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The write-up below is based on parallel man page
Parallel is a Perl script written by Ole Tange that extends and improves capabilities of xargs. Unlike xargs, parallel can then split the input and pipe it into commands in parallel. Hence the name. See O. Tange (2011): Parallel - The Command-Line Power Tool, ;login: The USENIX Magazine, February 2011:42-47.
It can be used as a Slurping tool.
Parallel is written in Perl, and use several standard Perl modules such as Getopt::Long, IPC::Open3, Symbol, IO::File, POSIX, and File::Temp. For remote usage it also uses rsync with ssh.
If you use xargs and tee today you will find parallel very easy to use as parallel is written to have the same options as xargs. If you write loops in shell, you will find parallel may be able to replace most of the loops and make them run faster by running several jobs in parallel.
Parallel makes sure output from the commands is the same output as you would get had you run the commands sequentially. This makes it possible to use output from parallel as input for other programs.\
For each line of input parallel will execute command with the line as arguments. If no command is given, the line of input is executed. Several lines will be run in parallel. parallel can often be used as a substitute for xargs or cat | bash.
The most interesting part of parallel is that it allow ssh login via option --sshlogin (or -S). In this case ssh logging must not require a password.
Transferring Files
If your servers are not sharing storage (using NFS or something similar), you often need to transfer the files to be processed to the remote computers and the results back to the local computer.
To transfer a file to a remote computer, you will use --transfer:
parallel -S .. --transfer gzip < {} | wc -c ::: *.txt
Here we transfer each of the .txt files to the remote servers, compress them, and count how many bytes they now take up.
After a transfer you often will want to remove the transferred file from the remote computers.--cleanup does that for you:
parallel -S .. --transfer --cleanup gzip < {} | wc -c ::: *.txt
When processing files the result is often a file that you want copied back, after which the transferred and the result file should be removed from the remote computers:
parallel -S .. --transfer --return {.}.bz2 --cleanup zcat < {} | bzip2 >{.}.bz2 ::: *.gz
Here the .gz files will be transferred and then recompressed using zcat and bzip2.The resulting .bz2 file is transferred back, and the .gz and the .bz2 files are removed from the remote computers.The combination --transfer --cleanup --return foo is used so often that it has its own abbreviation: --trc foo.
You can specify multiple --trc if your command generates multiple result files.
GNU Parallel will try to detect the number of cores on remote computers and run one job per CPU core even if the computers have different number of CPU cores:
parallel -S .. --trc {.}.bz2 zcat < {} | bzip2 >{.}.bz2 ::: *.gz
Before looking at the options you may want to check out the EXAMPLEs after the list of options. That will give you an idea of what parallel is capable of.
You can also watch the intro video for a quick introduction: http://tinyogg.com/watch/TORaR/ http://tinyogg.com/watch/hfxKj/ and http://tinyogg.com/watch/YQuXd/ or http://www.youtube.com/watch?v=OpaiGYxkSuQ and http://www.youtube.com/watch?v=1ntxT-47VPA
parallel [options] [command [arguments]] < list_of_arguments parallel [options] [command [arguments]] ( ::: arguments | :::: argfile(s) ) ...parallel --semaphore [options] command
#!/usr/bin/parallel --shebang [options] [command [arguments]]
If command is given, parallel will behave similar to xargs. If command is not given parallel will behave similar to cat | sh.
The command must be an executable, a script or a composed command: an alias or a function will not work (see why http://www.perlmonks.org/index.pl?node_id=484296).
{.} can be used the same places as {}. The replacement string {.} can be changed with -U.
{/} can be used the same places as {}. The replacement string {/} can be changed with --basenamereplace.
{//} can be used the same places as {}. The replacement string {//} can be changed with --dirnamereplace.
{/.} can be used the same places as {}. The replacement string {/.} can be changed with --basenameextensionreplace.
The replacement string {#} can be changed with --seqreplace.
{n} can be used the same places as {}.
{n.} can be used the same places as {n}.
{n/} can be used the same places as {n}.
{n/.} can be used the same places as {n}.
The following are equivalent:
(echo file1; echo file2) | parallel gzip parallel gzip ::: file1 file2 parallel gzip {} ::: file1 file2 parallel --arg-sep ,, gzip {} ,, file1 file2 parallel --arg-sep ,, gzip ,, file1 file2 parallel ::: "gzip file1" "gzip file2"
To avoid treating ::: as special use --arg-sep to set the argument separator to something else. See also --arg-sep.
stdin (standard input) will be passed to the first process run.
If multiple ::: are given, each group will be treated as an input source, and all combinations of input sources will be generated. E.g. ::: 1 2 ::: a b c will result in the combinations (1,a) (1,b) (1,c) (2,a) (2,b) (2,c). This is useful for replacing nested for-loops.
::: and :::: can be mixed. So these are equivalent:
parallel echo {1} {2} {3} ::: 6 7 ::: 4 5 ::: 1 2 3 parallel echo {1} {2} {3} :::: <(seq 6 7) <(seq 4 5) :::: <(seq 1 3) parallel -a <(seq 6 7) echo {1} {2} {3} :::: <(seq 4 5) :::: <(seq 1 3) parallel -a <(seq 6 7) -a <(seq 4 5) echo {1} {2} {3} ::: 1 2 3 seq 6 7 | parallel -a - -a <(seq 4 5) echo {1} {2} {3} ::: 1 2 3 seq 4 5 | parallel echo {1} {2} {3} :::: <(seq 6 7) - ::: 1 2 3
::: and :::: can be mixed.
See -a.
If multiple -a are given, each input-file will be treated as an input source, and all combinations of input sources will be generated. E.g. The file foo contains 1 2, the file bar contains a b c. -a foo -a bar will result in the combinations (1,a) (1,b) (1,c) (2,a) (2,b) (2,c). This is useful for replacing nested for-loops.
See also --xapply
See also: ::::.
Also useful if you command uses ::: but you still want to read arguments from stdin (standard input): Simply change --arg-sep to a string that is not in the command line.
See also: :::.
See also: --fg
Implies --semaphore.
parallel tries to meet the block size but can be off by the length of one record.
size defaults to 1M.
See --pipe for use of this.
find log -name '*gz' | parallel \ --sshlogin server.example.com --transfer --return {.}.bz2 \ --cleanup "zcat {} | bzip -9 >{.}.bz2"
With --transfer the file transferred to the remote computer will be removed on the remote computer. Directories created will not be removed - even if they are empty.
With --return the file transferred from the remote computer will be removed on the remote computer. Directories created will not be removed - even if they are empty.
--cleanup is ignored when not used with --transfer or --return.
--colsep implies --trim rl.
regexp is a Perl Regular Expression: http://perldoc.perl.org/perlre.html
See also: --bg
Implies --semaphore.
To convert the times into ISO-8601 strict do:
perl -a -F"\t" -ne 'chomp($F[2]=`date -d \@$F[2] +%FT%T`); print join("\t",@F)'
If --semaphore is set default is 1 thus making a mutex.
parallel -j4 sleep {}\; echo {} ::: 2 1 4 3 parallel -j4 -k sleep {}\; echo {} ::: 2 1 4 3
-L 0 means read one line, but insert 0 arguments on the command line.
Implies -X unless -m is set.
-l 0 is an alias for -l 1.
Implies -X unless -m is set.
The load average is only sampled every 10 seconds to avoid stressing small computers.
Support for -m with --sshlogin is limited and may fail.
See also -X for context replace. If in doubt use -X as that will most likely do what is needed.
The block size is determined by --block. The strings --recstart and --recend tell parallel how a record starts and/or ends. The block read will have the final partial record removed before the block is passed on to the job. The partial record will be prepended to next block.
If --recstart is given this will be used to split at record start.
If --recend is given this will be used to split at record end.
If both --recstart and --recend are given both will have to match to find a split position.
If neither --recstart nor --recend are given --recend defaults to '\n'. To have no record separator use --recend "".
--files is often used with --pipe.
By sending parallel SIGUSR2 you can toggle turning on/off --progress on a running parallel process.
-n 0 means read one argument, but insert 0 arguments on the command line.
Implies -X unless -m is set.
-N 0 means read one argument, but insert 0 arguments on the command line.
This will set the owner of the homedir to the user:
tr ':' '\012' < /etc/passwd | parallel -N7 chown {1} {6}
Implies -X unless -m or <--pipe> is set.
When used with --pipe -N is the number of records to read. This is much slower than --blocksize so avoid it if performance is important.
profilename corresponds to the file ~/.parallel/profilename.
Default: config
If --recend is given endstring will be used to split at record end.
If both --recstart and --recend are given the string startstringendstring will have to match to find a split position. This is useful if either startstring or endstring match in the middle of a record.
If neither --recstart nor --recend are given then --recend defaults to '\n'. To have no record separator use --recend "".
--recstart and --recend are used with --pipe.
Use --regexp to interpret --recstart and --recend as regular expressions. This is slow, however.
Only used with --pipe.
echo foo/bar.txt | parallel \ --sshlogin server.example.com --return {.}.out touch {.}.out
This will transfer the file $HOME/foo/bar.out from the computer server.example.com to the file foo/bar.out after running touch foo/bar.out on server.example.com.
echo /tmp/foo/bar.txt | parallel \ --sshlogin server.example.com --return {.}.out touch {.}.out
This will transfer the file /tmp/foo/bar.out from the computer server.example.com to the file /tmp/foo/bar.out after running touch /tmp/foo/bar.out on server.example.com.
Multiple files can be transferred by repeating the options multiple times:
echo /tmp/foo/bar.txt | \ parallel --sshlogin server.example.com \ --return {.}.out --return {.}.out2 touch {.}.out {.}.out2
--return is often used with --transfer and --cleanup.
--return is ignored when used with --sshlogin : or when not used with --sshlogin.
Implies -X unless -m is set.
--semaphore implies --bg unless --fg is specified.
--semaphore implies --semaphorename `tty` unless --semaphorename is specified.
Used with --fg, --wait, and --semaphorename.
The command sem is an alias for parallel --semaphore.
Implies --semaphore.
Implies --semaphore.
