
*********************
GNU PARALLEL EXAMPLES
*********************


EXAMPLE: Working as xargs -n1. Argument appending
=================================================


GNU \ **parallel**\  can work similar to \ **xargs -n1**\ .

To compress all html files using \ **gzip**\  run:


.. code-block:: perl

   find . -name '*.html' | parallel gzip --best


If the file names may contain a newline use \ **-0**\ . Substitute FOO BAR with FUBAR in all files in this dir and subdirs:


.. code-block:: perl

   find . -type f -print0 | \
     parallel -q0 perl -i -pe 's/FOO BAR/FUBAR/g'


Note \ **-q**\  is needed because of the space in 'FOO BAR'.


EXAMPLE: Simple network scanner
===============================


\ **prips**\  can generate IP-addresses from CIDR notation. With GNU \ **parallel**\  you can build a simple network scanner to see which addresses respond to \ **ping**\ :


.. code-block:: perl

   prips 130.229.16.0/20 | \
     parallel --timeout 2 -j0 \
       'ping -c 1 {} >/dev/null && echo {}' 2>/dev/null



EXAMPLE: Reading arguments from command line
============================================


GNU \ **parallel**\  can take the arguments from command line instead of stdin (standard input). To compress all html files in the current dir using \ **gzip**\  run:


.. code-block:: perl

   parallel gzip --best ::: *.html


To convert \*.wav to \*.mp3 using LAME running one process per CPU run:


.. code-block:: perl

   parallel lame {} -o {.}.mp3 ::: *.wav



EXAMPLE: Inserting multiple arguments
=====================================


When moving a lot of files like this: \ **mv \*.log destdir**\  you will sometimes get the error:


.. code-block:: perl

   bash: /bin/mv: Argument list too long


because there are too many files. You can instead do:


.. code-block:: perl

   ls | grep -E '\.log$' | parallel mv {} destdir


This will run \ **mv**\  for each file. It can be done faster if \ **mv**\  gets as many arguments that will fit on the line:


.. code-block:: perl

   ls | grep -E '\.log$' | parallel -m mv {} destdir


In many shells you can also use \ **printf**\ :


.. code-block:: perl

   printf '%s\0' *.log | parallel -0 -m mv {} destdir



EXAMPLE: Context replace
========================


To remove the files \ *pict0000.jpg*\  .. \ *pict9999.jpg*\  you could do:


.. code-block:: perl

   seq -w 0 9999 | parallel rm pict{}.jpg


You could also do:


.. code-block:: perl

   seq -w 0 9999 | perl -pe 's/(.*)/pict$1.jpg/' | parallel -m rm


The first will run \ **rm**\  10000 times, while the last will only run \ **rm**\  as many times needed to keep the command line length short enough to avoid \ **Argument list too long**\  (it typically runs 1-2 times).

You could also run:


.. code-block:: perl

   seq -w 0 9999 | parallel -X rm pict{}.jpg


This will also only run \ **rm**\  as many times needed to keep the command line length short enough.


EXAMPLE: Compute intensive jobs and substitution
================================================


If ImageMagick is installed this will generate a thumbnail of a jpg file:


.. code-block:: perl

   convert -geometry 120 foo.jpg thumb_foo.jpg


This will run with number-of-cpus jobs in parallel for all jpg files in a directory:


.. code-block:: perl

   ls *.jpg | parallel convert -geometry 120 {} thumb_{}


To do it recursively use \ **find**\ :


.. code-block:: perl

   find . -name '*.jpg' | \
     parallel convert -geometry 120 {} {}_thumb.jpg


Notice how the argument has to start with \ **{}**\  as \ **{}**\  will include path (e.g. running \ **convert -geometry 120 ./foo/bar.jpg thumb_./foo/bar.jpg**\  would clearly be wrong). The command will generate files like ./foo/bar.jpg_thumb.jpg.

Use \ **{.}**\  to avoid the extra .jpg in the file name. This command will make files like ./foo/bar_thumb.jpg:


.. code-block:: perl

   find . -name '*.jpg' | \
     parallel convert -geometry 120 {} {.}_thumb.jpg



EXAMPLE: Substitution and redirection
=====================================


This will generate an uncompressed version of .gz-files next to the .gz-file:


.. code-block:: perl

   parallel zcat {} ">"{.} ::: *.gz


Quoting of > is necessary to postpone the redirection. Another solution is to quote the whole command:


.. code-block:: perl

   parallel "zcat {} >{.}" ::: *.gz


Other special shell characters (such as \* ; $ > < | >> <<) also need to be put in quotes, as they may otherwise be interpreted by the shell and not given to GNU \ **parallel**\ .


EXAMPLE: Composed commands
==========================


A job can consist of several commands. This will print the number of files in each directory:


.. code-block:: perl

   ls | parallel 'echo -n {}" "; ls {}|wc -l'


To put the output in a file called <name>.dir:


.. code-block:: perl

   ls | parallel '(echo -n {}" "; ls {}|wc -l) >{}.dir'


Even small shell scripts can be run by GNU \ **parallel**\ :


.. code-block:: perl

   find . | parallel 'a={}; name=${a##*/};' \
     'upper=$(echo "$name" | tr "[:lower:]" "[:upper:]");'\
     'echo "$name - $upper"'
 
   ls | parallel 'mv {} "$(echo {} | tr "[:upper:]" "[:lower:]")"'


Given a list of URLs, list all URLs that fail to download. Print the line number and the URL.


.. code-block:: perl

   cat urlfile | parallel "wget {} 2>/dev/null || grep -n {} urlfile"


Create a mirror directory with the same file names except all files and symlinks are empty files.


.. code-block:: perl

   cp -rs /the/source/dir mirror_dir
   find mirror_dir -type l | parallel -m rm {} '&&' touch {}


Find the files in a list that do not exist


.. code-block:: perl

   cat file_list | parallel 'if [ ! -e {} ] ; then echo {}; fi'



EXAMPLE: Composed command with perl replacement string
======================================================


You have a bunch of file. You want them sorted into dirs. The dir of each file should be named the first letter of the file name.


.. code-block:: perl

   parallel 'mkdir -p {=s/(.).*/$1/=}; mv {} {=s/(.).*/$1/=}' ::: *



EXAMPLE: Composed command with multiple input sources
=====================================================


You have a dir with files named as 24 hours in 5 minute intervals: 00:00, 00:05, 00:10 .. 23:55. You want to find the files missing:


.. code-block:: perl

   parallel [ -f {1}:{2} ] "||" echo {1}:{2} does not exist \
     ::: {00..23} ::: {00..55..5}



EXAMPLE: Calling Bash functions
===============================


If the composed command is longer than a line, it becomes hard to read. In Bash you can use functions. Just remember to \ **export -f**\  the function.


.. code-block:: perl

   doit() {
     echo Doing it for $1
     sleep 2
     echo Done with $1
   }
   export -f doit
   parallel doit ::: 1 2 3
 
   doubleit() {
     echo Doing it for $1 $2
     sleep 2
     echo Done with $1 $2
   }
   export -f doubleit
   parallel doubleit ::: 1 2 3 ::: a b


To do this on remote servers you need to transfer the function using \ **--env**\ :


.. code-block:: perl

   parallel --env doit -S server doit ::: 1 2 3
   parallel --env doubleit -S server doubleit ::: 1 2 3 ::: a b


If your environment (aliases, variables, and functions) is small you can copy the full environment without having to \ **export -f**\  anything. See \ **env_parallel**\ .


EXAMPLE: Function tester
========================


To test a program with different parameters:


.. code-block:: perl

   tester() {
     if (eval "$@") >&/dev/null; then
       perl -e 'printf "\033[30;102m[ OK ]\033[0m @ARGV\n"' "$@"
     else
       perl -e 'printf "\033[30;101m[FAIL]\033[0m @ARGV\n"' "$@"
     fi
   }
   export -f tester
   parallel tester my_program ::: arg1 arg2
   parallel tester exit ::: 1 0 2 0


If \ **my_program**\  fails a red FAIL will be printed followed by the failing command; otherwise a green OK will be printed followed by the command.


EXAMPLE: Identify few failing jobs
==================================


\ **--bar**\  works best if jobs have no output. If the failing jobs have output you can identify the jobs like this:


.. code-block:: perl

   job-with-few-failures() {
       # Force reproducibility
       RANDOM=$1
       # This fails 1% (328 of 32768)
       if [ $RANDOM -lt 328 ] ; then
         echo Failed $1
       fi
   }
   export -f job-with-few-failures
   seq 1000 | parallel --bar --tag job-with-few-failures



EXAMPLE: Continously show the latest line of output
===================================================


It can be useful to monitor the output of running jobs.

