs in parallel
  -k             Keep same order
  -X             Multiple arguments with context replace
  --colsep regexp      Split input on regexp for positional replacements
  {} {.} {/} {/.} {#}  Replacement strings
  {3} {3.} {3/} {3/.}  Positional replacement strings
  
  -S sshlogin    Example: foo@server.example.com
  --slf ..       Use ~/.parallel/sshloginfile as the list of sshlogins
  --trc {}.bar   Shorthand for --transfer --return {}.bar --cleanup
  --onall        Run the given command with argument on all sshlogins
  --nonall       Run the given command with no arguments on all sshlogins
  
  --pipe         Split stdin (standard input) to multiple jobs.
  --recend str   Record end separator for --pipe.
  --recstart str Record start separator for --pipe.
  
  See 'man parallel' for details
  
  When using GNU Parallel for a publication please cite:
  
  O. Tange (2011): GNU Parallel - The Command-Line Power Tool,
  ;login: The USENIX Magazine, February 2011:42-47.

    When asking for help, always report the full output of this:

  parallel --version

Output:

  GNU parallel 20130822
  Copyright (C) 2007,2008,2009,2010,2011,2012,2013 Ole Tange and Free Software Foundation, Inc.
  License GPLv3+: GNU GPL version 3 or later <http://gnu.org/licenses/gpl.html>
  This is free software: you are free to change and redistribute it.
  GNU parallel comes with no warranty.
  
  Web site: http://www.gnu.org/software/parallel
  
  When using GNU Parallel for a publication please cite:
  
  O. Tange (2011): GNU Parallel - The Command-Line Power Tool, 
  ;login: The USENIX Magazine, February 2011:42-47.

In scripts --minversion can be used to ensure the user has at least this version:

  parallel --minversion 20130722 && echo Your version is at least 20130722.

Output:

  20130722
  Your version is at least 20130722.

If using GNU parallel for research the BibTeX citation can be generated using --bibtex:

  parallel --bibtex

Output:

  @article{Tange2011a,
   title = {GNU Parallel - The Command-Line Power Tool},
   author = {O. Tange},
   address = {Frederiksberg, Denmark},
   journal = {;login: The USENIX Magazine},
   month = {Feb},
   number = {1},
   volume = {36},
   url = {http://www.gnu.org/s/parallel},
   year = {2011},
   pages = {42-47}
  }

With --max-line-length-allowed GNU parallel will report the maximal size of the command line:

  parallel --max-line-length-allowed

Output (may vary on different systems):

--number-of-cpus and --number-of-cores run system specific code to determine the number of CPUs and CPU cores on the system. On unsupported platforms they will return 1:

  parallel --number-of-cpus 
  parallel --number-of-cores

Output (may vary on different systems):

  4
  64

Profiles

The defaults for GNU parallel can be changed systemwide by putting the command line options in /etc/parallel/config. They can be changed for a user by putting them in ~/.parallel/config.

Profiles work the same way, but have to be referred to with --profile:

  echo '--nice 17' > ~/.parallel/nicetimeout
  echo '--timeout 300%' >> ~/.parallel/nicetimeout
  parallel --profile nicetimeout echo ::: A B C

Output:

  A
  B
  C

Profiles can be combined:

  echo '-vv --dry-run' > ~/.parallel/dryverbose
  parallel --profile dryverbose --profile nicetimeout echo ::: A B C

Output:

  \nice -n17 /bin/bash -c echo\ A
  \nice -n17 /bin/bash -c echo\ B
  \nice -n17 /bin/bash -c echo\ C

Spread the word

I hope you have learned something from this tutorial.

If you like GNU parallel:

(Re-)walk through the tutorial if you have not done so in the past year (http://www.gnu.org/software/parallel/parallel_tutorial.html)
Give a demo at your local user group/team/colleagues
Post the intro videos and the tutorial on Reddit, Diaspora*, forums, blogs, Identi.ca, Google+, Twitter, Facebook, Linkedin, mailing lists
Request or write a review for your favourite blog or magazine (especially if you do something cool with GNU parallel)
Invite me for your next conference

If you use GNU parallel for research:

Please cite GNU parallel in you publications (use --bibtex)

If GNU parallel saves you money:

(Have your company) donate to FSF or become a member https://my.fsf.org/donate/