#!/usr/bin/perl -w

=head1 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.

=head1 Prerequisites

To run this tutorial you must have the following:

=over 9

=item parallel >= version 20130814

Install the newest version with:

  (wget -O - pi.dk/3 || curl 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.


=item abc-file:

The file can be generated by:

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

=item def-file:

The file can be generated by:

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

=item abc0-file:

The file can be generated by:

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

=item abc_-file:

The file can be generated by:

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

=item tsv-file.tsv

The file can be generated by:

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

=item num30000

The file can be generated by:

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

=item num1000000

The file can be generated by:

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

=item num_%header

The file can be generated by:

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

=item 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.

=back


=head1 Input sources

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

=head2 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.


=head2 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.

=head3 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

=head2 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.


=head2 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.

=head2 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

=head2 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


=head1 Building the command line

=head2 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 and only if $SHELL=.../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

=head2 Replacement strings

=head3 The 5 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:

  A

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

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

Output:

  B

The replacement string {#} gives the job number:

  parallel echo {#} ::: A B C

Output (the order may be different):

  1
  2
  3

=head2 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:

  A

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

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

Output:

  B

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

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

Output (the order may be different):

  1
  2
  3

=head2 Positional replacement strings

With multiple input sources the argument from the individual input
sources can be access 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

=head2 Input from columns

The columns in a file can be bound to positional replacement strings
using --colsep. Here the columns are separated with 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

=head2 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

=head2 More than one argument

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

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

Output:

  2

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:

  17

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

Running 4 jobs in parallel will split the last line of arguments into
4 jobs resulting in a total of 5 jobs:

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

Output:

  5

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

=head2 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:

  A

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:

  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


=head2 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


=head1 Controling 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:

  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 (which, however, is much slower):

  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

=head2 Saving output into files

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

  parallel --files ::: A B C

Output will be similar to:

  /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 ::: A B C

Output will be similar to:

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

Or:

  TMPDIR=/var/tmp parallel --files ::: 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

but also these files were generated containing the standard output
(stdout) and standard error (stderr):

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

This is useful if you are running multiple variables:

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

Generated files:

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

The directories are named after the variables and their values.

=head1 Control the execution

=head2 Number of simultaneous jobs 

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

  /usr/bin/time parallel -N0 -j64 sleep 1 ::: {1..128}

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 ::: {1..128}

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

  /usr/bin/time parallel -N0 --jobs 200% sleep 1 ::: {1..128}

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

  /usr/bin/time parallel -N0 --jobs 0 sleep 1 ::: {1..128}

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 ::: {1..128} &
  sleep 1
  echo 0 > my_jobs
  wait

The first second only 50% of the CPU cores will run a job. The '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 ::: {1..128}

=head2 Interactiveness

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

=head2 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:

  parallel --timeout 2.1 sleep {}\; echo {} ::: 1 2 3 4

Output:

  1
  2

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:

  2.1
  2.2
  3
  2.3

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 

=head2 Progress

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 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 if the job was
run on a remote host, 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 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 != 0.

=head2 Termination

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

  parallel -j2 --halt 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 2 the running jobs will be killed immediately:

  parallel -j2 --halt 2 echo {}\; exit {} ::: 0 0 1 2 3

Output:

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

GNU Parallel can retry the command with --retries. This is useful if a
command fails for unkown 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.

=head2 Limiting the ressources

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

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

=head1 Remote execution

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

=head2 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

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.

The 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.

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

To force GNU Parallel to treat a server having a given number of CPU
cores prepend #/ to the sshlogin:

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

Output:

  force 4 cpus on server

=head2 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 --transfer cat ::: input_file 

Output:

  This is input_file

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

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

Output: Same as above.

There is a short hand for --transfer --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.


=head2 Working dir

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

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

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

The special I<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/...]


=head2 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.

=head2 Ignore hosts that are down

In clusters with many hosts a few of the 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

=head2 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.