This shows the most recent output line until a job finishes. After which the output of the job is printed in full:


.. code-block:: perl

   parallel '{} | tee >(cat >&3)' ::: 'command 1' 'command 2' \
     3> >(perl -ne '$|=1;chomp;printf"%.'$COLUMNS's\r",$_." "x100')



EXAMPLE: Log rotate
===================


Log rotation renames a logfile to an extension with a higher number: log.1 becomes log.2, log.2 becomes log.3, and so on. The oldest log is removed. To avoid overwriting files the process starts backwards from the high number to the low number.  This will keep 10 old versions of the log:


.. code-block:: perl

   seq 9 -1 1 | parallel -j1 mv log.{} log.'{= $_++ =}'
   mv log log.1



EXAMPLE: Removing file extension when processing files
======================================================


When processing files removing the file extension using \ **{.}**\  is often useful.

Create a directory for each zip-file and unzip it in that dir:


.. code-block:: perl

   parallel 'mkdir {.}; cd {.}; unzip ../{}' ::: *.zip


Recompress all .gz files in current directory using \ **bzip2**\  running 1 job per CPU in parallel:


.. code-block:: perl

   parallel "zcat {} | bzip2 >{.}.bz2 && rm {}" ::: *.gz


Convert all WAV files to MP3 using LAME:


.. code-block:: perl

   find sounddir -type f -name '*.wav' | parallel lame {} -o {.}.mp3


Put all converted in the same directory:


.. code-block:: perl

   find sounddir -type f -name '*.wav' | \
     parallel lame {} -o mydir/{/.}.mp3



EXAMPLE: Replacing parts of file names
======================================


If you deal with paired end reads, you will have files like barcode1_R1.fq.gz, barcode1_R2.fq.gz, barcode2_R1.fq.gz, and barcode2_R2.fq.gz.

You want barcode\ *N*\ _R1 to be processed with barcode\ *N*\ _R2.


.. code-block:: perl

     parallel --plus myprocess {} {/_R1.fq.gz/_R2.fq.gz} ::: *_R1.fq.gz


If the barcode does not contain '_R1', you can do:


.. code-block:: perl

     parallel --plus myprocess {} {/_R1/_R2} ::: *_R1.fq.gz



EXAMPLE: Removing strings from the argument
===========================================


If you have directory with tar.gz files and want these extracted in the corresponding dir (e.g foo.tar.gz will be extracted in the dir foo) you can do:


.. code-block:: perl

   parallel --plus 'mkdir {..}; tar -C {..} -xf {}' ::: *.tar.gz


If you want to remove a different ending, you can use {%string}:


.. code-block:: perl

   parallel --plus echo {%_demo} ::: mycode_demo keep_demo_here


You can also remove a starting string with {#string}


.. code-block:: perl

   parallel --plus echo {#demo_} ::: demo_mycode keep_demo_here


To remove a string anywhere you can use regular expressions with {/regexp/replacement} and leave the replacement empty:


.. code-block:: perl

   parallel --plus echo {/demo_/} ::: demo_mycode remove_demo_here



EXAMPLE: Download 24 images for each of the past 30 days
========================================================


Let us assume a website stores images like:


.. code-block:: perl

   https://www.example.com/path/to/YYYYMMDD_##.jpg


where YYYYMMDD is the date and ## is the number 01-24. This will download images for the past 30 days:


.. code-block:: perl

   getit() {
     date=$(date -d "today -$1 days" +%Y%m%d)
     num=$2
     echo wget https://www.example.com/path/to/${date}_${num}.jpg
   }
   export -f getit
   
   parallel getit ::: $(seq 30) ::: $(seq -w 24)


\ **$(date -d "today -$1 days" +%Y%m%d)**\  will give the dates in YYYYMMDD with \ **$1**\  days subtracted.


EXAMPLE: Download world map from NASA
=====================================


NASA provides tiles to download on earthdata.nasa.gov. Download tiles for Blue Marble world map and create a 10240x20480 map.


.. code-block:: perl

   base=https://map1a.vis.earthdata.nasa.gov/wmts-geo/wmts.cgi
   service="SERVICE=WMTS&REQUEST=GetTile&VERSION=1.0.0"
   layer="LAYER=BlueMarble_ShadedRelief_Bathymetry"
   set="STYLE=&TILEMATRIXSET=EPSG4326_500m&TILEMATRIX=5"
   tile="TILEROW={1}&TILECOL={2}"
   format="FORMAT=image%2Fjpeg"
   url="$base?$service&$layer&$set&$tile&$format"
 
   parallel -j0 -q wget "$url" -O {1}_{2}.jpg ::: {0..19} ::: {0..39}
   parallel eval convert +append {}_{0..39}.jpg line{}.jpg ::: {0..19}
   convert -append line{0..19}.jpg world.jpg



EXAMPLE: Download Apollo-11 images from NASA using jq
=====================================================


Search NASA using their API to get JSON for images related to 'apollo 11' and has 'moon landing' in the description.

The search query returns JSON containing URLs to JSON containing collections of pictures. One of the pictures in each of these collection is \ *large*\ .

\ **wget**\  is used to get the JSON for the search query. \ **jq**\  is then used to extract the URLs of the collections. \ **parallel**\  then calls \ **wget**\  to get each collection, which is passed to \ **jq**\  to extract the URLs of all images. \ **grep**\  filters out the \ *large*\  images, and \ **parallel**\  finally uses \ **wget**\  to fetch the images.


.. code-block:: perl

   base="https://images-api.nasa.gov/search"
   q="q=apollo 11"
   description="description=moon landing"
   media_type="media_type=image"
   wget -O - "$base?$q&$description&$media_type" |
     jq -r .collection.items[].href |
     parallel wget -O - |
     jq -r .[] |
     grep large |
     parallel wget



EXAMPLE: Download video playlist in parallel
============================================


\ **youtube-dl**\  is an excellent tool to download videos. It can, however, not download videos in parallel. This takes a playlist and downloads 10 videos in parallel.


.. code-block:: perl

   url='youtu.be/watch?v=0wOf2Fgi3DE&list=UU_cznB5YZZmvAmeq7Y3EriQ'
   export url
   youtube-dl --flat-playlist "https://$url" |
     parallel --tagstring {#} --lb -j10 \
       youtube-dl --playlist-start {#} --playlist-end {#} '"https://$url"'



EXAMPLE: Prepend last modified date (ISO8601) to file name
==========================================================



.. code-block:: perl

   parallel mv {} '{= $a=pQ($_); $b=$_;' \
     '$_=qx{date -r "$a" +%FT%T}; chomp; $_="$_ $b" =}' ::: *


\ **{=**\  and \ **=}**\  mark a perl expression. \ **pQ**\  perl-quotes the string. \ **date +%FT%T**\  is the date in ISO8601 with time.


EXAMPLE: Save output in ISO8601 dirs
====================================


Save output from \ **ps aux**\  every second into dirs named yyyy-mm-ddThh:mm:ss+zz:zz.


.. code-block:: perl

   seq 1000 | parallel -N0 -j1 --delay 1 \
     --results '{= $_=`date -Isec`; chomp=}/' ps aux



EXAMPLE: Digital clock with "blinking" :
========================================


The : in a digital clock blinks. To make every other line have a ':' and the rest a ' ' a perl expression is used to look at the 3rd input source. If the value modulo 2 is 1: Use ":" otherwise use " ":


.. code-block:: perl

   parallel -k echo {1}'{=3 $_=$_%2?":":" "=}'{2}{3} \
     ::: {0..12} ::: {0..5} ::: {0..9}



EXAMPLE: Aggregating content of files
=====================================


This:


.. code-block:: perl

   parallel --header : echo x{X}y{Y}z{Z} \> x{X}y{Y}z{Z} \
   ::: X {1..5} ::: Y {01..10} ::: Z {1..5}


will generate the files x1y01z1 .. x5y10z5. If you want to aggregate the output grouping on x and z you can do this:


.. code-block:: perl

   parallel eval 'cat {=s/y01/y*/=} > {=s/y01//=}' ::: *y01*


For all values of x and z it runs commands like:


.. code-block:: perl

   cat x1y*z1 > x1z1


So you end up with x1z1 .. x5z5 each containing the content of all values of y.


EXAMPLE: Breadth first parallel web crawler/mirrorer
====================================================


This script below will crawl and mirror a URL in parallel.  It downloads first pages that are 1 click down, then 2 clicks down, then 3; instead of the normal depth first, where the first link link on each page is fetched first.

Run like this:


.. code-block:: perl

   PARALLEL=-j100 ./parallel-crawl http://gatt.org.yeslab.org/


Remove the \ **wget**\  part if you only want a web crawler.

It works by fetching a page from a list of URLs and looking for links in that page that are within the same starting URL and that have not already been seen. These links are added to a new queue. When all the pages from the list is done, the new queue is moved to the list of URLs and the process is started over until no unseen links are found.