An sshlogin is of the form:
[sshcommand [options]][username@]hostname
The sshlogin must not require a password.
The sshlogin ':' is special, it means 'no ssh' and will therefore run on the local computer.
The sshlogin '..' is special, it read sshlogins from ~/.parallel/sshloginfile
To specify more sshlogins separate the sshlogins by comma or repeat the options multiple times.
For examples: see --sshloginfile.
The remote host must have parallel installed.
--sshlogin is known to cause problems with -m and -X.
--sshlogin is often used with --transfer, --return, --cleanup, and --trc.
server.example.com [email protected] 8/my-8-core-server.example.com 2/[email protected] # This server has SSH running on port 2222 ssh -p 2222 server.example.net 4/ssh -p 2222 quadserver.example.net # Use a different ssh program myssh -p 2222 -l myusername hexacpu.example.net # Use a different ssh program with default number of cores //usr/local/bin/myssh -p 2222 -l myusername hexacpu.example.net # Use a different ssh program with 6 cores 6//usr/local/bin/myssh -p 2222 -l myusername hexacpu.example.net # Assume 16 cores on the local computer 16/:
When using a different ssh program the last argument must be the hostname.
The sshloginfile '..' is special, it read sshlogins from ~/.parallel/sshloginfile
See also -v and -p.
echo foo/bar.txt | parallel \ --sshlogin server.example.com --transfer wc
This will transfer the file foo/bar.txt to the computer server.example.com to the file $HOME/foo/bar.txt before running wc foo/bar.txt on server.example.com.
echo /tmp/foo/bar.txt | parallel \ --sshlogin server.example.com --transfer wc
This will transfer the file foo/bar.txt to the computer server.example.com to the file /tmp/foo/bar.txt before running wc /tmp/foo/bar.txt on server.example.com.
--transfer is often used with --return and --cleanup.
--transfer is ignored when used with --sshlogin : or when not used with --sshlogin.
--transfer --return filename --cleanup
Use -v -v to print the wrapping ssh command when running remotely.
Implies --semaphore.
Normally -X will do the right thing, whereas -m can give unexpected results if {} is used as part of a word.
Support for -X with --sshlogin is limited and may fail.
See also -m.
Compare these two:
parallel echo {1} {2} ::: 1 2 3 ::: a b c parallel --xapply echo {1} {2} ::: 1 2 3 ::: a b c
#!/usr/bin/parallel -Yr traceroute
foss.org.my debian.org freenetproject.org
For this to work --shebang or -Y must be set as the first option.
parallel can work similar to xargs -n1.
To compress all html files using gzip run:
find . -name '*.html' | parallel gzip
If the file names may contain a newline use -0. Substitute FOO BAR with FUBAR in all files in this dir and subdirs:
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'.
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:
parallel gzip ::: *.html
To convert *.wav to *.mp3 using LAME running one process per CPU core run:
parallel lame {} -o {.}.mp3 ::: *.wav
When moving a lot of files like this: mv * destdir you will sometimes get the error:
bash: /bin/mv: Argument list too long
because there are too many files. You can instead do:
ls | 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:
ls | parallel -m mv {} destdir
To remove the files pict0000.jpg .. pict9999.jpg you could do:
seq -w 0 9999 | parallel rm pict{}.jpg
You could also do:
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:
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.
If ImageMagick is installed this will generate a thumbnail of a jpg file:
convert -geometry 120 foo.jpg thumb_foo.jpg
This will run with number-of-cpu-cores jobs in parallel for all jpg files in a directory:
ls *.jpg | parallel convert -geometry 120 {} thumb_{}
To do it recursively use find:
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:
find . -name '*.jpg' | parallel convert -geometry 120 {} {.}_thumb.jpg
This will generate an uncompressed version of .gz-files next to the .gz-file:
parallel zcat {} ">"{.} ::: *.gz
Quoting of > is necessary to postpone the redirection. Another solution is to quote the whole command:
parallel "zcat {} >{.}" ::: *.gz
Other special shell charaters (such as * ; $ > < | >> <<) also need to be put in quotes, as they may otherwise be interpreted by the shell and not given to parallel.
A job can consist of several commands. This will print the number of files in each directory:
ls | parallel 'echo -n {}" "; ls {}|wc -l'
To put the output in a file called <name>.dir:
ls | parallel '(echo -n {}" "; ls {}|wc -l) > {}.dir'
Even small shell scripts can be run by parallel:
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.
cat urlfile | parallel "wget {} 2>/dev/null || grep -n {} urlfile"
Create a mirror directory with the same filenames except all files and symlinks are empty files.
cp -rs /the/source/dir mirror_dir; find mirror_dir -type l | parallel -m rm {} '&&' touch {}
When processing files removing the file extension using {.} is often useful.
Create a directory for each zip-file and unzip it in that dir:
parallel 'mkdir {.}; cd {.}; unzip ../{}' ::: *.zip
Recompress all .gz files in current directory using bzip2 running 1 job per CPU core in parallel:
parallel "zcat {} | bzip2 >{.}.bz2 && rm {}" ::: *.gz
Convert all WAV files to MP3 using LAME:
find sounddir -type f -name '*.wav' | parallel lame {} -o {.}.mp3
Put all converted in the same directory:
find sounddir -type f -name '*.wav' | parallel lame {} -o mydir/{/.}.mp3
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:
ls *.tar.gz| parallel -U {tar} 'echo {tar}|parallel "mkdir -p {.} ; tar -C {.} -xf {.}.tar.gz"'
Let us assume a website stores images like:
http://www.example.com/path/to/YYYYMMDD_##.jpgwhere YYYYMMDD is the date and ## is the number 01-10. This will generate the past 30 days as YYYYMMDD:
seq 30 | parallel date -d '"today -{} days"' +%Y%m%d
Based on this we can let parallel generate 10 wgets per day:
the above | parallel -I {o} seq -w 10 "|" parallel wget http://www.example.com/path/to/{o}_{}.jpg
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.
tar xvf foo.tgz | perl -ne 'print $l;$l=$_;END{print $l}' | parallel echo
The Perl one-liner is needed to avoid race condition.
for-loops like this:
(for x in `cat list` ; do do_something $x done) | process_outputand while-read-loops like this:
cat list | (while read x ; do do_something $x done) | process_outputcan be written like this:
cat list | parallel do_something | process_output
If the processing requires more steps the for-loop like this:
(for x in `cat list` ; do no_extension=${x%.*}; do_something $x scale $no_extension.jpg do_step2 <$x $no_extension done) | process_outputand while-loops like this:
cat list | (while read x ; do no_extension=${x%.*}; do_something $x scale $no_extension.jpg do_step2 <$x $no_extension done) | process_outputcan be written like this:
cat list | parallel "do_something {} scale {.}.jpg ; do_step2 <{} {.}" | process_output
Nested for-loops like this:
(for x in `cat xlist` ; do for y in `cat ylist` ; do do_something $x $y done done) | process_outputcan be written like this:
cat xlist | parallel cat ylist \| parallel -I {o} do_something {} {o} | process_output
The above will run N*N jobs in parallel if parallel normally runs N jobs. To ensure the output order is the same as the input and only run N jobs do:
cat xlist | parallel -k cat ylist \| parallel -j1 -kI {o} do_something {} {o} | process_output
When running jobs that output data, you often do not want the output of multiple jobs to run together. parallel defaults to grouping the output of each job, so the output is printed when the job finishes. If you want the output to be printed while the job is running you can use -u.
Compare the output of:
parallel traceroute ::: foss.org.my debian.org freenetproject.org
to the output of:
parallel -u traceroute ::: foss.org.my debian.org freenetproject.org
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:
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:
parallel traceroute ::: foss.org.my debian.org freenetproject.org
will give traceroute of foss.org.my, 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:
parallel -k traceroute ::: foss.org.my debian.org freenetproject.org
This will make sure the traceroute to foss.org.my 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:
curl -r 10000000-19999999 http://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.
seq 0 99 | parallel -k curl -r \ {}0000000-{}9999999 http://example.com/the/big/file > file
grep -r greps recursively through directories. On multicore CPUs parallel can often speed this up.
find . -type f | parallel -k -j150% -n 1000 -m grep -H -n STRING {}
This will run 1.5 job per core, and give 1000 arguments to grep.
To grep a big file in parallel use --pipe:
cat bigfile | parallel --pipe grep foo
Depending on your disks and CPUs it may be faster to read larger blocks:
cat bigfile | parallel --pipe --block 10M grep foo
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 and ssh-agent may help you do that).
To run echo on server.example.com:
seq 10 | parallel --sshlogin server.example.com echoTo run commands on more than one remote computer run:
seq 10 | parallel --sshlogin server.example.com,server2.example.net echoOr:
seq 10 | parallel --sshlogin server.example.com \ --sshlogin server2.example.net echoIf the login username is foo on server2.example.net use:
seq 10 | parallel --sshlogin server.example.com \ --sshlogin [email protected] echoTo distribute the commands to a list of computers, make a file mycomputers with all the computers:
server.example.com [email protected] server3.example.comThen run:
seq 10 | parallel --sshloginfile mycomputers echoTo include the local computer add the special sshlogin ':' to the list:
server.example.com [email protected] server3.example.com :parallel will try to determine the number of CPU cores on each of the remote computers, and run one job per CPU core - even if the remote computers do not have the same number of CPU cores.
If the number of CPU cores on the remote computers is not identified correctly the number of CPU cores can be added in front. Here the computer has 8 CPU cores.
seq 10 | parallel --sshlogin 8/server.example.com echo
To recompress gzipped files with bzip2 using a remote computer run:
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:
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:
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:
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:
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:
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:
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:
find logs/ -name '*.gz' | parallel -S .. \ --trc {.}.bz2 "zcat {} | bzip2 -9 >{.}.bz2"
Convert *.mp3 to *.ogg running one process per CPU core on local computer and server2:
parallel --trc {.}.ogg -S server2,: \ 'mpg321 -w - {} | oggenc -q0 - -o {.}.ogg' ::: *.mp3
Copy files like foo.es.ext to foo.ext:
ls *.es.* | perl -pe 'print; s/\.es//' | parallel -N2 cp {1} {2}
The perl command spits out 2 lines for each input. parallel takes 2 inputs (using -N2) and replaces {1} and {2} with the inputs.