=head2 Transfer 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

=head2 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 -tt -oLogLevel=quiet lo  'eval `echo $SHELL | grep "/t\{0,1\}csh" > /dev/null  && echo setenv PARALLEL_SEQ '$PARALLEL_SEQ'\;  setenv PARALLEL_PID '$PARALLEL_PID'  || echo PARALLEL_SEQ='$PARALLEL_SEQ'\;export PARALLEL_SEQ\;  PARALLEL_PID='$PARALLEL_PID'\;export PARALLEL_PID` ;'  tty\ \>/dev/null\ \&\&\ stty\ isig\ -onlcr\ -echo\;echo\ bar;
  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 server mkdir -p .parallel/tmp/hk-31483-1; rsync -rlDzR -essh ./abc-file server:.parallel/tmp/hk-31483-1;ssh -tt -oLogLevel=quiet server  'eval `echo $SHELL | grep "/t\{0,1\}csh" > /dev/null  && echo setenv PARALLEL_SEQ '$PARALLEL_SEQ'\;  setenv PARALLEL_PID '$PARALLEL_PID'  || echo PARALLEL_SEQ='$PARALLEL_SEQ'\;export PARALLEL_SEQ\;  PARALLEL_PID='$PARALLEL_PID'\;export PARALLEL_PID` ;'  tty\ \>/dev/null\ \&\&\ stty\ isig\ -onlcr\ -echo\;mkdir\ -p\ .parallel/tmp/hk-31483-1\;\ cd\ .parallel/tmp/hk-31483-1\ \&\&\ echo\ \$SHELL\ \|\ grep\ \"/t\\\{0,1\\\}csh\"\ \>\ /dev/null\ \&\&\ setenv\ my_func3\ \\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func\\\ \\\$1\\\ \\\>\\\ \\\$1.out\"'
  '\"\\\}\ \&\&\ setenv\ VAR\ foo\ \&\&\ setenv\ my_func2\ \\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func2\\\ \\\$VAR\\\ \\\$1\"'
  '\"\\\}\ \|\|\ export\ my_func3=\\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func\\\ \\\$1\\\ \\\>\\\ \\\$1.out\"'
  '\"\\\}\ \&\&\ export\ VAR=foo\ \&\&\ export\ my_func2=\\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func2\\\ \\\$VAR\\\ \\\$1\"'
  '\"\\\}\ \&\&\ eval\ my_func3\"\$my_func3\"\ \&\&\ eval\ my_func2\"\$my_func2\"\;\\nice\ -n17\ /bin/bash\ -c\ my_func3\\\ abc-file;_EXIT_status=$?; mkdir -p .; rsync --rsync-path=cd\ .parallel/tmp/hk-31483-1/.\;\ rsync -rlDzR -essh server:abc-file.out .;ssh server rm\ -f\ .parallel/tmp/hk-31483-1/abc-file\;rm\ -f\ .parallel/tmp/hk-31483-1/abc-file.out\;rm -rf .parallel/tmp/hk-31483-1\;; exit $_EXIT_status;

=head1 --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.

=head2 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.

=head2 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).

=head2 Record separators

GNU Parallel uses separators to determine where two record 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

=head2 Header

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 %:

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

Output (the order may be different):

  %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.

=head1 Shebang

=head2 Input data and parallel command in the same file

GNU Parallel is often called as:

  cat input_file | parallel command

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

UNIX-scripts start with a shebang line like:

  #!/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

=head2 Parallelizing existing scripts

GNU Parallel is often called as:

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

If command is a script parallel can be combined into a single file so:

  cat input_file | command
  command foo bar

will run the script in parallel.

This perl script perl_echo works like echo:

  #!/usr/bin/perl

  print "@ARGV\n"

It can be called as:

  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:

=over 9

=item Perl:

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

=item Python:

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

=item Bash:

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

=item R:

#!/usr/bin/parallel --shebang-wrap /usr/bin/Rscript --vanilla --slave

=item GNUplot:

#!/usr/bin/parallel --shebang-wrap ARG={} /usr/bin/gnuplot

=item Ruby:

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

=back

=head1 Semaphore

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

An alias for 'parallel --semaphore' is 'sem'. The default is to allow
only one program to run at a time (technically called a mutex). The
program is started in the background. Use --wait for all 'sem's 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:

  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 the same 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.

=head2 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:

  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


=head1 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:

  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):

  131071

--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

=head1 Profiles

The defaults for GNU Parallel can be changed systemwise 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 '-S :,'$SERVER1 > ~/.parallel/cluster
  echo '--nice 17' >> ~/.parallel/cluster
  echo '--filter-hosts' >> ~/.parallel/cluster
  echo '--timeout 300%' >> ~/.parallel/cluster
  echo '--env _' >> ~/.parallel/cluster
  parallel --profile cluster echo ::: A B C

Output:

  A
  B
  C

Profiles can be combined:

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

Output:

  ssh -tt -oLogLevel=quiet lo  'eval `echo $SHELL | grep "/t\{0,1\}csh" > /dev/null  && echo setenv PARALLEL_SEQ '$PARALLEL_SEQ'\;  setenv PARALLEL_PID '$PARALLEL_PID'  || echo PARALLEL_SEQ='$PARALLEL_SEQ'\;export PARALLEL_SEQ\;  PARALLEL_PID='$PARALLEL_PID'\;export PARALLEL_PID` ;'  tty\ \>/dev/null\ \&\&\ stty\ isig\ -onlcr\ -echo\;echo\ \$SHELL\ \|\ grep\ \"/t\\\{0,1\\\}csh\"\ \>\ /dev/null\ \&\&\ setenv\ SERVER1\ lo\ \&\&\ setenv\ MYVAR\ foo\\\ bar\ \&\&\ setenv\ VAR\ foo\ \&\&\ setenv\ my_func\ \\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func\\\ \\\$1\"'
  '\"\\\}\ \&\&\ setenv\ my_func2\ \\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func2\\\ \\\$VAR\\\ \\\$1\"'
  '\"\\\}\ \|\|\ export\ SERVER1=lo\ \&\&\ export\ MYVAR=foo\\\ bar\ \&\&\ export\ VAR=foo\ \&\&\ export\ my_func=\\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func\\\ \\\$1\"'
  '\"\\\}\ \&\&\ export\ my_func2=\\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func2\\\ \\\$VAR\\\ \\\$1\"'
  '\"\\\}\ \&\&\ eval\ my_func\"\$my_func\"\ \&\&\ eval\ my_func2\"\$my_func2\"\;\\nice\ -n17\ /bin/bash\ -c\ echo\\\ A;
  ssh -tt -oLogLevel=quiet lo  'eval `echo $SHELL | grep "/t\{0,1\}csh" > /dev/null  && echo setenv PARALLEL_SEQ '$PARALLEL_SEQ'\;  setenv PARALLEL_PID '$PARALLEL_PID'  || echo PARALLEL_SEQ='$PARALLEL_SEQ'\;export PARALLEL_SEQ\;  PARALLEL_PID='$PARALLEL_PID'\;export PARALLEL_PID` ;'  tty\ \>/dev/null\ \&\&\ stty\ isig\ -onlcr\ -echo\;echo\ \$SHELL\ \|\ grep\ \"/t\\\{0,1\\\}csh\"\ \>\ /dev/null\ \&\&\ setenv\ SERVER1\ lo\ \&\&\ setenv\ MYVAR\ foo\\\ bar\ \&\&\ setenv\ VAR\ foo\ \&\&\ setenv\ my_func\ \\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func\\\ \\\$1\"'
  '\"\\\}\ \&\&\ setenv\ my_func2\ \\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func2\\\ \\\$VAR\\\ \\\$1\"'
  '\"\\\}\ \|\|\ export\ SERVER1=lo\ \&\&\ export\ MYVAR=foo\\\ bar\ \&\&\ export\ VAR=foo\ \&\&\ export\ my_func=\\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func\\\ \\\$1\"'
  '\"\\\}\ \&\&\ export\ my_func2=\\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func2\\\ \\\$VAR\\\ \\\$1\"'
  '\"\\\}\ \&\&\ eval\ my_func\"\$my_func\"\ \&\&\ eval\ my_func2\"\$my_func2\"\;\\nice\ -n17\ /bin/bash\ -c\ echo\\\ B;
  ssh -tt -oLogLevel=quiet lo  'eval `echo $SHELL | grep "/t\{0,1\}csh" > /dev/null  && echo setenv PARALLEL_SEQ '$PARALLEL_SEQ'\;  setenv PARALLEL_PID '$PARALLEL_PID'  || echo PARALLEL_SEQ='$PARALLEL_SEQ'\;export PARALLEL_SEQ\;  PARALLEL_PID='$PARALLEL_PID'\;export PARALLEL_PID` ;'  tty\ \>/dev/null\ \&\&\ stty\ isig\ -onlcr\ -echo\;echo\ \$SHELL\ \|\ grep\ \"/t\\\{0,1\\\}csh\"\ \>\ /dev/null\ \&\&\ setenv\ SERVER1\ lo\ \&\&\ setenv\ MYVAR\ foo\\\ bar\ \&\&\ setenv\ VAR\ foo\ \&\&\ setenv\ my_func\ \\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func\\\ \\\$1\"'
  '\"\\\}\ \&\&\ setenv\ my_func2\ \\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func2\\\ \\\$VAR\\\ \\\$1\"'
  '\"\\\}\ \|\|\ export\ SERVER1=lo\ \&\&\ export\ MYVAR=foo\\\ bar\ \&\&\ export\ VAR=foo\ \&\&\ export\ my_func=\\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func\\\ \\\$1\"'
  '\"\\\}\ \&\&\ export\ my_func2=\\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func2\\\ \\\$VAR\\\ \\\$1\"'
  '\"\\\}\ \&\&\ eval\ my_func\"\$my_func\"\ \&\&\ eval\ my_func2\"\$my_func2\"\;\\nice\ -n17\ /bin/bash\ -c\ echo\\\ C;


=head1 Spread the word

I hope you have learned something from this tutorial.

If you like GNU Parallel:

=over 2

=item *

Give a demo at your local user group/team/colleagues

=item *

Post the intro videos and the tutorial on Reddit, Diaspora*,
forums, blogs, Identi.ca, Google+, Twitter, Facebook, Linkedin,
mailing lists

=item *

Request or write a review for your favourite blog or magazine

=item *

Invite me for your next conference

=back

If you use GNU Parallel for research:

=over 2

=item *

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

=back

If GNU Parallel saves you money:

=over 2

=item *

(Have your company) donate to FSF https://my.fsf.org/donate/

=back

(C) 20130822 Ole Tange GPLv3


=cut