.. code-block:: perl

   #!/bin/bash
 
   # E.g. http://gatt.org.yeslab.org/
   URL=$1
   # Stay inside the start dir
   BASEURL=$(echo $URL | perl -pe 's:#.*::; s:(//.*/)[^/]*:$1:')
   URLLIST=$(mktemp urllist.XXXX)
   URLLIST2=$(mktemp urllist.XXXX)
   SEEN=$(mktemp seen.XXXX)
 
   # Spider to get the URLs
   echo $URL >$URLLIST
   cp $URLLIST $SEEN
 
   while [ -s $URLLIST ] ; do
     cat $URLLIST |
       parallel lynx -listonly -image_links -dump {} \; \
         wget -qm -l1 -Q1 {} \; echo Spidered: {} \>\&2 |
         perl -ne 's/#.*//; s/\s+\d+.\s(\S+)$/$1/ and
           do { $seen{$1}++ or print }' |
       grep -F $BASEURL |
       grep -v -x -F -f $SEEN | tee -a $SEEN > $URLLIST2
     mv $URLLIST2 $URLLIST
   done
 
   rm -f $URLLIST $URLLIST2 $SEEN



EXAMPLE: Process files from a tar file while unpacking
======================================================


If the files to be processed are in a tar file then unpacking one file and processing it immediately may be faster than first unpacking all files.


.. code-block:: perl

   tar xvf foo.tgz | perl -ne 'print $l;$l=$_;END{print $l}' | \
     parallel echo


The Perl one-liner is needed to make sure the file is complete before handing it to GNU \ **parallel**\ .


EXAMPLE: Rewriting a for-loop and a while-read-loop
===================================================


for-loops like this:


.. code-block:: perl

   (for x in `cat list` ; do
     do_something $x
   done) | process_output


and while-read-loops like this:


.. code-block:: perl

   cat list | (while read x ; do
     do_something $x
   done) | process_output


can be written like this:


.. code-block:: perl

   cat list | parallel do_something | process_output


For example: Find which host name in a list has IP address 1.2.3 4:


.. code-block:: perl

   cat hosts.txt | parallel -P 100 host | grep 1.2.3.4


If the processing requires more steps the for-loop like this:


.. code-block:: perl

   (for x in `cat list` ; do
     no_extension=${x%.*};
     do_step1 $x scale $no_extension.jpg
     do_step2 <$x $no_extension
   done) | process_output


and while-loops like this:


.. code-block:: perl

   cat list | (while read x ; do
     no_extension=${x%.*};
     do_step1 $x scale $no_extension.jpg
     do_step2 <$x $no_extension
   done) | process_output


can be written like this:


.. code-block:: perl

   cat list | parallel "do_step1 {} scale {.}.jpg ; do_step2 <{} {.}" |\
     process_output


If the body of the loop is bigger, it improves readability to use a function:


.. code-block:: perl

   (for x in `cat list` ; do
     do_something $x
     [... 100 lines that do something with $x ...]
   done) | process_output
 
   cat list | (while read x ; do
     do_something $x
     [... 100 lines that do something with $x ...]
   done) | process_output


can both be rewritten as:


.. code-block:: perl

   doit() {
     x=$1
     do_something $x
     [... 100 lines that do something with $x ...]
   }
   export -f doit
   cat list | parallel doit



EXAMPLE: Rewriting nested for-loops
===================================


Nested for-loops like this:


.. code-block:: perl

   (for x in `cat xlist` ; do
     for y in `cat ylist` ; do
       do_something $x $y
     done
   done) | process_output


can be written like this:


.. code-block:: perl

   parallel do_something {1} {2} :::: xlist ylist | process_output


Nested for-loops like this:


.. code-block:: perl

   (for colour in red green blue ; do
     for size in S M L XL XXL ; do
       echo $colour $size
     done
   done) | sort


can be written like this:


.. code-block:: perl

   parallel echo {1} {2} ::: red green blue ::: S M L XL XXL | sort



EXAMPLE: Finding the lowest difference between files
====================================================


\ **diff**\  is good for finding differences in text files. \ **diff | wc -l**\  gives an indication of the size of the difference. To find the differences between all files in the current dir do:


.. code-block:: perl

   parallel --tag 'diff {1} {2} | wc -l' ::: * ::: * | sort -nk3


This way it is possible to see if some files are closer to other files.


EXAMPLE: for-loops with column names
====================================


When doing multiple nested for-loops it can be easier to keep track of the loop variable if is is named instead of just having a number. Use \ **--header :**\  to let the first argument be an named alias for the positional replacement string:


.. code-block:: perl

   parallel --header : echo {colour} {size} \
     ::: colour red green blue ::: size S M L XL XXL


This also works if the input file is a file with columns:


.. code-block:: perl

   cat addressbook.tsv | \
     parallel --colsep '\t' --header : echo {Name} {E-mail address}



EXAMPLE: All combinations in a list
===================================


GNU \ **parallel**\  makes all combinations when given two lists.

To make all combinations in a single list with unique values, you repeat the list and use replacement string \ **{choose_k}**\ :


.. code-block:: perl

   parallel --plus echo {choose_k} ::: A B C D ::: A B C D
 
   parallel --plus echo 2{2choose_k} 1{1choose_k} ::: A B C D ::: A B C D


\ **{choose_k}**\  works for any number of input sources:


.. code-block:: perl

   parallel --plus echo {choose_k} ::: A B C D ::: A B C D ::: A B C D


Where \ **{choose_k}**\  does not care about order, \ **{uniq}**\  cares about order. It simply skips jobs where values from different input sources are the same:


.. code-block:: perl

   parallel --plus echo {uniq} ::: A B C  ::: A B C  ::: A B C
   parallel --plus echo {1uniq}+{2uniq}+{3uniq} \
     ::: A B C  ::: A B C  ::: A B C


The behaviour of \ **{choose_k}**\  is undefined, if the input values of each source are different.


EXAMPLE: From a to b and b to c
===============================


Assume you have input like:


.. code-block:: perl

   aardvark
   babble
   cab
   dab
   each


and want to run combinations like:


.. code-block:: perl

   aardvark babble
   babble cab
   cab dab
   dab each


If the input is in the file in.txt:


.. code-block:: perl

   parallel echo {1} - {2} ::::+ <(head -n -1 in.txt) <(tail -n +2 in.txt)


If the input is in the array $a here are two solutions:


.. code-block:: perl

   seq $((${#a[@]}-1)) | \
     env_parallel --env a echo '${a[{=$_--=}]} - ${a[{}]}'
   parallel echo {1} - {2} ::: "${a[@]::${#a[@]}-1}" :::+ "${a[@]:1}"



EXAMPLE: Count the differences between all files in a dir
=========================================================


Using \ **--results**\  the results are saved in /tmp/diffcount\*.


.. code-block:: perl

   parallel --results /tmp/diffcount "diff -U 0 {1} {2} | \
     tail -n +3 |grep -v '^@'|wc -l" ::: * ::: *


To see the difference between file A and file B look at the file '/tmp/diffcount/1/A/2/B'.


EXAMPLE: Speeding up fast jobs
==============================


Starting a job on the local machine takes around 3-10 ms. This can be a big overhead if the job takes very few ms to run. Often you can group small jobs together using \ **-X**\  which will make the overhead less significant. Compare the speed of these:


.. code-block:: perl

   seq -w 0 9999 | parallel touch pict{}.jpg
   seq -w 0 9999 | parallel -X touch pict{}.jpg


If your program cannot take multiple arguments, then you can use GNU \ **parallel**\  to spawn multiple GNU \ **parallel**\ s:


.. code-block:: perl

   seq -w 0 9999999 | \
     parallel -j10 -q -I,, --pipe parallel -j0 touch pict{}.jpg


If \ **-j0**\  normally spawns 252 jobs, then the above will try to spawn 2520 jobs. On a normal GNU/Linux system you can spawn 32000 jobs using this technique with no problems. To raise the 32000 jobs limit raise /proc/sys/kernel/pid_max to 4194303.

If you do not need GNU \ **parallel**\  to have control over each job (so no need for \ **--retries**\  or \ **--joblog**\  or similar), then it can be even faster if you can generate the command lines and pipe those to a shell. So if you can do this:


.. code-block:: perl

   mygenerator | sh


Then that can be parallelized like this:


.. code-block:: perl

   mygenerator | parallel --pipe --block 10M sh


E.g.


.. code-block:: perl

   mygenerator() {
     seq 10000000 | perl -pe 'print "echo This is fast job number "';
   }
   mygenerator | parallel --pipe --block 10M sh


The overhead is 100000 times smaller namely around 100 nanoseconds per job.


EXAMPLE: Using shell variables
==============================


When using shell variables you need to quote them correctly as they may otherwise be interpreted by the shell.