Print the number on the opposing sides of a six sided die:
parallel -a <(seq 6) -a <(seq 6 -1 1) echo
parallel 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):
parallel -a <(find . -type f | sort) -a <(seq $(find . -type f|wc -l)) convert {1} {2}.png
Alternative version:
find . -type f | sort | parallel convert {} \$PARALLEL_SEQ.png
Content of table_file.tsv:
foo<TAB>bar baz <TAB> quuxTo run:
cmd -o bar -i foo cmd -o quux -i bazyou can run:
parallel -a table_file.tsv --colsep '\t' cmd -o {2} -i {1}
Note: The default for parallel is to remove the spaces around the columns. To keep the spaces:
parallel -a table_file.tsv --trim n --colsep '\t' cmd -o {2} -i {1}
If you want to run the same command with the same arguments 10 times in parallel you can do:
seq 10 | parallel -n0 my_command my_args
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:
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=10.0.0.255To run 100 processes simultaneously do:
parallel -j 100 < jobs_to_run
As there is not a command the jobs will be evaluated by the shell.
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:
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 core. 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 parallel can put the output of each command into a file. This will sort a big file in parallel:
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.
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, 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:
for i in `ls *.log` ; do echo $i sem -j10 gzip $i ";" echo done done sem --waitA 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.
seq 3 | parallel sem sed -i -e 'i{}' myfileAs 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:
seq 3 | parallel sem --id mymutex sed -i -e 'i{}' myfile
You can use Parallel to start interactive programs like emacs or vi:
cat filelist | parallel -T -X emacs
cat filelist | parallel -T -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.
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:
parallel sudo echo ::: This is a bad ideais no good, as you would be prompted for the sudo password for each of the jobs. You can either do:
sudo echo This parallel sudo echo ::: is a good ideaor:
sudo parallel echo ::: This is a good ideaThis way you only have to enter the sudo password once.
parallel can work as a simple job queue system or batch manager. The idea is to put the jobs into a file and have parallel read from that continuously. As parallel will stop at end of file we use tail to continue reading:
echo >jobqueue; tail -f jobqueue | parallel
To submit your jobs to the queue:
echo my_command my_arg >> jobqueue
You can of course use -S to distribute the jobs to remote computers:
echo >jobqueue; tail -f jobqueue | parallel -S ..
There are a two small issues when using parallel as queue system/batch manager:
- You will get a warning if you do not submit JobSlots jobs within the first second. E.g. if you have 8 cores and use -j+2 you have to submit 10 jobs. These can be dummy jobs (e.g. echo foo). You can also simply ignore the warning.
- Jobs will be run immediately, but output from jobs will only be printed when JobSlots more jobs has been started. E.g. if you have 10 jobslots then the output from the first completed job will only be printed when job 11 is started.
If you have a dir in which users drop files that needs to be processed you can do this on /Linux (If you know what inotifywait is called on other platforms file a bug report):
inotifywait -q -m -r -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.
The -u is needed because of a small bug in parallel. If that proves to be a problem, file a bug report.
You can of course use -S to distribute the jobs to remote computers:
inotifywait -q -m -r -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.
parallel is very liberal in quoting. You only need to quote characters that have special meaning in shell:
( ) $ ` ' " < > ; | \
and depending on context these needs to be quoted, too:
* ~ & # ! ? space * {
Therefore most people will never need more quoting than putting '\' in front of the special characters.
However, when you want to use a shell variable you need to quote the $-sign. Here is an example using $PARALLEL_SEQ. This variable is set by parallel itself, so the evaluation of the $ must be done by the sub shell started by parallel:
seq 10 | parallel -N2 echo seq:\$PARALLEL_SEQ arg1:{1} arg2:{2}
If the variable is set before parallel starts you can do this:
VAR=this_is_set_before_starting
echo test | parallel echo {} $VAR
Prints: test this_is_set_before_starting
It is a little more tricky if the variable contains more than one space in a row:
VAR="two spaces between each word"
echo test | parallel echo {} \'"$VAR"\'
Prints: test two spaces between each word
If the variable should not be evaluated by the shell starting parallel but be evaluated by the sub shell started by parallel, then you need to quote it:
echo test | parallel VAR=this_is_set_after_starting \; echo {} \$VAR
Prints: test this_is_set_after_starting
It is a little more tricky if the variable contains space:
echo test | parallel VAR='"two spaces between each word"' echo {} \'"$VAR"\'
Prints: test two spaces between each word
$$ is the shell variable containing the process id of the shell. This will print the process id of the shell running parallel:
seq 10 | parallel echo $$
And this will print the process ids of the sub shells started by parallel.
seq 10 | parallel echo \$\$
If the special characters should not be evaluated by the sub shell then you need to protect it against evaluation from both the shell starting parallel and the sub shell:
echo test | parallel echo {} \\\$VAR
Prints: test $VAR
parallel can protect against evaluation by the sub shell by using -q:
echo test | parallel -q echo {} \$VAR
Prints: test $VAR
This is particularly useful if you have lots of quoting. If you want to run a perl script like this:
perl -ne '/^\S+\s+\S+$/ and print $ARGV,"\n"' file
It needs to be quoted like this:
ls | parallel perl -ne '/^\\S+\\s+\\S+\$/\ and\ print\ \$ARGV,\"\\n\"'
Notice how spaces, \'s, "'s, and $'s need to be quoted. parallel can do the quoting by using option -q:
ls | parallel -q perl -ne '/^\S+\s+\S+$/ and print $ARGV,"\n"'
However, this means you cannot make the sub shell interpret special characters. For example because of -q this WILL NOT WORK:
ls *.gz | parallel -q "zcat {} >{.}"
ls *.gz | parallel -q "zcat {} | bzip2 >{.}.bz2"
because > and | need to be interpreted by the sub shell.
If you get errors like:
sh: -c: line 0: syntax error near unexpected token sh: Syntax error: Unterminated quoted string sh: -c: line 0: unexpected EOF while looking for matching `'' sh: -c: line 1: syntax error: unexpected end of file
then you might try using -q.
If you are using bash process substitution like <(cat foo) then you may try -q and prepending command with bash -c:
ls | parallel -q bash -c 'wc -c <(echo {})'
Or for substituting output:
ls | parallel -q bash -c 'tar c {} | tee >(gzip >{}.tar.gz) | bzip2 >{}.tar.bz2'
Conclusion: To avoid dealing with the quoting problems it may be easier just to write a small script and have parallel call that script.
If you want a list of the jobs currently running you can run:
killall -USR1 parallel
parallel will then print the currently running jobs on STDERR.
If you regret starting a lot of jobs you can simply break parallel, but if you want to make sure you do not have halfcompleted jobs you should send the signal SIGTERM to parallel:
killall -TERM parallel
This will tell parallel to not start any new jobs, but wait until the currently running jobs are finished before exiting.
Example: If each of the jobs tests a solution and one of jobs finds the solution the job can tell parallel not to start more jobs by: kill -TERM $PARALLEL_PID. This only works on the local computer.
Example:
seq 10 | parallel -N2 echo seq:'$'PARALLEL_SEQ arg1:{1} arg2:{2}
Example:
cat list | parallel -j1 -k -v ls
can be written as:
cat list | PARALLEL="-kvj1" parallel ls
cat list | parallel -j1 -k -v -S"myssh user@server" ls
can be written as:
cat list | PARALLEL='-kvj1 -S myssh\ user@server' parallel echo
Notice the \ in the middle is needed because 'myssh' and 'user@server' must be one argument.
The file ~/.parallel/config (formerly known as .parallelrc) will be read if it exists. Lines starting with '#' will be ignored. It can be formatted like the environment variable $PARALLEL, but it is often easier to simply put each option on its own line.
Options on the command line takes precedence over the environment variable $PARALLEL which takes precedence over the file ~/.parallel/config.
If --profile set, parallel will read the profile from that file instead of ~/.parallel/config.
Example: Profile for running every command with -j-1 and nice
echo -j-1 nice > ~/.parallel/nice_profile parallel -J nice_profile bzip2 -9 ::: *
Example: Profile for running a perl script before every command:
echo "perl -e '\$a=\$\$; print \$a,\" \",'\$PARALLEL_SEQ',\" \";';" > ~/.parallel/pre_perl parallel -J pre_perl echo ::: *
Note how the $ and " need to be quoted using \.
Example: Profile for running distributed jobs with nice on the remote computers:
echo -S .. nice > ~/.parallel/dist parallel -J dist --trc {.}.bz2 bzip2 -9 ::: *
If --halt-on-error 0 or not specified:
Some of the jobs failed. The exit status gives the number of failed jobs
If --halt-on-error 1 or 2: Exit status of the failing job.
Because of the way newline is quoted this will not work:
echo 1,2,3 | parallel -vkd, "echo 'a{}b'"
However, these will all work:
echo 1,2,3 | parallel -vkd, echo a{}b
echo 1,2,3 | parallel -vkd, "echo 'a'{}'b'"
echo 1,2,3 | parallel -vkd, "echo 'a'"{}"'b'"
parallel is slow at starting up. Half of the startup time on the local computer is spent finding the maximal length of a command line. Setting -s will remove this part of the startup time.
When using multiple computers parallel opens ssh connections to them to figure out how many connections can be used reliably simultaneously (Namely SSHD's MaxStartup). This test is done for each host in serial, so if your --sshloginfile contains many hosts it may be slow.
The current implementation of --nice is too pessimistic in the max allowed command length. It only uses a little more than half of what it could. This affects -X and -m. If this becomes a real problem for you file a bug-report.
If you get:
Can't exec "command": No such file or directory
or:
open3: exec of by command failed
it may be because command is not known, but it could also be because command is an alias or a function. parallel will never support running aliases and functions (see why http://www.perlmonks.org/index.pl?node_id=484296), so change your alias or function to a script.
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Nov 08, 2018 | www.gnu.org
Welcome to the web page of the pexec program!
