Provided by: parallel_20210822+ds-2_all 
NAME
parallel_alternatives - Alternatives to GNU parallel
DIFFERENCES BETWEEN GNU Parallel AND ALTERNATIVES
There are a lot programs with some of the functionality of GNU parallel. GNU parallel
strives to include the best of the functionality without sacrificing ease of use.
parallel has existed since 2002 and as GNU parallel since 2010. A lot of the alternatives
have not had the vitality to survive that long, but have come and gone during that time.
GNU parallel is actively maintained with a new release every month since 2010. Most other
alternatives are fleeting interests of the developers with irregular releases and only
maintained for a few years.
SUMMARY LEGEND
The following features are in some of the comparable tools:
Inputs
I1. Arguments can be read from stdin
I2. Arguments can be read from a file
I3. Arguments can be read from multiple files
I4. Arguments can be read from command line
I5. Arguments can be read from a table
I6. Arguments can be read from the same file using #! (shebang)
I7. Line oriented input as default (Quoting of special chars not needed)
Manipulation of input
M1. Composed command
M2. Multiple arguments can fill up an execution line
M3. Arguments can be put anywhere in the execution line
M4. Multiple arguments can be put anywhere in the execution line
M5. Arguments can be replaced with context
M6. Input can be treated as the complete command line
Outputs
O1. Grouping output so output from different jobs do not mix
O2. Send stderr (standard error) to stderr (standard error)
O3. Send stdout (standard output) to stdout (standard output)
O4. Order of output can be same as order of input
O5. Stdout only contains stdout (standard output) from the command
O6. Stderr only contains stderr (standard error) from the command
O7. Buffering on disk
O8. Cleanup of temporary files if killed
O9. Test if disk runs full during run
O10. Output of a line bigger than 4 GB
Execution
E1. Running jobs in parallel
E2. List running jobs
E3. Finish running jobs, but do not start new jobs
E4. Number of running jobs can depend on number of cpus
E5. Finish running jobs, but do not start new jobs after first failure
E6. Number of running jobs can be adjusted while running
E7. Only spawn new jobs if load is less than a limit
Remote execution
R1. Jobs can be run on remote computers
R2. Basefiles can be transferred
R3. Argument files can be transferred
R4. Result files can be transferred
R5. Cleanup of transferred files
R6. No config files needed
R7. Do not run more than SSHD's MaxStartups can handle
R8. Configurable SSH command
R9. Retry if connection breaks occasionally
Semaphore
S1. Possibility to work as a mutex
S2. Possibility to work as a counting semaphore
Legend
- = no
x = not applicable
ID = yes
As every new version of the programs are not tested the table may be outdated. Please file
a bug report if you find errors (See REPORTING BUGS).
parallel:
I1 I2 I3 I4 I5 I6 I7
M1 M2 M3 M4 M5 M6
O1 O2 O3 O4 O5 O6 O7 O8 O9 O10
E1 E2 E3 E4 E5 E6 E7
R1 R2 R3 R4 R5 R6 R7 R8 R9
S1 S2
DIFFERENCES BETWEEN xargs AND GNU Parallel
Summary (see legend above):
I1 I2 - - - - -
- M2 M3 - - -
- O2 O3 - O5 O6
E1 - - - - - -
- - - - - x - - -
- -
xargs offers some of the same possibilities as GNU parallel.
xargs deals badly with special characters (such as space, \, ' and "). To see the problem
try this:
touch important_file
touch 'not important_file'
ls not* | xargs rm
mkdir -p "My brother's 12\" records"
ls | xargs rmdir
touch 'c:\windows\system32\clfs.sys'
echo 'c:\windows\system32\clfs.sys' | xargs ls -l
You can specify -0, but many input generators are not optimized for using NUL as separator
but are optimized for newline as separator. E.g. awk, ls, echo, tar -v, head (requires
using -z), tail (requires using -z), sed (requires using -z), perl (-0 and \0 instead of
\n), locate (requires using -0), find (requires using -print0), grep (requires using -z or
-Z), sort (requires using -z).
GNU parallel's newline separation can be emulated with:
cat | xargs -d "\n" -n1 command
xargs can run a given number of jobs in parallel, but has no support for running number-
of-cpu-cores jobs in parallel.
xargs has no support for grouping the output, therefore output may run together, e.g. the
first half of a line is from one process and the last half of the line is from another
process. The example Parallel grep cannot be done reliably with xargs because of this. To
see this in action try:
parallel perl -e '\$a=\"1\".\"{}\"x10000000\;print\ \$a,\"\\n\"' \
'>' {} ::: a b c d e f g h
# Serial = no mixing = the wanted result
# 'tr -s a-z' squeezes repeating letters into a single letter
echo a b c d e f g h | xargs -P1 -n1 grep 1 | tr -s a-z
# Compare to 8 jobs in parallel
parallel -kP8 -n1 grep 1 ::: a b c d e f g h | tr -s a-z
echo a b c d e f g h | xargs -P8 -n1 grep 1 | tr -s a-z
echo a b c d e f g h | xargs -P8 -n1 grep --line-buffered 1 | \
tr -s a-z
Or try this:
slow_seq() {
echo Count to "$@"
seq "$@" |
perl -ne '$|=1; for(split//){ print; select($a,$a,$a,0.100);}'
}
export -f slow_seq
# Serial = no mixing = the wanted result
seq 8 | xargs -n1 -P1 -I {} bash -c 'slow_seq {}'
# Compare to 8 jobs in parallel
seq 8 | parallel -P8 slow_seq {}
seq 8 | xargs -n1 -P8 -I {} bash -c 'slow_seq {}'
xargs has no support for keeping the order of the output, therefore if running jobs in
parallel using xargs the output of the second job cannot be postponed till the first job
is done.
xargs has no support for running jobs on remote computers.
xargs has no support for context replace, so you will have to create the arguments.