Notice the difference between:


.. code-block:: perl

   ARR=("My brother's 12\" records are worth <\$\$\$>"'!' Foo Bar)
   parallel echo ::: ${ARR[@]} # This is probably not what you want


and:


.. code-block:: perl

   ARR=("My brother's 12\" records are worth <\$\$\$>"'!' Foo Bar)
   parallel echo ::: "${ARR[@]}"


When using variables in the actual command that contains special characters (e.g. space) you can quote them using \ **'"$VAR"'**\  or using "'s and \ **-q**\ :


.. code-block:: perl

   VAR="My brother's 12\" records are worth <\$\$\$>"
   parallel -q echo "$VAR" ::: '!'
   export VAR
   parallel echo '"$VAR"' ::: '!'


If \ **$VAR**\  does not contain ' then \ **"'$VAR'"**\  will also work (and does not need \ **export**\ ):


.. code-block:: perl

   VAR="My 12\" records are worth <\$\$\$>"
   parallel echo "'$VAR'" ::: '!'


If you use them in a function you just quote as you normally would do:


.. code-block:: perl

   VAR="My brother's 12\" records are worth <\$\$\$>"
   export VAR
   myfunc() { echo "$VAR" "$1"; }
   export -f myfunc
   parallel myfunc ::: '!'



EXAMPLE: Group output lines
===========================


When running jobs that output data, you often do not want the output of multiple jobs to run together. GNU \ **parallel**\  defaults to grouping the output of each job, so the output is printed when the job finishes. If you want full lines to be printed while the job is running you can use \ **--line-buffer**\ . If you want output to be printed as soon as possible you can use \ **-u**\ .

Compare the output of:


.. code-block:: perl

   parallel wget --progress=dot --limit-rate=100k \
     https://ftpmirror.gnu.org/parallel/parallel-20{}0822.tar.bz2 \
     ::: {12..16}
   parallel --line-buffer wget --progress=dot --limit-rate=100k \
     https://ftpmirror.gnu.org/parallel/parallel-20{}0822.tar.bz2 \
     ::: {12..16}
   parallel --latest-line wget --progress=dot --limit-rate=100k \
     https://ftpmirror.gnu.org/parallel/parallel-20{}0822.tar.bz2 \
     ::: {12..16}
   parallel -u wget --progress=dot --limit-rate=100k \
     https://ftpmirror.gnu.org/parallel/parallel-20{}0822.tar.bz2 \
     ::: {12..16}



EXAMPLE: Tag output lines
=========================


GNU \ **parallel**\  groups the output lines, but it can be hard to see where the different jobs begin. \ **--tag**\  prepends the argument to make that more visible:


.. code-block:: perl

   parallel --tag wget --limit-rate=100k \
     https://ftpmirror.gnu.org/parallel/parallel-20{}0822.tar.bz2 \
     ::: {12..16}


\ **--tag**\  works with \ **--line-buffer**\  but not with \ **-u**\ :


.. code-block:: perl

   parallel --tag --line-buffer wget --limit-rate=100k \
     https://ftpmirror.gnu.org/parallel/parallel-20{}0822.tar.bz2 \
     ::: {12..16}


Check the uptime of the servers in \ *~/.parallel/sshloginfile*\ :


.. code-block:: perl

   parallel --tag -S .. --nonall uptime



EXAMPLE: Colorize output
========================


Give each job a new color. Most terminals support ANSI colors with the escape code "\\033[30;3Xm" where 0 <= X <= 7:


.. code-block:: perl

     seq 10 | \
       parallel --tagstring '\033[30;3{=$_=++$::color%8=}m' seq {}
     parallel --rpl '{color} $_="\033[30;3".(++$::color%8)."m"' \
       --tagstring {color} seq {} ::: {1..10}


To get rid of the initial \\t (which comes from \ **--tagstring**\ ):


.. code-block:: perl

     ... | perl -pe 's/\t//'



EXAMPLE: Keep order of output same as order of input
====================================================


Normally the output of a job will be printed as soon as it completes. Sometimes you want the order of the output to remain the same as the order of the input. This is often important, if the output is used as input for another system. \ **-k**\  will make sure the order of output will be in the same order as input even if later jobs end before earlier jobs.

Append a string to every line in a text file:


.. code-block:: perl

   cat textfile | parallel -k echo {} append_string


If you remove \ **-k**\  some of the lines may come out in the wrong order.

Another example is \ **traceroute**\ :


.. code-block:: perl

   parallel traceroute ::: qubes-os.org debian.org freenetproject.org


will give traceroute of qubes-os.org, debian.org and freenetproject.org, but it will be sorted according to which job completed first.

To keep the order the same as input run:


.. code-block:: perl

   parallel -k traceroute ::: qubes-os.org debian.org freenetproject.org


This will make sure the traceroute to qubes-os.org will be printed first.

A bit more complex example is downloading a huge file in chunks in parallel: Some internet connections will deliver more data if you download files in parallel. For downloading files in parallel see: "EXAMPLE: Download 10 images for each of the past 30 days". But if you are downloading a big file you can download the file in chunks in parallel.

To download byte 10000000-19999999 you can use \ **curl**\ :


.. code-block:: perl

   curl -r 10000000-19999999 https://example.com/the/big/file >file.part


To download a 1 GB file we need 100 10MB chunks downloaded and combined in the correct order.


.. code-block:: perl

   seq 0 99 | parallel -k curl -r \
     {}0000000-{}9999999 https://example.com/the/big/file > file



EXAMPLE: Parallel grep
======================


\ **grep -r**\  greps recursively through directories. GNU \ **parallel**\  can often speed this up.


.. code-block:: perl

   find . -type f | parallel -k -j150% -n 1000 -m grep -H -n STRING {}


This will run 1.5 job per CPU, and give 1000 arguments to \ **grep**\ .

There are situations where the above will be slower than \ **grep -r**\ :


- 
 
 If data is already in RAM. The overhead of starting jobs and buffering output may outweigh the benefit of running in parallel.
 


- 
 
 If the files are big. If a file cannot be read in a single seek, the disk may start thrashing.
 


The speedup is caused by two factors:


- 
 
 On rotating harddisks small files often require a seek for each file. By searching for more files in parallel, the arm may pass another wanted file on its way.
 


- 
 
 NVMe drives often perform better by having multiple command running in parallel.
 



EXAMPLE: Grepping n lines for m regular expressions.
====================================================


The simplest solution to grep a big file for a lot of regexps is:


.. code-block:: perl

   grep -f regexps.txt bigfile


Or if the regexps are fixed strings:


.. code-block:: perl

   grep -F -f regexps.txt bigfile


There are 3 limiting factors: CPU, RAM, and disk I/O.

RAM is easy to measure: If the \ **grep**\  process takes up most of your free memory (e.g. when running \ **top**\ ), then RAM is a limiting factor.

CPU is also easy to measure: If the \ **grep**\  takes >90% CPU in \ **top**\ , then the CPU is a limiting factor, and parallelization will speed this up.

It is harder to see if disk I/O is the limiting factor, and depending on the disk system it may be faster or slower to parallelize. The only way to know for certain is to test and measure.

Limiting factor: RAM
--------------------


The normal \ **grep -f regexps.txt bigfile**\  works no matter the size of bigfile, but if regexps.txt is so big it cannot fit into memory, then you need to split this.

\ **grep -F**\  takes around 100 bytes of RAM and \ **grep**\  takes about 500 bytes of RAM per 1 byte of regexp. So if regexps.txt is 1% of your RAM, then it may be too big.

If you can convert your regexps into fixed strings do that. E.g. if the lines you are looking for in bigfile all looks like:


.. code-block:: perl

   ID1 foo bar baz Identifier1 quux
   fubar ID2 foo bar baz Identifier2


then your regexps.txt can be converted from:


.. code-block:: perl

   ID1.*Identifier1
   ID2.*Identifier2


into:


.. code-block:: perl

   ID1 foo bar baz Identifier1
   ID2 foo bar baz Identifier2


This way you can use \ **grep -F**\  which takes around 80% less memory and is much faster.

If it still does not fit in memory you can do this:


.. code-block:: perl

   parallel --pipe-part -a regexps.txt --block 1M grep -F -f - -n bigfile | \
     sort -un | perl -pe 's/^\d+://'


The 1M should be your free memory divided by the number of CPU threads and divided by 200 for \ **grep -F**\  and by 1000 for normal \ **grep**\ . On GNU/Linux you can do:


.. code-block:: perl

   free=$(awk '/^((Swap)?Cached|MemFree|Buffers):/ { sum += $2 }
               END { print sum }' /proc/meminfo)
   percpu=$((free / 200 / $(parallel --number-of-threads)))k
 
   parallel --pipe-part -a regexps.txt --block $percpu --compress \
     grep -F -f - -n bigfile | \
     sort -un | perl -pe 's/^\d+://'


If you can live with duplicated lines and wrong order, it is faster to do:


.. code-block:: perl

   parallel --pipe-part -a regexps.txt --block $percpu --compress \
     grep -F -f - bigfile



Limiting factor: CPU
--------------------


If the CPU is the limiting factor parallelization should be done on the regexps:


.. code-block:: perl

   cat regexps.txt | parallel --pipe -L1000 --round-robin --compress \
     grep -f - -n bigfile | \
     sort -un | perl -pe 's/^\d+://'


The command will start one \ **grep**\  per CPU and read \ *bigfile*\  one time per CPU, but as that is done in parallel, all reads except the first will be cached in RAM. Depending on the size of \ *regexps.txt*\  it may be faster to use \ **--block 10m**\  instead of \ **-L1000**\ .