The main purpose of the program pexec is to execute the given command or shell script (e.g. parsed by /bin/sh ) in parallel on the local host or on remote hosts, while some of the execution parameters, namely the redirected standard input, output or error and environmental variables can be varied. This program is therefore capable to replace the classic shell loop iterators (e.g. for ~ in ~ done , in bash ) by executing the body of the loop in parallel. Thus, the program pexec implements shell level data parallelism in a barely simple form. The capabilities of the program is extended with additional features, such as allowing to define mutual exclusions, do atomic command executions and implement higher level resource and job control. See the complete manual for more details. See a brief Hungarian description of the program here .
The actual version of the program package is 1.0rc8 .
You may browse the package directory here (for FTP access, see this directory ). See the GNU summary page of this project here . The latest version of the program source package is pexec-1.0rc8.tar.gz . Here is another mirror of the package directory.
Please consider making donations to the author (via PayPal ) in order to help further development of the program or support the GNU project via the FSF .
Sep 02, 2015 | www.codeword.xyz
Wednesday, September 02, 2015 | 9 CommentsI was recently troubleshooting some issues we were having with Shippable , trying to get a bunch of our unit tests to run in parallel so that our builds would complete faster. I didn't care what order the different processes completed in, but I didn't want the shell script to exit until all the spawned unit test processes had exited. I ultimately wasn't able to satisfactorily solve the issue we were having, but I did learn more than I ever wanted to know about how to run processes in parallel in shell scripts. So here I shall impart unto you the knowledge I have gained. I hope someone else finds it useful!
Wait
The simplest way to achieve what I wanted was to use the
wait
command. You simply fork all of your processes with&
, and then follow them with await
command. Behold:#!/bin/sh /usr/bin/my-process-1 --args1 & /usr/bin/my-process-2 --args2 & /usr/bin/my-process-3 --args3 & wait echo all processes completeIt's really as easy as that. When you run the script, all three processes will be forked in parallel, and the script will wait until all three have completed before exiting. Anything after the
wait
command will execute only after the three forked processes have exited.Pros
Damn, son! It doesn't get any simpler than that!
Cons
I don't think there's really any way to determine the exit codes of the processes you forked. That was a deal-breaker for my use case, since I needed to know if any of the tests failed and return an error code from the parent shell script if they did.
Another downside is that output from the processes will be all mish-mashed together, which makes it difficult to follow. In our situation, it was basically impossible to determine which unit tests had failed because they were all spewing their output at the same time.
GNU Parallel
There is a super nifty program called GNU Parallel that does exactly what I wanted. It works kind of like
xargs
in that you can give it a collection of arguments to pass to a single command which will all be run, only this will run them in parallel instead of in serial likexargs
does (OR DOES IT??</foreshadowing>). It is super powerful, and all the different ways you can use it are beyond the scope of this article, but here's a rough equivalent to the example script above:#!/bin/sh parallel /usr/bin/my-process-{} --args{} ::: 1 2 3 echo all processes completeThe official "10 seconds installation" method for the latest version of GNU Parallel (from the README) is as follows:
(wget -O - pi.dk/3 || curl pi.dk/3/ || fetch -o - http://pi.dk/3) | bashPros
If any of the processes returns a non-zero exit code,
parallel
will return a non-zero exit code. This means you can use$?
in your shell script to detect if any of the processes failed. Nice! GNU Parallel also (by default) collates the output of each process together, so you'll see the complete output of each process as it completes instead of a mash-up of all the output combined together as it's produced. Also nice!I am such a damn fanboy I might even buy an official GNU Parallel mug and t-shirt . Actually I'll probably save the money and get the new Star Wars Battlefront game when it comes out instead. But I did seriously consider the
parallel
schwag for a microsecond or so.Cons
Literally none.
Xargs
So it turns out that our old friend
xargs
has supported parallel processing all along! Who knew? It's like the nerdy chick in the movies who gets a makeover near the end and it turns out she's even hotter than the stereotypical hot cheerleader chicks who were picking on her the whole time. Just pass it a-Pn
argument and it will run your commands using up ton
threads. Check out this mega-sexy equivalent to the above scripts:#!/bin/sh printf "1\n2\n3" | xargs -n1 -P3 -I{} /usr/bin/my-process-{} --args{} echo all processes completePros
xargs
returns a non-zero exit code if any of the processes fails, so you can again use$?
in your shell script to detect errors. The difference is it will return123
, unlike GNU Parallel which passes through the non-zero exit code of the process that failed (I'm not sure howparallel
picks if more than one process fails, but I'd assume it's either the first or last process to fail). Another pro is thatxargs
is most likely already installed on your preferred distribution of Linux.Cons
I have read reports that the non-GNU version of
xargs
does not support parallel processing, so you may or may not be out of luck with this option if you're on AIX or a BSD or something.
xargs
also has the same problem as thewait
solution where the output from your processes will be all mixed together.Another con is that
xargs
is a little less flexible thanparallel
in how you specify the processes to run. You have to pipe your values into it, and if you use the-I
argument for string-replacement then your values have to be separated by newlines (which is more annoying when running it ad-hoc). It's still pretty nice, but nowhere near as flexible or powerful asparallel
.Also there's no place to buy an
xargs
mug and t-shirt. Lame!And The Winner Is
After determining that the Shippable problem we were having was completely unrelated to the parallel scripting method I was using, I ended up sticking with
parallel
for my unit tests. Even though it meant one more dependency on our build machine, the ease
Jun 23, 2018 | stackoverflow.com
Gnats ,Jul 23, 2010 at 19:33
I'm trying to use xargs in a shell script to run parallel instances of a function I've defined in the same script. The function times the fetching of a page, and so it's important that the pages are actually fetched concurrently in parallel processes, and not in background processes (if my understanding of this is wrong and there's negligible difference between the two, just let me know).The function is:
function time_a_url () { oneurltime=$($time_command -p wget -p $1 -O /dev/null 2>&1 1>/dev/null | grep real | cut -d" " -f2) echo "Fetching $1 took $oneurltime seconds." }How does one do this with an xargs pipe in a form that can take number of times to run time_a_url in parallel as an argument? And yes, I know about GNU parallel, I just don't have the privilege to install software where I'm writing this.
Dennis Williamson ,Jul 23, 2010 at 23:03
Here's a demo of how you might be able to get your function to work:$ f() { echo "[$@]"; } $ export -f f $ echo -e "b 1\nc 2\nd 3 4" | xargs -P 0 -n 1 -I{} bash -c f\ \{\} [b 1] [d 3 4] [c 2]The keys to making this work are to
export
the function so thebash
thatxargs
spawns will see it and to escape the space between the function name and the escaped braces. You should be able to adapt this to work in your situation. You'll need to adjust the arguments for-P
and-n
(or remove them) to suit your needs.You can probably get rid of the
grep
andcut
. If you're using the Bash builtintime
, you can specify an output format using theTIMEFORMAT
variable. If you're using GNU/usr/bin/time
, you can use the--format
argument. Either of these will allow you to drop the-p
also.You can replace this part of your
wget
command:2>&1 1>/dev/null
with-q
. In any case, you have those reversed. The correct order would be>/dev/null 2>&1
.Lee Netherton ,Aug 30, 2011 at 16:32
I usedxargs -P0 -n1 -I{} bash -c "f {}"
which still works, and seems a little tidier. – Lee Netherton Aug 30 '11 at 16:32tmpvar ,Jul 24, 2010 at 15:21
On Mac OS X:xargs: max. processes must be >0 (for: xargs -P [>0])
f() { echo "[$@]"; } export -f f echo -e "b 1\nc 2\nd 3 4" | sed 's/ /\\ /g' | xargs -P 10 -n 1 -I{} bash -c f\ \{\} echo -e "b 1\nc 2\nd 3 4" | xargs -P 10 -I '{}' bash -c 'f "$@"' arg0 '{}',
If you install GNU Parallel on another system, you will see the functionality is in a single file (called parallel).You should be able to simply copy that file to your own ~/bin.
Jun 02, 2018 | www.techrepublic.com
Scratching the surface
We've only just scratched the surface of GNU Parallel. I highly recommend you give the official GNU Parallel tutorial a read, and watch this video tutorial series on Yutube , so you can understand the complexities of the tool (of which there are many).
But this will get you started on a path to helping your data center Linux servers use commands with more efficiency.
EXAMPLE: Working as xargs -n1. Argument appendingGNU parallel can work similar to xargs -n1.
To compress all html files using gzip run:
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:
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: Reading arguments from command lineGNU 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:
parallel gzip --best ::: *.html
To convert *.wav to *.mp3 using LAME running one process per CPU core run:
EXAMPLE: Inserting multiple argumentsparallel lame {} -o {.}.mp3 ::: *.wav
When moving a lot of files like this: mv *.log destdir you will sometimes get the error:
bash: /bin/mv: Argument list too long
because there are too many files. You can instead do:
ls | grep -E '\.log$' | parallel mv {} destdir
This will run mv for each file. It can be done faster if mv gets as many arguments that will fit on the line:
ls | grep -E '\.log$' | parallel -m mv {} destdir
In many shells you can also use printf:
EXAMPLE: Context replaceprintf '%s\0' *.log | parallel -0 -m mv {} destdir
To remove the files pict0000.jpg .. pict9999.jpg you could do:
seq -w 0 9999 | parallel rm pict{}.jpg
You could also do:
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:
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 substitutionIf ImageMagick is installed this will generate a thumbnail of a jpg file:
convert -geometry 120 foo.jpg thumb_foo.jpg
This will run with number-of-cpu-cores jobs in parallel for all jpg files in a directory:
ls *.jpg | parallel convert -geometry 120 {} thumb_{}
To do it recursively use find:
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:
EXAMPLE: Substitution and redirectionfind . -name '*.jpg' | parallel convert -geometry 120 {} {.}_thumb.jpg
This will generate an uncompressed version of .gz-files next to the .gz-file:
parallel zcat {} ">"{.} ::: *.gz
Quoting of > is necessary to postpone the redirection. Another solution is to quote the whole command:
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 commandsA job can consist of several commands. This will print the number of files in each directory:
ls | parallel 'echo -n {}" "; ls {}|wc -l'
To put the output in a file called <name>.dir:
ls | parallel '(echo -n {}" "; ls {}|wc -l) >{}.dir'
Even small shell scripts can be run by GNU parallel:
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.
cat urlfile | parallel "wget {} 2>/dev/null || grep -n {} urlfile"
Create a mirror directory with the same filenames except all files and symlinks are empty files.