Some storage systems perform better when reading multiple chunks in parallel. This is true for some RAID systems and for some network file systems. To parallelize the reading of \ *bigfile*\ :


.. code-block:: perl

   parallel --pipe-part --block 100M -a bigfile -k --compress \
     grep -f regexps.txt


This will split \ *bigfile*\  into 100MB chunks and run \ **grep**\  on each of these chunks. To parallelize both reading of \ *bigfile*\  and \ *regexps.txt*\  combine the two using \ **--cat**\ :


.. code-block:: perl

   parallel --pipe-part --block 100M -a bigfile --cat cat regexps.txt \
     \| parallel --pipe -L1000 --round-robin grep -f - {}


If a line matches multiple regexps, the line may be duplicated.


Bigger problem
--------------


If the problem is too big to be solved by this, you are probably ready for Lucene.



EXAMPLE: Using remote computers
===============================


To run commands on a remote computer SSH needs to be set up and you must be able to login without entering a password (The commands \ **ssh-copy-id**\ , \ **ssh-agent**\ , and \ **sshpass**\  may help you do that).

If you need to login to a whole cluster, you typically do not want to accept the host key for every host. You want to accept them the first time and be warned if they are ever changed. To do that:


.. code-block:: perl

   # Add the servers to the sshloginfile
   (echo servera; echo serverb) > .parallel/my_cluster
   # Make sure .ssh/config exist
   touch .ssh/config
   cp .ssh/config .ssh/config.backup
   # Disable StrictHostKeyChecking temporarily
   (echo 'Host *'; echo StrictHostKeyChecking no) >> .ssh/config
   parallel --slf my_cluster --nonall true
   # Remove the disabling of StrictHostKeyChecking
   mv .ssh/config.backup .ssh/config


The servers in \ **.parallel/my_cluster**\  are now added in \ **.ssh/known_hosts**\ .

To run \ **echo**\  on \ **server.example.com**\ :


.. code-block:: perl

   seq 10 | parallel --sshlogin server.example.com echo


To run commands on more than one remote computer run:


.. code-block:: perl

   seq 10 | parallel --sshlogin s1.example.com,s2.example.net echo


Or:


.. code-block:: perl

   seq 10 | parallel --sshlogin server.example.com \
     --sshlogin server2.example.net echo


If the login username is \ *foo*\  on \ *server2.example.net*\  use:


.. code-block:: perl

   seq 10 | parallel --sshlogin server.example.com \
     --sshlogin foo@server2.example.net echo


If your list of hosts is \ *server1-88.example.net*\  with login \ *foo*\ :


.. code-block:: perl

   seq 10 | parallel -Sfoo@server{1..88}.example.net echo


To distribute the commands to a list of computers, make a file \ *mycomputers*\  with all the computers:


.. code-block:: perl

   server.example.com
   foo@server2.example.com
   server3.example.com


Then run:


.. code-block:: perl

   seq 10 | parallel --sshloginfile mycomputers echo


To include the local computer add the special sshlogin ':' to the list:


.. code-block:: perl

   server.example.com
   foo@server2.example.com
   server3.example.com
   :


GNU \ **parallel**\  will try to determine the number of CPUs on each of the remote computers, and run one job per CPU - even if the remote computers do not have the same number of CPUs.

If the number of CPUs on the remote computers is not identified correctly the number of CPUs can be added in front. Here the computer has 8 CPUs.


.. code-block:: perl

   seq 10 | parallel --sshlogin 8/server.example.com echo



EXAMPLE: Transferring of files
==============================


To recompress gzipped files with \ **bzip2**\  using a remote computer run:


.. code-block:: perl

   find logs/ -name '*.gz' | \
     parallel --sshlogin server.example.com \
     --transfer "zcat {} | bzip2 -9 >{.}.bz2"


This will list the .gz-files in the \ *logs*\  directory and all directories below. Then it will transfer the files to \ *server.example.com*\  to the corresponding directory in \ *$HOME/logs*\ . On \ *server.example.com*\  the file will be recompressed using \ **zcat**\  and \ **bzip2**\  resulting in the corresponding file with \ *.gz*\  replaced with \ *.bz2*\ .

If you want the resulting bz2-file to be transferred back to the local computer add \ *--return {.}.bz2*\ :


.. code-block:: perl

   find logs/ -name '*.gz' | \
     parallel --sshlogin server.example.com \
     --transfer --return {.}.bz2 "zcat {} | bzip2 -9 >{.}.bz2"


After the recompressing is done the \ *.bz2*\ -file is transferred back to the local computer and put next to the original \ *.gz*\ -file.

If you want to delete the transferred files on the remote computer add \ *--cleanup*\ . This will remove both the file transferred to the remote computer and the files transferred from the remote computer:


.. code-block:: perl

   find logs/ -name '*.gz' | \
     parallel --sshlogin server.example.com \
     --transfer --return {.}.bz2 --cleanup "zcat {} | bzip2 -9 >{.}.bz2"


If you want run on several computers add the computers to \ *--sshlogin*\  either using ',' or multiple \ *--sshlogin*\ :


.. code-block:: perl

   find logs/ -name '*.gz' | \
     parallel --sshlogin server.example.com,server2.example.com \
     --sshlogin server3.example.com \
     --transfer --return {.}.bz2 --cleanup "zcat {} | bzip2 -9 >{.}.bz2"


You can add the local computer using \ *--sshlogin :*\ . This will disable the removing and transferring for the local computer only:


.. code-block:: perl

   find logs/ -name '*.gz' | \
     parallel --sshlogin server.example.com,server2.example.com \
     --sshlogin server3.example.com \
     --sshlogin : \
     --transfer --return {.}.bz2 --cleanup "zcat {} | bzip2 -9 >{.}.bz2"


Often \ *--transfer*\ , \ *--return*\  and \ *--cleanup*\  are used together. They can be shortened to \ *--trc*\ :


.. code-block:: perl

   find logs/ -name '*.gz' | \
     parallel --sshlogin server.example.com,server2.example.com \
     --sshlogin server3.example.com \
     --sshlogin : \
     --trc {.}.bz2 "zcat {} | bzip2 -9 >{.}.bz2"


With the file \ *mycomputers*\  containing the list of computers it becomes:


.. code-block:: perl

   find logs/ -name '*.gz' | parallel --sshloginfile mycomputers \
     --trc {.}.bz2 "zcat {} | bzip2 -9 >{.}.bz2"


If the file \ *~/.parallel/sshloginfile*\  contains the list of computers the special short hand \ *-S ..*\  can be used:


.. code-block:: perl

   find logs/ -name '*.gz' | parallel -S .. \
     --trc {.}.bz2 "zcat {} | bzip2 -9 >{.}.bz2"



EXAMPLE: Advanced file transfer
===============================


Assume you have files in in/\*, want them processed on server, and transferred back into /other/dir:


.. code-block:: perl

   parallel -S server --trc /other/dir/./{/}.out \
     cp {/} {/}.out ::: in/./*



EXAMPLE: Distributing work to local and remote computers
========================================================


Convert \*.mp3 to \*.ogg running one process per CPU on local computer and server2:


.. code-block:: perl

   parallel --trc {.}.ogg -S server2,: \
     'mpg321 -w - {} | oggenc -q0 - -o {.}.ogg' ::: *.mp3



EXAMPLE: Running the same command on remote computers
=====================================================


To run the command \ **uptime**\  on remote computers you can do:


.. code-block:: perl

   parallel --tag --nonall -S server1,server2 uptime


\ **--nonall**\  reads no arguments. If you have a list of jobs you want to run on each computer you can do:


.. code-block:: perl

   parallel --tag --onall -S server1,server2 echo ::: 1 2 3


Remove \ **--tag**\  if you do not want the sshlogin added before the output.

If you have a lot of hosts use '-j0' to access more hosts in parallel.


EXAMPLE: Running 'sudo' on remote computers
===========================================


Put the password into passwordfile then run:


.. code-block:: perl

   parallel --ssh 'cat passwordfile | ssh' --nonall \
     -S user@server1,user@server2 sudo -S ls -l /root



EXAMPLE: Using remote computers behind NAT wall
===============================================


If the workers are behind a NAT wall, you need some trickery to get to them.