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
EXAMPLE: Composed command with multiple input sourcescat file_list | parallel 'if [ ! -e {} ] ; then echo {}; fi'
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:
EXAMPLE: Calling Bash functionsparallel [ -f {1}:{2} ] "||" echo {1}:{2} does not exist \ ::: {00..23} ::: {00..55..5}
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.
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 $2 } export -f doubleit parallel doubleit ::: 1 2 3 ::: a b
To do this on remote servers you need to transfer the function using --env:
parallel --env doit -S server doit ::: 1 2 3 parallel --env doubleit -S server doubleit ::: 1 2 3 ::: a b
If your environment (aliases, variables, and functions) is small you can copy the full environment without having to export -f anything. See env_parallel.
EXAMPLE: Function testerTo test a program with different parameters:
tester() { if (eval "$@") >&/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: Log rotateLog 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:
EXAMPLE: Removing file extension when processing filesseq 9 -1 1 | parallel -j1 mv log.{} log.'{= $_++ =}' mv log log.1
When processing files removing the file extension using {.} is often useful.
Create a directory for each zip-file and unzip it in that dir:
parallel 'mkdir {.}; cd {.}; unzip ../{}' ::: *.zip
Recompress all .gz files in current directory using bzip2 running 1 job per CPU core in parallel:
parallel "zcat {} | bzip2 >{.}.bz2 && rm {}" ::: *.gz
Convert all WAV files to MP3 using LAME:
find sounddir -type f -name '*.wav' | parallel lame {} -o {.}.mp3
Put all converted in the same directory:
EXAMPLE: Removing strings from the argumentfind sounddir -type f -name '*.wav' | \ parallel lame {} -o mydir/{/.}.mp3
If you have directory with tar.gz files and want these extracted in the corresponding dir (e.g foo.tar.gz will be extracted in the dir foo) you can do:
parallel --plus 'mkdir {..}; tar -C {..} -xf {}' ::: *.tar.gz
If you want to remove a different ending, you can use {%string}:
parallel --plus echo {%_demo} ::: mycode_demo keep_demo_here
You can also remove a starting string with {#string}
parallel --plus echo {#demo_} ::: demo_mycode keep_demo_here
To remove a string anywhere you can use regular expressions with {/regexp/replacement} and leave the replacement empty:
EXAMPLE: Download 24 images for each of the past 30 daysparallel --plus echo {/demo_/} ::: demo_mycode remove_demo_here
Let us assume a website stores images like:
http://www.example.com/path/to/YYYYMMDD_##.jpg
where YYYYMMDD is the date and ## is the number 01-24. This will download images for the past 30 days:
getit() { date=$(date -d "today -$1 days" +%Y%m%d) num=$2 echo wget http://www.example.com/path/to/${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 $1 days subtracted.
EXAMPLE: Download world map from NASANASA provides tiles to download on earthdata.nasa.gov. Download tiles for Blue Marble world map and create a 10240x20480 map.
EXAMPLE: Download Apollo-11 images from NASA using jqbase=https://map1a.vis.earthdata.nasa.gov/wmts-geo/wmts.cgi service="SERVICE=WMTS&REQUEST=GetTile&VERSION=1.0.0" layer="LAYER=BlueMarble_ShadedRelief_Bathymetry" set="STYLE=&TILEMATRIXSET=EPSG4326_500m&TILEMATRIX=5" tile="TILEROW={1}&TILECOL={2}" format="FORMAT=image%2Fjpeg" url="$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
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.
EXAMPLE: Copy files as last modified date (ISO8601) with added random digitsbase="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
find . | parallel cp {} '../destdir/{= $a=int(10000*rand); $_=pQ($_); $_=`date -r "$_" +%FT%T"$a"`; chomp; =}'
{= and =} mark a perl expression. pQ quotes the string. date +%FT%T is the date in ISO8601 with time.
EXAMPLE: Digtal 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 modudo 2 is 1: Use ":" otherwise use " ":
EXAMPLE: Aggregating content of filesparallel -k echo {1}'{=3 $_=$_%2?":":" "=}'{2}{3} \ ::: {0..12} ::: {0..5} ::: {0..9}
This:
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:
parallel eval 'cat {=s/y01/y*/=} > {=s/y01//=}' ::: *y01*
For all values of x and z it runs commands like:
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/mirrorerThis 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:
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.
EXAMPLE: Process files from a tar file while unpacking#!/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
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.
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-loopfor-loops like this:
(for x in `cat list` ; do do_something $x done) | process_output
and while-read-loops like this:
cat list | (while read x ; do do_something $x done) | process_output
can be written like this:
cat list | parallel do_something | process_output
For example: Find which host name in a list has IP address 1.2.3 4:
cat hosts.txt | parallel -P 100 host | grep 1.2.3.4
If the processing requires more steps the for-loop like this:
(for x in `cat list` ; do no_extension=${x%.*}; do_step1 $x scale $no_extension.jpg do_step2 <$x $no_extension done) | process_output
and while-loops like this:
cat list | (while read x ; do no_extension=${x%.*}; do_step1 $x scale $no_extension.jpg do_step2 <$x $no_extension done) | process_output
can be written like this:
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:
(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:
EXAMPLE: Rewriting nested for-loopsdoit() { x=$1 do_something $x [... 100 lines that do something with $x ...] } export -f doit cat list | parallel doit
Nested for-loops like this:
(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:
parallel do_something {1} {2} :::: xlist ylist | process_output
Nested for-loops like this:
(for colour in red green blue ; do for size in S M L XL XXL ; do echo $colour $size done done) | sort
can be written like this:
EXAMPLE: Finding the lowest difference between filesparallel echo {1} {2} ::: red green blue ::: S M L XL XXL | sort
diff is good for finding differences in text files. diff | wc -l gives an indication of the size of the difference. To find the differences between all files in the current dir do:
parallel --tag 'diff {1} {2} | wc -l' ::: * ::: * | sort -nk3
This way it is possible to see if some files are closer to other files.
EXAMPLE: for-loops with column namesWhen doing multiple nested for-loops it can be easier to keep track of the loop variable if is is named instead of just having a number. Use --header : to let the first argument be an named alias for the positional replacement string:
parallel --header : echo {colour} {size} \ ::: colour red green blue ::: size S M L XL XXL
This also works if the input file is a file with columns:
EXAMPLE: All combinations in a listcat addressbook.tsv | \ parallel --colsep '\t' --header : echo {Name} {E-mail address}
GNU parallel makes all combinations when given two lists.
To make all combinations in a single list with unique values, you repeat the list and use replacement string with a Perl expression that skips the job if the value from input source 1 is greater than or equal to the value from input source 2:
parallel echo {= 'if($arg[1] ge $arg[2]) { skip() }' =} ::: A B C D ::: A B C D
Or more generally:
EXAMPLE: From a to b and b to cparallel echo \ '{= for $t (2..$#arg){ if($arg[$t-1] ge $arg[$t]) { skip() } } =}' \ ::: A B C D ::: A B C D ::: A B C D
Assume you have input like:
aardvark babble cab dab each
and want to run combinations like:
aardvark babble babble cab cab dab dab each
If the input is in the file in.txt:
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:
EXAMPLE: Count the differences between all files in a dirseq $((${#a[@]}-1)) | env_parallel --env a echo '${a[{=$_--=}]} - ${a[{}]}' parallel echo {1} - {2} ::: "${a[@]::${#a[@]}-1}" :::+ "${a[@]:1}"
Using --results the results are saved in /tmp/diffcount*.
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 jobsStarting a job on the local machine takes around 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:
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 parallels:
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.
EXAMPLE: Using shell variablesWhen using shell variables you need to quote them correctly as they may otherwise be interpreted by the shell.
Notice the difference between:
ARR=("My brother's 12\" records are worth <\$\$\$>"'!' Foo Bar) parallel echo ::: ${ARR[@]} # This is probably not what you want
and:
ARR=("My brother's 12\" records are worth <\$\$\$>"'!' Foo Bar) parallel echo ::: "${ARR[@]}"
When using variables in the actual command that contains special characters (e.g. space) you can quote them using '"$VAR"' or using "'s and -q:
VAR="My brother's 12\" records are worth <\$\$\$>" parallel -q echo "$VAR" ::: '!' export VAR parallel echo '"$VAR"' ::: '!'
If $VAR does not contain ' then "'$VAR'" will also work (and does not need export):
VAR="My 12\" records are worth <\$\$\$>" parallel echo "'$VAR'" ::: '!'
If you use them in a function you just quote as you normally would do:
EXAMPLE: Group output linesVAR="My brother's 12\" records are worth <\$\$\$>" export VAR myfunc() { echo "$VAR" "$1"; } export -f myfunc parallel myfunc ::: '!'
When running jobs that output data, you often do not want the output of multiple jobs to run together. GNU parallel defaults to grouping the output of each job, so the output is printed when the job finishes. If you want full lines to be printed while the job is running you can use --line-buffer. If you want output to be printed as soon as possible you can use -u.
Compare the output of:
EXAMPLE: Tag output linesparallel wget --limit-rate=100k \ https://ftpmirror.gnu.org/parallel/parallel-20{}0822.tar.bz2 \ ::: {12..16} parallel --line-buffer wget --limit-rate=100k \ https://ftpmirror.gnu.org/parallel/parallel-20{}0822.tar.bz2 \ ::: {12..16} parallel -u wget --limit-rate=100k \ https://ftpmirror.gnu.org/parallel/parallel-20{}0822.tar.bz2 \ ::: {12..16}
GNU parallel groups the output lines, but it can be hard to see where the different jobs begin. --tag prepends the argument to make that more visible:
parallel --tag wget --limit-rate=100k \ https://ftpmirror.gnu.org/parallel/parallel-20{}0822.tar.bz2 \ ::: {12..16}
--tag works with --line-buffer but not with -u:
parallel --tag --line-buffer wget --limit-rate=100k \ https://ftpmirror.gnu.org/parallel/parallel-20{}0822.tar.bz2 \ ::: {12..16}
Check the uptime of the servers in ~/.parallel/sshloginfile:
EXAMPLE: Colorize outputparallel --tag -S .. --nonall uptime
Give each job a new color. Most terminals support ANSI colors with the escape code "\033[30;3Xm" where 0 <= X <= 7:
parallel --tagstring '\033[30;3{=$_=++$::color%8=}m' seq {} ::: {1..10} 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):
EXAMPLE: Keep order of output same as order of input... | perl -pe 's/\t//'
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:
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:
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:
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:
curl -r 10000000-19999999 http://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.
EXAMPLE: Parallel grepseq 0 99 | parallel -k curl -r \ {}0000000-{}9999999 http://example.com/the/big/file > file
grep -r greps recursively through directories. On multicore CPUs GNU parallel can often speed this up.
find . -type f | parallel -k -j150% -n 1000 -m grep -H -n STRING {}
This will run 1.5 job per core, and give 1000 arguments to grep.
EXAMPLE: Grepping n lines for m regular expressions.The simplest solution to grep a big file for a lot of regexps is:
grep -f regexps.txt bigfile
Or if the regexps are fixed strings:
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 regexs.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:
ID1 foo bar baz Identifier1 quux fubar ID2 foo bar baz Identifier2
then your regexps.txt can be converted from:
ID1.*Identifier1 ID2.*Identifier2
into:
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:
parallel --pipepart -a regexps.txt --block 1M grep -Ff - -n bigfile | sort -un | perl -pe 's/^\d+://'
The 1M should be your free memory divided by the number of cores and divided by 200 for grep -F and by 1000 for normal grep. On GNU/Linux you can do:
free=$(awk '/^((Swap)?Cached|MemFree|Buffers):/ { sum += $2 } END { print sum }' /proc/meminfo) percpu=$((free / 200 / $(parallel --number-of-cores)))k parallel --pipepart -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:
parallel --pipepart -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:
cat regexp.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 regexp.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:
parallel --pipepart --block 100M -a bigfile -k --compress \ grep -f regexp.txt
This will split bigfile into 100MB chunks and run grep on each of these chunks. To parallelize both reading of bigfile and regexp.txt combine the two using --fifo:
parallel --pipepart --block 100M -a bigfile --fifo cat regexp.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 computersTo 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:
# 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:
seq 10 | parallel --sshlogin server.example.com echo
To run commands on more than one remote computer run:
seq 10 | parallel --sshlogin server.example.com,server2.example.net echo
Or:
seq 10 | parallel --sshlogin server.example.com \ --sshlogin server2.example.net echo
If the login username is foo on server2.example.net use:
seq 10 | parallel --sshlogin server.example.com \ --sshlogin [email protected] echo
If your list of hosts is server1-88.example.net with login foo:
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:
server.example.com [email protected] server3.example.com
Then run:
seq 10 | parallel --sshloginfile mycomputers echo
To include the local computer add the special sshlogin ':' to the list:
server.example.com [email protected] server3.example.com :
GNU parallel will try to determine the number of CPU cores on each of the remote computers, and run one job per CPU core - even if the remote computers do not have the same number of CPU cores.
If the number of CPU cores on the remote computers is not identified correctly the number of CPU cores can be added in front. Here the computer has 8 CPU cores.
EXAMPLE: Transferring of filesseq 10 | parallel --sshlogin 8/server.example.com echo
To recompress gzipped files with bzip2 using a remote computer run:
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:
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:
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:
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:
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:
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:
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:
EXAMPLE: Distributing work to local and remote computersfind logs/ -name '*.gz' | parallel -S .. \ --trc {.}.bz2 "zcat {} | bzip2 -9 >{.}.bz2"
Convert *.mp3 to *.ogg running one process per CPU core on local computer and server2:
EXAMPLE: Running the same command on remote computersparallel --trc {.}.ogg -S server2,: \ 'mpg321 -w - {} | oggenc -q0 - -o {.}.ogg' ::: *.mp3
To run the command uptime on remote computers you can do:
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:
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: Using remote computers behind NAT wallIf 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:
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.
So instead put this in ~/.ssh/config:
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:
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:
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:
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:
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:
parallel --ssh 'torsocks ssh' -S izjafdceobowklhz.onion \ -S zfcdaeiojoklbwhz.onion,auclucjzobowklhi.onion echo ::: a b c
If not all hosts are accessible through TOR:
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: Parallelizing rsyncrsync is a great tool, but sometimes it will not fill up the available bandwidth. This is often a problem when copying several big files over high speed connections.
The following will start one rsync per big file in src-dir to dest-dir on the server fooserver:
cd src-dir; find . -type f -size +100000 | \ parallel -v ssh fooserver mkdir -p /dest-dir/{//}\; \ rsync -s -Havessh {} fooserver:/dest-dir/{}
The dirs created may end up with wrong permissions and smaller files are not being transferred. To fix those run rsync a final time:
rsync -Havessh src-dir/ fooserver:/dest-dir/
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:
EXAMPLE: Use multiple inputs in one commandseq -w 0 99 | parallel rsync -Havessh fooserver:src/*{}.png destdir/
Copy files like foo.es.ext to foo.ext:
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:
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:
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):
parallel --link -a <(find . -type f | sort) \ -a <(seq $(find . -type f|wc -l)) convert {1} {2}.png
Alternative version:
EXAMPLE: Use a table as inputfind . -type f | sort | parallel convert {} {#}.png
Content of table_file.tsv:
foo<TAB>bar baz <TAB> quux
To run:
cmd -o bar -i foo cmd -o quux -i baz
you can run:
parallel -a table_file.tsv --colsep '\t' cmd -o {2} -i {1}
Note: The default for GNU parallel is to remove the spaces around the columns. To keep the spaces:
EXAMPLE: Output to databaseparallel -a table_file.tsv --trim n --colsep '\t' cmd -o {2} -i {1}
GNU parallel can output to a database table and a CSV-file:
DBURL=csv:///%2Ftmp%2Fmy.csv DBTABLEURL=$DBURL/mytable parallel --sqlandworker $DBTABLEURL seq ::: {1..10}
It is rather slow and takes up a lot of CPU time because GNU parallel parses the whole CSV file for each update.
A better approach is to use an SQLite-base and then convert that to CSV:
DBURL=sqlite3:///%2Ftmp%2Fmy.sqlite DBTABLEURL=$DBURL/mytable parallel --sqlandworker $DBTABLEURL seq ::: {1..10} sql $DBURL '.headers on' '.mode csv' 'SELECT * FROM mytable;'
This takes around a second per job.
If you have access to a real database system, such as PostgreSQL, it is even faster:
DBURL=pg://user:pass@host/mydb DBTABLEURL=$DBURL/mytable parallel --sqlandworker $DBTABLEURL seq ::: {1..10} sql $DBURL "COPY (SELECT * FROM mytable) TO stdout DELIMITER ',' CSV HEADER;"
Or MySQL:
EXAMPLE: Output to CSV-file for RDBURL=mysql://user:pass@host/mydb DBTABLEURL=$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/\\\\/\\/g; s/\\t/\t/g; s/\\n/\n/g;' mytable.tsv
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:
EXAMPLE: Use XML as inputparallel --results my.csv seq ::: 10 20 30 R > mydf <- read.csv("my.csv"); > print(mydf[2,]) > write(as.character(mydf[2,c("Stdout")]),'')
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 2016 and download them using GNU parallel:
EXAMPLE: Run the same command 10 timeswget -O - http://arkiv.radio24syv.dk/audiopodcast/channel/4466232 | xpath -e "//ancestor::pubDate[contains(text(),'2016')]/../enclosure/@url" | parallel -u wget '{= s/ url="//; s/"//; =}'
If you want to run the same command with the same arguments 10 times in parallel you can do:
EXAMPLE: Working as cat | sh. Resource inexpensive jobs and evaluationseq 10 | parallel -n0 my_command my_args
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:
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:
parallel -j 100 < jobs_to_run
As there is not a command the jobs will be evaluated by the shell.
EXAMPLE: Processing a big file using more coresTo 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:
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 core. 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:
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:
EXAMPLE: Grouping input linesparallel --pipepart --block 100m -a bigfile --files sort |\ parallel -Xj1 sort -m {} ';' rm {} >bigfile.sort
When processing with --pipe you may have lines grouped by a value. Here is my.csv:
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 = $F[1]). Here we first make a 50 character random string, which we then use as the separator:
sep=`perl -e 'print map { ("a".."z","A".."Z")[rand(52)] } (1..50);'` cat my.csv | perl -ape '$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 workaroundIf 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 parallels then each of them can run 250 jobs. This will spawn up to 2500 jobs:
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):
EXAMPLE: Working as mutex and counting semaphorecat myinput |\ parallel --pipe -N 250 --round-robin -j250 parallel -j250 your_prg
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:
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.
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:
EXAMPLE: Mutex for a scriptseq 3 | parallel sem --id mymutex sed -i -e '1i{}' myfile
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:
#!/usr/bin/sem --shebang-wrap -u --id $0 --fg /bin/bash echo This will run sleep 5 echo exclusively
Here perl:
#!/usr/bin/sem --shebang-wrap -u --id $0 --fg /usr/bin/perl print "This will run "; sleep 5; print "exclusively\n";
Here python:
EXAMPLE: Start editor with filenames from stdin (standard input)#!/usr/local/bin/sem --shebang-wrap -u --id $0 --fg /usr/bin/python import time print "This will run "; time.sleep(5) print "exclusively";
You can use GNU parallel to start interactive programs like emacs or vi:
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 sudosudo 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:
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. You can either do:
sudo echo This parallel sudo echo ::: is a good idea
or:
sudo parallel echo ::: This is a good idea
This way you only have to enter the sudo password once.