If you can \ **ssh**\  to a jumphost, and reach the workers from there, then the obvious solution would be this, but it \ **does not work**\ :


.. code-block:: perl

   parallel --ssh 'ssh jumphost ssh' -S host1 echo ::: DOES NOT WORK


It does not work because the command is dequoted by \ **ssh**\  twice where as GNU \ **parallel**\  only expects it to be dequoted once.

You can use a bash function and have GNU \ **parallel**\  quote the command:


.. code-block:: perl

   jumpssh() { ssh -A jumphost ssh $(parallel --shellquote ::: "$@"); }
   export -f jumpssh
   parallel --ssh jumpssh -S host1 echo ::: this works


Or you can instead put this in \ **~/.ssh/config**\ :


.. code-block:: perl

   Host host1 host2 host3
     ProxyCommand ssh jumphost.domain nc -w 1 %h 22


It requires \ **nc(netcat)**\  to be installed on jumphost. With this you can simply:


.. code-block:: perl

   parallel -S host1,host2,host3 echo ::: This does work


No jumphost, but port forwards
------------------------------


If there is no jumphost but each server has port 22 forwarded from the firewall (e.g. the firewall's port 22001 = port 22 on host1, 22002 = host2, 22003 = host3) then you can use \ **~/.ssh/config**\ :


.. code-block:: perl

   Host host1.v
     Port 22001
   Host host2.v
     Port 22002
   Host host3.v
     Port 22003
   Host *.v
     Hostname firewall


And then use host{1..3}.v as normal hosts:


.. code-block:: perl

   parallel -S host1.v,host2.v,host3.v echo ::: a b c



No jumphost, no port forwards
-----------------------------


If ports cannot be forwarded, you need some sort of VPN to traverse the NAT-wall. TOR is one options for that, as it is very easy to get working.

You need to install TOR and setup a hidden service. In \ **torrc**\  put:


.. code-block:: perl

   HiddenServiceDir /var/lib/tor/hidden_service/
   HiddenServicePort 22 127.0.0.1:22


Then start TOR: \ **/etc/init.d/tor restart**\ 

The TOR hostname is now in \ **/var/lib/tor/hidden_service/hostname**\  and is something similar to \ **izjafdceobowklhz.onion**\ . Now you simply prepend \ **torsocks**\  to \ **ssh**\ :


.. code-block:: perl

   parallel --ssh 'torsocks ssh' -S izjafdceobowklhz.onion \
     -S zfcdaeiojoklbwhz.onion,auclucjzobowklhi.onion echo ::: a b c


If not all hosts are accessible through TOR:


.. code-block:: perl

   parallel -S 'torsocks ssh izjafdceobowklhz.onion,host2,host3' \
     echo ::: a b c


See more \ **ssh**\  tricks on https://en.wikibooks.org/wiki/OpenSSH/Cookbook/Proxies_and_Jump_Hosts



EXAMPLE: Use sshpass with ssh
=============================


If you cannot use passwordless login, you may be able to use \ **sshpass**\ :


.. code-block:: perl

   seq 10 | parallel -S user-with-password:MyPassword@server echo


or:


.. code-block:: perl

   export SSHPASS='MyPa$$w0rd'
   seq 10 | parallel -S user-with-password:@server echo



EXAMPLE: Use outrun instead of ssh
==================================


\ **outrun**\  lets you run a command on a remote server. \ **outrun**\  sets up a connection to access files at the source server, and automatically transfers files. \ **outrun**\  must be installed on the remote system.

You can use \ **outrun**\  in an sshlogin this way:


.. code-block:: perl

   parallel -S 'outrun user@server' command


or:


.. code-block:: perl

   parallel --ssh outrun -S server command



EXAMPLE: Slurm cluster
======================


The Slurm Workload Manager is used in many clusters.

Here is a simple example of using GNU \ **parallel**\  to call \ **srun**\ :


.. code-block:: perl

   #!/bin/bash
   
   #SBATCH --time 00:02:00
   #SBATCH --ntasks=4
   #SBATCH --job-name GnuParallelDemo
   #SBATCH --output gnuparallel.out
   
   module purge
   module load gnu_parallel
   
   my_parallel="parallel --delay .2 -j $SLURM_NTASKS"
   my_srun="srun --export=all --exclusive -n1"
   my_srun="$my_srun --cpus-per-task=1 --cpu-bind=cores"
   $my_parallel "$my_srun" echo This is job {} ::: {1..20}



EXAMPLE: Parallelizing rsync
============================


\ **rsync**\  is a great tool, but sometimes it will not fill up the available bandwidth. Running multiple \ **rsync**\  in parallel can fix this.


.. code-block:: perl

   cd src-dir
   find . -type f |
     parallel -j10 -X rsync -zR -Ha ./{} fooserver:/dest-dir/


Adjust \ **-j10**\  until you find the optimal number.

\ **rsync -R**\  will create the needed subdirectories, so all files are not put into a single dir. The \ **./**\  is needed so the resulting command looks similar to:


.. code-block:: perl

   rsync -zR ././sub/dir/file fooserver:/dest-dir/


The \ **/./**\  is what \ **rsync -R**\  works on.

If you are unable to push data, but need to pull them and the files are called digits.png (e.g. 000000.png) you might be able to do:


.. code-block:: perl

   seq -w 0 99 | parallel rsync -Havessh fooserver:src/*{}.png destdir/



EXAMPLE: Use multiple inputs in one command
===========================================


Copy files like foo.es.ext to foo.ext:


.. code-block:: perl

   ls *.es.* | perl -pe 'print; s/\.es//' | parallel -N2 cp {1} {2}


The perl command spits out 2 lines for each input. GNU \ **parallel**\  takes 2 inputs (using \ **-N2**\ ) and replaces {1} and {2} with the inputs.

Count in binary:


.. code-block:: perl

   parallel -k echo ::: 0 1 ::: 0 1 ::: 0 1 ::: 0 1 ::: 0 1 ::: 0 1


Print the number on the opposing sides of a six sided die:


.. code-block:: perl

   parallel --link -a <(seq 6) -a <(seq 6 -1 1) echo
   parallel --link echo :::: <(seq 6) <(seq 6 -1 1)


Convert files from all subdirs to PNG-files with consecutive numbers (useful for making input PNG's for \ **ffmpeg**\ ):


.. code-block:: perl

   parallel --link -a <(find . -type f | sort) \
     -a <(seq $(find . -type f|wc -l)) convert {1} {2}.png


Alternative version:


.. code-block:: perl

   find . -type f | sort | parallel convert {} {#}.png



EXAMPLE: Use a table as input
=============================


Content of table_file.tsv:


.. code-block:: perl

   foo<TAB>bar
   baz <TAB> quux


To run:


.. code-block:: perl

   cmd -o bar -i foo
   cmd -o quux -i baz


you can run:


.. code-block:: perl

   parallel -a table_file.tsv --colsep '\t' cmd -o {2} -i {1}


Note: The default for GNU \ **parallel**\  is to remove the spaces around the columns. To keep the spaces:


.. code-block:: perl

   parallel -a table_file.tsv --trim n --colsep '\t' cmd -o {2} -i {1}



EXAMPLE: Output to database
===========================


GNU \ **parallel**\  can output to a database table and a CSV-file:


.. code-block:: perl

   dburl=csv:///%2Ftmp%2Fmydir
   dbtableurl=$dburl/mytable.csv
   parallel --sqlandworker $dbtableurl seq ::: {1..10}


It is rather slow and takes up a lot of CPU time because GNU \ **parallel**\  parses the whole CSV file for each update.

A better approach is to use an SQLite-base and then convert that to CSV:


.. code-block:: perl

   dburl=sqlite3:///%2Ftmp%2Fmy.sqlite
   dbtableurl=$dburl/mytable
   parallel --sqlandworker $dbtableurl seq ::: {1..10}
   sql $dburl '.headers on' '.mode csv' 'SELECT * FROM mytable;'


This takes around a second per job.

If you have access to a real database system, such as PostgreSQL, it is even faster:


.. code-block:: perl

   dburl=pg://user:pass@host/mydb
   dbtableurl=$dburl/mytable
   parallel --sqlandworker $dbtableurl seq ::: {1..10}
   sql $dburl \
     "COPY (SELECT * FROM mytable) TO stdout DELIMITER ',' CSV HEADER;"


Or MySQL:


.. code-block:: perl

   dburl=mysql://user:pass@host/mydb
   dbtableurl=$dburl/mytable
   parallel --sqlandworker $dbtableurl seq ::: {1..10}
   sql -p -B $dburl "SELECT * FROM mytable;" > mytable.tsv
   perl -pe 's/"/""/g; s/\t/","/g; s/^/"/; s/$/"/;
     %s=("\\" => "\\", "t" => "\t", "n" => "\n");
     s/\\([\\tn])/$s{$1}/g;' mytable.tsv



EXAMPLE: Output to CSV-file for R
=================================


If you have no need for the advanced job distribution control that a database provides, but you simply want output into a CSV file that you can read into R or LibreCalc, then you can use \ **--results**\ :


.. code-block:: perl

   parallel --results my.csv seq ::: 10 20 30
   R
   > mydf <- read.csv("my.csv");
   > print(mydf[2,])
   > write(as.character(mydf[2,c("Stdout")]),'')



EXAMPLE: Use XML as input
=========================


The show Aflyttet on Radio 24syv publishes an RSS feed with their audio podcasts on: http://arkiv.radio24syv.dk/audiopodcast/channel/4466232

Using \ **xpath**\  you can extract the URLs for 2019 and download them using GNU \ **parallel**\ :


.. code-block:: perl

   wget -O - http://arkiv.radio24syv.dk/audiopodcast/channel/4466232 | \
     xpath -e "//pubDate[contains(text(),'2019')]/../enclosure/@url" | \
     parallel -u wget '{= s/ url="//; s/"//; =}'



EXAMPLE: Run the same command 10 times
======================================


If you want to run the same command with the same arguments 10 times in parallel you can do:


.. code-block:: perl

   seq 10 | parallel -n0 my_command my_args



EXAMPLE: Working as cat | sh. Resource inexpensive jobs and evaluation
======================================================================


GNU \ **parallel**\  can work similar to \ **cat | sh**\ .

A resource inexpensive job is a job that takes very little CPU, disk I/O and network I/O. Ping is an example of a resource inexpensive job. wget is too - if the webpages are small.

The content of the file jobs_to_run:


.. code-block:: perl

   ping -c 1 10.0.0.1
   wget http://example.com/status.cgi?ip=10.0.0.1
   ping -c 1 10.0.0.2
   wget http://example.com/status.cgi?ip=10.0.0.2
   ...
   ping -c 1 10.0.0.255
   wget http://example.com/status.cgi?ip=10.0.0.255


To run 100 processes simultaneously do:


.. code-block:: perl

   parallel -j 100 < jobs_to_run


As there is not a \ *command*\  the jobs will be evaluated by the shell.


EXAMPLE: Call program with FASTA sequence
=========================================


FASTA files have the format:


.. code-block:: perl

   >Sequence name1
   sequence
   sequence continued
   >Sequence name2
   sequence
   sequence continued
   more sequence


To call \ **myprog**\  with the sequence as argument run:


.. code-block:: perl

   cat file.fasta |
     parallel --pipe -N1 --recstart '>' --rrs \
       'read a; echo Name: "$a"; myprog $(tr -d "\n")'



EXAMPLE: Call program with interleaved FASTQ records
====================================================


FASTQ files have the format:


.. code-block:: perl

   @M10991:61:000000000-A7EML:1:1101:14011:1001 1:N:0:28
   CTCCTAGGTCGGCATGATGGGGGAAGGAGAGCATGGGAAGAAATGAGAGAGTAGCAAGG
   +
   #8BCCGGGGGFEFECFGGGGGGGGG@;FFGGGEG@FF<EE<@FFC,CEGCCGGFF<FGF


Interleaved FASTQ starts with a line like these:


.. code-block:: perl

   @HWUSI-EAS100R:6:73:941:1973#0/1
   @EAS139:136:FC706VJ:2:2104:15343:197393 1:Y:18:ATCACG
   @EAS139:136:FC706VJ:2:2104:15343:197393 1:N:18:1


where '/1' and ' 1:' determines this is read 1.

This will cut big.fq into one chunk per CPU thread and pass it on stdin (standard input) to the program fastq-reader:


.. code-block:: perl

   parallel --pipe-part -a big.fq --block -1 --regexp \
     --recend '\n' --recstart '@.*(/1| 1:.*)\n[A-Za-z\n\.~]' \
     fastq-reader



EXAMPLE: Processing a big file using more CPUs
==============================================


To process a big file or some output you can use \ **--pipe**\  to split up the data into blocks and pipe the blocks into the processing program.

If the program is \ **gzip -9**\  you can do:


.. code-block:: perl

   cat bigfile | parallel --pipe --recend '' -k gzip -9 > bigfile.gz


This will split \ **bigfile**\  into blocks of 1 MB and pass that to \ **gzip -9**\  in parallel. One \ **gzip**\  will be run per CPU. The output of \ **gzip -9**\  will be kept in order and saved to \ **bigfile.gz**\ 

\ **gzip**\  works fine if the output is appended, but some processing does not work like that - for example sorting. For this GNU \ **parallel**\  can put the output of each command into a file. This will sort a big file in parallel:


.. code-block:: perl

   cat bigfile | parallel --pipe --files sort |\
     parallel -Xj1 sort -m {} ';' rm {} >bigfile.sort


Here \ **bigfile**\  is split into blocks of around 1MB, each block ending in '\\n' (which is the default for \ **--recend**\ ). Each block is passed to \ **sort**\  and the output from \ **sort**\  is saved into files. These files are passed to the second \ **parallel**\  that runs \ **sort -m**\  on the files before it removes the files. The output is saved to \ **bigfile.sort**\ .

GNU \ **parallel**\ 's \ **--pipe**\  maxes out at around 100 MB/s because every byte has to be copied through GNU \ **parallel**\ . But if \ **bigfile**\  is a real (seekable) file GNU \ **parallel**\  can by-pass the copying and send the parts directly to the program:


.. code-block:: perl

   parallel --pipe-part --block 100m -a bigfile --files sort |\
     parallel -Xj1 sort -m {} ';' rm {} >bigfile.sort



EXAMPLE: Grouping input lines
=============================


When processing with \ **--pipe**\  you may have lines grouped by a value. Here is \ *my.csv*\ :


.. code-block:: perl

    Transaction Customer Item
 	1	a	53
 	2	b	65
 	3	b	82
 	4	c	96
 	5	c	67
 	6	c	13
 	7	d	90
 	8	d	43
 	9	d	91
 	10	d	84
 	11	e	72
 	12	e	102
 	13	e	63
 	14	e	56
 	15	e	74


Let us assume you want GNU \ **parallel**\  to process each customer. In other words: You want all the transactions for a single customer to be treated as a single record.

To do this we preprocess the data with a program that inserts a record separator before each customer (column 2 = $F[1]). Here we first make a 50 character random string, which we then use as the separator:


.. code-block:: perl

   sep=`perl -e 'print map { ("a".."z","A".."Z")[rand(52)] } (1..50);'`
   cat my.csv | \
      perl -ape '$F[1] ne $l and print "'$sep'"; $l = $F[1]' | \
      parallel --recend $sep --rrs --pipe -N1 wc


If your program can process multiple customers replace \ **-N1**\  with a reasonable \ **--blocksize**\ .


EXAMPLE: Running more than 250 jobs workaround
==============================================


If you need to run a massive amount of jobs in parallel, then you will likely hit the filehandle limit which is often around 250 jobs. If you are super user you can raise the limit in /etc/security/limits.conf but you can also use this workaround. The filehandle limit is per process. That means that if you just spawn more GNU \ **parallel**\ s then each of them can run 250 jobs. This will spawn up to 2500 jobs:


.. code-block:: perl

   cat myinput |\
     parallel --pipe -N 50 --round-robin -j50 parallel -j50 your_prg


This will spawn up to 62500 jobs (use with caution - you need 64 GB RAM to do this, and you may need to increase /proc/sys/kernel/pid_max):


.. code-block:: perl

   cat myinput |\
     parallel --pipe -N 250 --round-robin -j250 parallel -j250 your_prg



EXAMPLE: Working as mutex and counting semaphore
================================================


The command \ **sem**\  is an alias for \ **parallel --semaphore**\ .

A counting semaphore will allow a given number of jobs to be started in the background.  When the number of jobs are running in the background, GNU \ **sem**\  will wait for one of these to complete before starting another command. \ **sem --wait**\  will wait for all jobs to complete.

Run 10 jobs concurrently in the background:


.. code-block:: perl

   for i in *.log ; do
     echo $i
     sem -j10 gzip $i ";" echo done
   done
   sem --wait


A mutex is a counting semaphore allowing only one job to run. This will edit the file \ *myfile*\  and prepends the file with lines with the numbers 1 to 3.


.. code-block:: perl

   seq 3 | parallel sem sed -i -e '1i{}' myfile


As \ *myfile*\  can be very big it is important only one process edits the file at the same time.