EXAMPLE: GNU Parallel as queue system/batch managerGNU 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:
true >jobqueue; tail -n+0 -f jobqueue | parallel
To submit your jobs to the queue:
echo my_command my_arg >> jobqueue
You can of course use -S to distribute the jobs to remote computers:
true >jobqueue; tail -n+0 -f jobqueue | parallel -S ..
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:
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:
# 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.
There is a a small issue when using GNU parallel as queue system/batch manager: You have to submit JobSlot number of jobs before they will start, and after that you can submit one at a time, and job will start immediately if free slots are available. Output from the running or completed jobs are held back and will only be printed when JobSlots more jobs has been started (unless you use --ungroup or --line-buffer, in which case the output from the jobs are printed immediately). E.g. if you have 10 jobslots then the output from the first completed job will only be printed when job 11 has started, and the output of second completed job will only be printed when job 12 has started.
EXAMPLE: GNU Parallel as dir processorIf 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):
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:
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 packageIf you have downloaded source and tried compiling it, you may have seen:
$ ./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://gitlab.com/ole.tange/tangetools can tell which files a program tried to access. In this case we are interested in one of the last files:
QUOTING$ tracefile -un ./configure | tail | parallel -j0 apt-file search
GNU parallel is very liberal in quoting. You only need to quote characters that have special meaning in shell:
( ) $ ` ' " < > ; | \
and depending on context these needs to be quoted, too:
~ & # ! ? space * {
Therefore most people will never need more quoting than putting '\' in front of the special characters.
Often you can simply put \' around every ':
perl -ne '/^\S+\s+\S+$/ and print $ARGV,"\n"' file
can be quoted:
parallel perl -ne \''/^\S+\s+\S+$/ and print $ARGV,"\n"'\' ::: file
However, when you want to use a shell variable you need to quote the $-sign. Here is an example using $PARALLEL_SEQ. This variable is set by GNU parallel itself, so the evaluation of the $ must be done by the sub shell started by GNU parallel:
seq 10 | parallel -N2 echo seq:\$PARALLEL_SEQ arg1:{1} arg2:{2}
If the variable is set before GNU parallel starts you can do this:
VAR=this_is_set_before_starting echo test | parallel echo {} $VAR
Prints: test this_is_set_before_starting
It is a little more tricky if the variable contains more than one space in a row:
VAR="two spaces between each word" echo test | parallel echo {} \'"$VAR"\'
Prints: test two spaces between each word
If the variable should not be evaluated by the shell starting GNU parallel but be evaluated by the sub shell started by GNU parallel, then you need to quote it:
echo test | parallel VAR=this_is_set_after_starting \; echo {} \$VAR
Prints: test this_is_set_after_starting
It is a little more tricky if the variable contains space:
echo test |\ parallel VAR='"two spaces between each word"' echo {} \'"$VAR"\'
Prints: test two spaces between each word
$$ is the shell variable containing the process id of the shell. This will print the process id of the shell running GNU parallel:
seq 10 | parallel echo $$
And this will print the process ids of the sub shells started by GNU parallel.
seq 10 | parallel echo \$\$
If the special characters should not be evaluated by the sub shell then you need to protect it against evaluation from both the shell starting GNU parallel and the sub shell:
echo test | parallel echo {} \\\$VAR
Prints: test $VAR
GNU parallel can protect against evaluation by the sub shell by using -q:
echo test | parallel -q echo {} \$VAR
Prints: test $VAR
This is particularly useful if you have lots of quoting. If you want to run a perl script like this:
perl -ne '/^\S+\s+\S+$/ and print $ARGV,"\n"' file
It needs to be quoted like one of these:
ls | parallel perl -ne '/^\\S+\\s+\\S+\$/\ and\ print\ \$ARGV,\"\\n\"' ls | parallel perl -ne \''/^\S+\s+\S+$/ and print $ARGV,"\n"'\'
Notice how spaces, \'s, "'s, and $'s need to be quoted. GNU parallel can do the quoting by using option -q:
ls | parallel -q perl -ne '/^\S+\s+\S+$/ and print $ARGV,"\n"'
However, this means you cannot make the sub shell interpret special characters. For example because of -q this WILL NOT WORK:
ls *.gz | parallel -q "zcat {} >{.}" ls *.gz | parallel -q "zcat {} | bzip2 >{.}.bz2"
because > and | need to be interpreted by the sub shell.
If you get errors like:
sh: -c: line 0: syntax error near unexpected token sh: Syntax error: Unterminated quoted string sh: -c: line 0: unexpected EOF while looking for matching `'' sh: -c: line 1: syntax error: unexpected end of file zsh:1: no matches found:
then you might try using -q.
If you are using bash process substitution like <(cat foo) then you may try -q and prepending command with bash -c:
ls | parallel -q bash -c 'wc -c <(echo {})'
Or for substituting output:
ls | parallel -q bash -c \ 'tar c {} | tee >(gzip >{}.tar.gz) | bzip2 >{}.tar.bz2'
Conclusion: To avoid dealing with the quoting problems it may be easier just to write a small script or a function (remember to export -f the function) and have GNU parallel call that.
LIST RUNNING JOBSIf you want a list of the jobs currently running you can run:
killall -USR1 parallel
GNU parallel will then print the currently running jobs on stderr (standard error).
COMPLETE RUNNING JOBS BUT DO NOT START NEW JOBSIf you regret starting a lot of jobs you can simply break GNU parallel, but if you want to make sure you do not have half-completed jobs you should send the signal SIGTERM to GNU parallel:
killall -TERM parallel
This will tell GNU parallel to not start any new jobs, but wait until the currently running jobs are finished before exiting.
ENVIRONMENT VARIABLESDEFAULT PROFILE (CONFIG FILE)
- $PARALLEL_HOME
- Dir where GNU parallel stores config files, semaphores, and caches information between invocations. Default: $HOME/.parallel.
- $PARALLEL_PID
- The environment variable $PARALLEL_PID is set by GNU parallel and is visible to the jobs started from GNU parallel. This makes it possible for the jobs to communicate directly to GNU parallel. Remember to quote the $, so it gets evaluated by the correct shell.
Example: If each of the jobs tests a solution and one of jobs finds the solution the job can tell GNU parallel not to start more jobs by: kill -TERM $PARALLEL_PID. This only works on the local computer.
- $PARALLEL_RSYNC_OPTS
- Options to pass on to rsync. Defaults to: -rlDzR.
- $PARALLEL_SHELL
- Use this shell for the commands run by GNU Parallel:
- $PARALLEL_SHELL. If undefined use:
- The shell that started GNU Parallel. If that cannot be determined:
- $SHELL. If undefined use:
- /bin/sh
- $PARALLEL_SSH
- GNU parallel defaults to using ssh for remote access. This can be overridden with $PARALLEL_SSH, which again can be overridden with --ssh. It can also be set on a per server basis (see --sshlogin).
- $PARALLEL_SEQ
- $PARALLEL_SEQ will be set to the sequence number of the job running. Remember to quote the $, so it gets evaluated by the correct shell.
Example:
seq 10 | parallel -N2 \ echo seq:'$'PARALLEL_SEQ arg1:{1} arg2:{2}
- $PARALLEL_TMUX
- Path to tmux. If unset the tmux in $PATH is used.
- $TMPDIR
- Directory for temporary files. See: --tmpdir.
- $PARALLEL
- The environment variable $PARALLEL will be used as default options for GNU parallel. If the variable contains special shell characters (e.g. $, *, or space) then these need to be to be escaped with \.
Example:
cat list | parallel -j1 -k -v ls cat list | parallel -j1 -k -v -S"myssh user@server" ls
can be written as:
cat list | PARALLEL="-kvj1" parallel ls cat list | PARALLEL='-kvj1 -S myssh\ user@server' \ parallel echo
Notice the \ in the middle is needed because 'myssh' and 'user@server' must be one argument.
The global configuration file /etc/parallel/config, followed by user configuration file ~/.parallel/config (formerly known as .parallelrc) will be read in turn if they exist. Lines starting with '#' will be ignored. The format can follow that of the environment variable $PARALLEL, but it is often easier to simply put each option on its own line.
Options on the command line take precedence, followed by the environment variable $PARALLEL, user configuration file ~/.parallel/config, and finally the global configuration file /etc/parallel/config.
Note that no file that is read for options, nor the environment variable $PARALLEL, may contain retired options such as --tollef.
PROFILE FILESIf --profile set, GNU parallel will read the profile from that file rather than the global or user configuration files. You can have multiple --profiles.
Example: Profile for running a command on every sshlogin in ~/.ssh/sshlogins and prepend the output with the sshlogin:
echo --tag -S .. --nonall > ~/.parallel/n parallel -Jn uptime
Example: Profile for running every command with -j-1 and nice
echo -j-1 nice > ~/.parallel/nice_profile parallel -J nice_profile bzip2 -9 ::: *
Example: Profile for running a perl script before every command:
echo "perl -e '\$a=\$\$; print \$a,\" \",'\$PARALLEL_SEQ',\" \";';" \ > ~/.parallel/pre_perl parallel -J pre_perl echo ::: *
Note how the $ and " need to be quoted using \.
Example: Profile for running distributed jobs with nice on the remote computers:
echo -S .. nice > ~/.parallel/dist parallel -J dist --trc {.}.bz2 bzip2 -9 ::: *
login: VOL. 36, NO. 1
... ... ...
Your First Parallel Job
GNU Parallel is available as a package for most UNIX distributions.See http:// www.gnu.org/s/parallel if it is not obvious how to install it on your system.After installation find a bunch of files on your computer and gzip them in parallel:
parallel gzip ::: *
Here your shell expands * to the files, ::: tells GNU Parallel to read arguments from the command line, and gzip is the command to run.The jobs are then run in parallel.After you have gziped the files, you can recompress them with bzip2:
parallel "zcat {} | bzip2 >{.}.bz2" ::: *
Here {} is being replaced with the file name.The output from zcat is piped to bzip2, which then compresses the output.The {.} is the file name with its extension stripped (e.g., foo.gz becomes foo), so the output from file.gz is stored in file.bz2.
GNU Parallel tries to be very liberal in quoting, so the above could also be written:
parallel zcat {} "|" bzip2 ">"{.}.bz2 ::: *
Only the chars that have special meaning in shell need to be quoted.
Reading Input
As we have seen, input can be given on the command line.Input can also be piped into GNU Parallel:
find . -type f | parallel gzip
GNU Parallel uses newline as a record separator and deals correctly with file names containing a word space or a dot.If you have normal users on your system, you will have experienced file names like these.If your users are really mean and write file names containing newlines, you can use NULL as a record separator:
find . -type f -print0 | parallel -0 gzip
You can read from a file using -a:
parallel -a filelist gzip
If you use more than one -a, a line from each input file will be available as {#}:
parallel -a sourcelist -a destlist gzip {1} ">"{2}
The same goes if you read a specific number of arguments at a time using -N:
cat filelist | parallel -N 3 diff {1} {2} ">" {3}
If your input is in columns you can split the columns using --colsep:
cat filelist.tsv | parallel --colsep '\t' diff {1} {2} ">" {3}
--colsep is a regexp, so you can match more advanced column separators.
Building the Command to Run
Just like xargs, GNU Parallel can take multiple input lines and put those on the same line.Compare these:
ls *.gz | parallel mv {} archive
ls *.gz | parallel -X mv {} archive
The first will run mv for every .gz file, whereas the second will fit as many files into {} as possible before running.
The {} can be put anywhere in the command, but if it is part of a word, that word will be repeated when using -X:
(echo 1; echo 2) | parallel -X echo foo bar{}baz quux
will repeat bar-baz and print:
foo bar1baz bar2baz quux
If you do not give a command to run, GNU Parallel will assume the input lines are command lines and run those in parallel:
(echo ls; echo grep root /etc/passwd) | parallel
;login: FEBRUARY 2011 GNU Parallel: The Command-Line Power Tool 4344 ;login: VOL. 36, NO. 1
Controlling the Output
One of the problems with running jobs in parallel is making sure the output of the running commands do not get mixed up.traceroute is a good example of this as it prints out slowly and parallel traceroutes will get mixed up.Try:
traceroute foss.org.my & traceroute debian.org & traceroute freenetproject.org & wait
and compare the output to:
parallel traceroute ::: foss.org.my debian.org freenetproject.org
As you can see, GNU Parallel only prints out when a job is done-thereby making sure the output is never mixed with other jobs.If you insist, GNU Parallel can give you the output immediately with -u, but output from different jobs may mix.
For some input, you want the output to come in the same order as the input.-k does that for you:
parallel -k echo {}';' sleep {} ::: 3 2 1 4
This will run the four commands in parallel, but postpone the output of the two middle commands until the first is finished.
Execution of the Jobs
GNU Parallel defaults to run one job per CPU core in parallel.You can change this with -j.You can put an integer as the number of jobs (e.g., -j 4 for four jobs in parallel) or you can put a percentage of the number of CPU cores (e.g., -j 200% to run two jobs per CPU core):
parallel -j200% gzip ::: *
If you pass -j a file name, the parameter will be read from that file:
parallel -j /tmp/number_of_jobs_to_run gzip ::: *
The file will be read again after each job finishes.This way you can change the number of jobs running during a parallel run.This is particularly useful if it is a very long run and you need to prioritize other tasks on the computer.
To list the currently running jobs you need to send GNU Parallel SIGUSR1:
killall -USR1 parallel
GNU Parallel will then print the currently running jobs on STDERR.
If you regret starting a lot of jobs, you can simply break GNU Parallel, but if you want to make sure you do not have half-completed jobs, you should send the signal SIGTERM to GNU Parallel:
killall -TERM parallel
This will tell GNU Parallel not to start any new jobs but to wait until the currently running jobs are finished before exiting.
When monitoring the progress on screen it is often nice to have the output prepended with the command that was run.-v will do that for you:
parallel -v gzip ::: *
If you want to monitor the progress as it goes you can also use --progress and --eta:
parallel --progress gzip ::: *
parallel --eta gzip ::: *
This is especially useful for debugging when jobs run on remote computers.
Remote Computers
GNU Parallel can use the CPU power of remote computers to help do computations. As an example, we will recompress .gz files into .bz2 files, but you can just as easily do other compute-intensive jobs such as video encoding or image transformation.
You will need to be able to log in to the remote host using ssh without entering a password (ssh-agent may be handy for that).To transfer files, rsync needs to be installed, and to help GNU Parallel figure out how many CPU cores each computer has, GNU Parallel should also be installed on the remote computers.
Try this simple example to see that your setup is working:
parallel --sshlogin yourserver.example.com hostname';' echo {} ::: 1 2 3This should print out the hostname of your server three times, each followed by the numbers 1 2 3.--sshlogin can be shortened to -S. To use more than one server, do:
parallel -S yourserver.example.com,server2.example.net hostname';' echo {} ::: 1 2 3If you have a different login name, just prepend login@ to the server name-just as you would with ssh.You can also give more than one -S instead of using a comma:
parallel -S yourserver.example.com -S [email protected] hostname';' echo {} ::: 1 2 3The special sshlogin ':' is your local computer:
parallel -S yourserver.example.com -S [email protected] -S : hostname';' echo {} ::: 1 2 3In this case you may see that GNU Parallel runs all three jobs on your local computer ,because the jobs are so fast to run.
If you have a file containing a list of the sshlogins to use, you can tell GNU Parallel to use that file:
parallel --sshloginfile mylistofsshlogins hostname';' echo {} ::: 1 2 3The special sshlogin ..will read the sshloginfile ~/.parallel/sshloginfile:
parallel -S .. hostname';' echo {} ::: 1 2 3Transferring Files
If your servers are not sharing storage (using NFS or something similar), you often need to transfer the files to be processed to the remote computers and the results back to the local computer.
To transfer a file to a remote computer, you will use --transfer:
parallel -S .. --transfer gzip '< {} | wc -c' ::: *.txt;login: FEBRUARY 2011 GNU Parallel: The Command-Line Power Tool 4546 ;login: VOL. 36, NO. 1
Here we transfer each of the .txt files to the remote servers, compress them, and count how many bytes they now take up.
After a transfer you often will want to remove the transferred file from the remote computers.--cleanup does that for you:
parallel -S .. --transfer --cleanup gzip '< {} | wc -c' ::: *.txtWhen processing files the result is often a file that you want copied back, after which the transferred and the result file should be removed from the remote computers:
parallel -S .. --transfer --return {.}.bz2 --cleanup zcat '< {} | bzip2 >{.}.bz2' ::: *.gzHere the .gz files will be transferred and then recompressed using zcat and bzip2.The resulting .bz2 file is transferred back, and the .gz and the .bz2 files are removed from the remote computers.The combination --transfer --cleanup --return foo is used so often that it has its own abbreviation: --trc foo.
You can specify multiple --trc if your command generates multiple result files.
GNU Parallel will try to detect the number of cores on remote computers and run one job per CPU core even if the computers have different number of CPU cores:
parallel -S .. --trc {.}.bz2 zcat '< {} | bzip2 >{.}.bz2' ::: *.gzGNU Parallel as Part of a Script
The more you practice using GNU Parallel, the more places you will see it can be useful.Every time you write a for loop or a while-read loop, consider if this could be done in parallel.Often the for loop can completely be replaced with a single line using GNU Parallel; if the jobs you want to run in parallel are very complex, you may want to make a script and have GNU Parallel call that script.Occasionally your for loop is so complex that neither of these is an option.
This is where parallel --semaphore can help you out.sem is the short alias for parallel --semaphore.
for i in `ls *.log` ; do
[... a lot of complex lines here ...]
sem -j4 --id my_id do_work $i
done
sem --wait --id my_id
This will run do_work in the background until four jobs are running.Then sem will wait until one of the four jobs has finished before starting another job.The last line (sem --wait) pauses the script until all the jobs started by sem have finished.my_id is a unique string used by sem to identify this script, since you may have other sems running at the same time.If you only run sem from one script at a time, --id my_id can be left out.
A special case is sem -j1, which works like a mutex and is useful if you only want one program running at a time.
GNU Parallel as a Job Queue Manager
With a few lines of code, GNU Parallel can work as a job queue manager:
echo >jobqueue; tail -f jobqueue | parallel
To submit your jobs to the queue, do:
echo my_command my_arg >> jobqueue
You can, of course, use -S to distribute the jobs to remote computers:
echo >jobqueue; tail -f jobqueue | parallel -S ..
If you have a dir into which users drop files that need to be processed, you can do this on GNU/Linux:
inotifywait -q -m -r -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.Here again you can use -S to distribute the jobs to remote computers:
inotifywait -q -m -r -e CLOSE_WRITE --format %w%f my_dir | parallel -S .. -u echo
See You on the Mailing List
I hope you have thought of situations where GNU Parallel can be of benefit to you.If you like GNU Parallel please let others know about it through email lists, forums, blogs, and social networks.If GNU Parallel saves you money, please donate to the FSF https://my.fsf.org/donate.If you have questions about GNU Parallel, join the mailing list at http://lists.gnu.org/mailman/listinfo/parallel.
;login: FEBRUARY 2011 GNU Parallel: The Command-Line Power Tool 47\Ole Tange works in bioinformatics in Copenhagen. He is active in the free software community and is best known for his "patented Web shop" that shows the dangers of software patents (http:// ole.tange.dk/swpat). He will be happy to go to your conference to give a talk about GNU Parallel. [email protected]
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Login. February 2011, Volume 36, Number 1 Authors: Ole Tange 105438-Tange.pdf<
GNU parallel can be found on the main GNU ftp server: http://ftp.gnu.org/gnu/parallel/ (via HTTP) and ftp://ftp.gnu.org/gnu/parallel/ (via FTP). It can also be found on the GNU mirrors; please use a mirror if possible.
Official packages exist for:
Community maintained packages:
Just like other GNU software GNU parallel has documentation available online:
Some short videos displaying the most common usage are available at: http://www.youtube.com/playlist?list=PL284C9FF2488BC6D1.
The history of GNU parallel can be found at http://www.gnu.org/software/parallel/history.html.
The package includes GNU env_parallel, GNU sem, GNU parcat, GNU parset, GNU sql, and GNU niceload.
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