Name the semaphore to have multiple different semaphores active at the same time:


.. code-block:: perl

   seq 3 | parallel sem --id mymutex sed -i -e '1i{}' myfile



EXAMPLE: Mutex for a script
===========================


Assume a script is called from cron or from a web service, but only one instance can be run at a time. With \ **sem**\  and \ **--shebang-wrap**\  the script can be made to wait for other instances to finish. Here in \ **bash**\ :


.. code-block:: perl

   #!/usr/bin/sem --shebang-wrap -u --id $0 --fg /bin/bash
   
   echo This will run
   sleep 5
   echo exclusively


Here \ **perl**\ :


.. code-block:: perl

   #!/usr/bin/sem --shebang-wrap -u --id $0 --fg /usr/bin/perl
   
   print "This will run ";
   sleep 5;
   print "exclusively\n";


Here \ **python**\ :


.. code-block:: perl

   #!/usr/local/bin/sem --shebang-wrap -u --id $0 --fg /usr/bin/python
   
   import time
   print "This will run ";
   time.sleep(5)
   print "exclusively";



EXAMPLE: Start editor with file names from stdin (standard input)
=================================================================


You can use GNU \ **parallel**\  to start interactive programs like emacs or vi:


.. code-block:: perl

   cat filelist | parallel --tty -X emacs
   cat filelist | parallel --tty -X vi


If there are more files than will fit on a single command line, the editor will be started again with the remaining files.


EXAMPLE: Running sudo
=====================


\ **sudo**\  requires a password to run a command as root. It caches the access, so you only need to enter the password again if you have not used \ **sudo**\  for a while.

The command:


.. code-block:: perl

   parallel sudo echo ::: This is a bad idea


is no good, as you would be prompted for the sudo password for each of the jobs. Instead do:


.. code-block:: perl

   sudo parallel echo ::: This is a good idea


This way you only have to enter the sudo password once.


EXAMPLE: Run ping in parallel
=============================


\ **ping**\  prints out statistics when killed with CTRL-C.

Unfortunately, CTRL-C will also normally kill GNU \ **parallel**\ .

But by using \ **--open-tty**\  and ignoring SIGINT you can get the wanted effect:


.. code-block:: perl

   parallel -j0 --open-tty --lb --tag ping '{= $SIG{INT}=sub {} =}' \
     ::: 1.1.1.1 8.8.8.8 9.9.9.9 21.21.21.21 80.80.80.80 88.88.88.88


\ **--open-tty**\  will make the \ **ping**\ s receive SIGINT (from CTRL-C). CTRL-C will not kill GNU \ **parallel**\ , so that will only exit after \ **ping**\  is done.


EXAMPLE: GNU Parallel as queue system/batch manager
===================================================


GNU \ **parallel**\  can work as a simple job queue system or batch manager. The idea is to put the jobs into a file and have GNU \ **parallel**\  read from that continuously. As GNU \ **parallel**\  will stop at end of file we use \ **tail**\  to continue reading:


.. code-block:: perl

   true >jobqueue; tail -n+0 -f jobqueue | parallel


To submit your jobs to the queue:


.. code-block:: perl

   echo my_command my_arg >> jobqueue


You can of course use \ **-S**\  to distribute the jobs to remote computers:


.. code-block:: perl

   true >jobqueue; tail -n+0 -f jobqueue | parallel -S ..


Output only will be printed when reading the next input after a job has finished: So you need to submit a job after the first has finished to see the output from the first job.

If you keep this running for a long time, jobqueue will grow. A way of removing the jobs already run is by making GNU \ **parallel**\  stop when it hits a special value and then restart. To use \ **--eof**\  to make GNU \ **parallel**\  exit, \ **tail**\  also needs to be forced to exit:


.. code-block:: perl

   true >jobqueue;
   while true; do
     tail -n+0 -f jobqueue |
       (parallel -E StOpHeRe -S ..; echo GNU Parallel is now done;
        perl -e 'while(<>){/StOpHeRe/ and last};print <>' jobqueue > j2;
        (seq 1000 >> jobqueue &);
        echo Done appending dummy data forcing tail to exit)
     echo tail exited;
     mv j2 jobqueue
   done


In some cases you can run on more CPUs and computers during the night:


.. code-block:: perl

   # Day time
   echo 50% > jobfile
   cp day_server_list ~/.parallel/sshloginfile
   # Night time
   echo 100% > jobfile
   cp night_server_list ~/.parallel/sshloginfile
   tail -n+0 -f jobqueue | parallel --jobs jobfile -S ..


GNU \ **parallel**\  discovers if \ **jobfile**\  or \ **~/.parallel/sshloginfile**\  changes.


EXAMPLE: GNU Parallel as dir processor
======================================


If you have a dir in which users drop files that needs to be processed you can do this on GNU/Linux (If you know what \ **inotifywait**\  is called on other platforms file a bug report):


.. code-block:: perl

   inotifywait -qmre MOVED_TO -e CLOSE_WRITE --format %w%f my_dir |\
     parallel -u echo


This will run the command \ **echo**\  on each file put into \ **my_dir**\  or subdirs of \ **my_dir**\ .

You can of course use \ **-S**\  to distribute the jobs to remote computers:


.. code-block:: perl

   inotifywait -qmre MOVED_TO -e CLOSE_WRITE --format %w%f my_dir |\
     parallel -S ..  -u echo


If the files to be processed are in a tar file then unpacking one file and processing it immediately may be faster than first unpacking all files. Set up the dir processor as above and unpack into the dir.

Using GNU \ **parallel**\  as dir processor has the same limitations as using GNU \ **parallel**\  as queue system/batch manager.


EXAMPLE: Locate the missing package
===================================


If you have downloaded source and tried compiling it, you may have seen:


.. code-block:: perl

   $ ./configure
   [...]
   checking for something.h... no
   configure: error: "libsomething not found"


Often it is not obvious which package you should install to get that file. Debian has \`apt-file\` to search for a file. \`tracefile\` from https://codeberg.org/tange/tangetools can tell which files a program tried to access. In this case we are interested in one of the last files:


.. code-block:: perl

   $ tracefile -un ./configure | tail | parallel -j0 apt-file search




******
AUTHOR
******


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.

This helps funding further development; and it won't cost you a cent. If you pay 10000 EUR you should feel free to use GNU Parallel without citing.

Copyright (C) 2007-10-18 Ole Tange, http://ole.tange.dk

Copyright (C) 2008-2010 Ole Tange, http://ole.tange.dk

Copyright (C) 2010-2024 Ole Tange, http://ole.tange.dk and Free Software Foundation, Inc.

Parts of the manual concerning \ **xargs**\  compatibility is inspired by the manual of \ **xargs**\  from GNU findutils 4.4.2.


*******
LICENSE
*******


This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 3 of the License, or at your option any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program.  If not, see <https://www.gnu.org/licenses/>.

Documentation license I
=======================


Permission is granted to copy, distribute and/or modify this documentation under the terms of the GNU Free Documentation License, Version 1.3 or any later version published by the Free Software Foundation; with no Invariant Sections, with no Front-Cover Texts, and with no Back-Cover Texts.  A copy of the license is included in the file LICENSES/GFDL-1.3-or-later.txt.


Documentation license II
========================


You are free:


- \ **to Share**\ 
 
 to copy, distribute and transmit the work
 


- \ **to Remix**\ 
 
 to adapt the work
 


Under the following conditions:


- \ **Attribution**\ 
 
 You must attribute the work in the manner specified by the author or licensor (but not in any way that suggests that they endorse you or your use of the work).
 


- \ **Share Alike**\ 
 
 If you alter, transform, or build upon this work, you may distribute the resulting work only under the same, similar or a compatible license.
 


With the understanding that:


- \ **Waiver**\ 
 
 Any of the above conditions can be waived if you get permission from the copyright holder.
 


- \ **Public Domain**\ 
 
 Where the work or any of its elements is in the public domain under applicable law, that status is in no way affected by the license.
 


- \ **Other Rights**\ 
 
 In no way are any of the following rights affected by the license:
 
 
 - 
  
  Your fair dealing or fair use rights, or other applicable copyright exceptions and limitations;
  
 
 
 - 
  
  The author's moral rights;
  
 
 
 - 
  
  Rights other persons may have either in the work itself or in how the work is used, such as publicity or privacy rights.
  
 
 



- \ **Notice**\ 
 
 For any reuse or distribution, you must make clear to others the license terms of this work.
 


A copy of the full license is included in the file as LICENCES/CC-BY-SA-4.0.txt



********
SEE ALSO
********


\ **parallel**\ (1), \ **parallel_tutorial**\ (7), \ **env_parallel**\ (1), \ **parset**\ (1), \ **parsort**\ (1), \ **parallel_alternatives**\ (7), \ **parallel_design**\ (7), \ **niceload**\ (1), \ **sql**\ (1), \ **ssh**\ (1), \ **ssh-agent**\ (1), \ **sshpass**\ (1), \ **ssh-copy-id**\ (1), \ **rsync**\ (1)