If you use a replace string in xargs (-I) you can not force xargs to use more than one
argument.
Quoting in xargs works like -q in GNU parallel. This means composed commands and
redirection require using bash -c.
ls | parallel "wc {} >{}.wc"
ls | parallel "echo {}; ls {}|wc"
becomes (assuming you have 8 cores and that none of the filenames contain space, " or ').
ls | xargs -d "\n" -P8 -I {} bash -c "wc {} >{}.wc"
ls | xargs -d "\n" -P8 -I {} bash -c "echo {}; ls {}|wc"
https://www.gnu.org/software/findutils/
DIFFERENCES BETWEEN find -exec AND GNU Parallel
Summary (see legend above):
- - - x - x -
- M2 M3 - - - -
- O2 O3 O4 O5 O6
- - - - - - -
- - - - - - - - -
x x
find -exec offers some of the same possibilities as GNU parallel.
find -exec only works on files. Processing other input (such as hosts or URLs) will
require creating these inputs as files. find -exec has no support for running commands in
parallel.
https://www.gnu.org/software/findutils/ (Last checked: 2019-01)
DIFFERENCES BETWEEN make -j AND GNU Parallel
Summary (see legend above):
- - - - - - -
- - - - - -
O1 O2 O3 - x O6
E1 - - - E5 -
- - - - - - - - -
- -
make -j can run jobs in parallel, but requires a crafted Makefile to do this. That results
in extra quoting to get filenames containing newlines to work correctly.
make -j computes a dependency graph before running jobs. Jobs run by GNU parallel does not
depend on each other.
(Very early versions of GNU parallel were coincidentally implemented using make -j).
https://www.gnu.org/software/make/ (Last checked: 2019-01)
DIFFERENCES BETWEEN ppss AND GNU Parallel
Summary (see legend above):
I1 I2 - - - - I7
M1 - M3 - - M6
O1 - - x - -
E1 E2 ?E3 E4 - - -
R1 R2 R3 R4 - - ?R7 ? ?
- -
ppss is also a tool for running jobs in parallel.
The output of ppss is status information and thus not useful for using as input for
another command. The output from the jobs are put into files.
The argument replace string ($ITEM) cannot be changed. Arguments must be quoted - thus
arguments containing special characters (space '"&!*) may cause problems. More than one
argument is not supported. Filenames containing newlines are not processed correctly. When
reading input from a file null cannot be used as a terminator. ppss needs to read the
whole input file before starting any jobs.
Output and status information is stored in ppss_dir and thus requires cleanup when
completed. If the dir is not removed before running ppss again it may cause nothing to
happen as ppss thinks the task is already done. GNU parallel will normally not need
cleaning up if running locally and will only need cleaning up if stopped abnormally and
running remote (--cleanup may not complete if stopped abnormally). The example Parallel
grep would require extra postprocessing if written using ppss.
For remote systems PPSS requires 3 steps: config, deploy, and start. GNU parallel only
requires one step.
EXAMPLES FROM ppss MANUAL
Here are the examples from ppss's manual page with the equivalent using GNU parallel:
1$ ./ppss.sh standalone -d /path/to/files -c 'gzip '
1$ find /path/to/files -type f | parallel gzip
2$ ./ppss.sh standalone -d /path/to/files -c 'cp "$ITEM" /destination/dir '
2$ find /path/to/files -type f | parallel cp {} /destination/dir
3$ ./ppss.sh standalone -f list-of-urls.txt -c 'wget -q '
3$ parallel -a list-of-urls.txt wget -q
4$ ./ppss.sh standalone -f list-of-urls.txt -c 'wget -q "$ITEM"'
4$ parallel -a list-of-urls.txt wget -q {}
5$ ./ppss config -C config.cfg -c 'encode.sh ' -d /source/dir \
-m 192.168.1.100 -u ppss -k ppss-key.key -S ./encode.sh \
-n nodes.txt -o /some/output/dir --upload --download;
./ppss deploy -C config.cfg
./ppss start -C config
5$ # parallel does not use configs. If you want a different username put it in nodes.txt: user@hostname
find source/dir -type f |
parallel --sshloginfile nodes.txt --trc {.}.mp3 lame -a {} -o {.}.mp3 --preset standard --quiet
6$ ./ppss stop -C config.cfg
6$ killall -TERM parallel
7$ ./ppss pause -C config.cfg
7$ Press: CTRL-Z or killall -SIGTSTP parallel
8$ ./ppss continue -C config.cfg
8$ Enter: fg or killall -SIGCONT parallel
9$ ./ppss.sh status -C config.cfg
9$ killall -SIGUSR2 parallel
https://github.com/louwrentius/PPSS
DIFFERENCES BETWEEN pexec AND GNU Parallel
Summary (see legend above):
I1 I2 - I4 I5 - -
M1 - M3 - - M6
O1 O2 O3 - O5 O6
E1 - - E4 - E6 -
R1 - - - - R6 - - -
S1 -
pexec is also a tool for running jobs in parallel.
EXAMPLES FROM pexec MANUAL
Here are the examples from pexec's info page with the equivalent using GNU parallel:
1$ pexec -o sqrt-%s.dat -p "$(seq 10)" -e NUM -n 4 -c -- \
'echo "scale=10000;sqrt($NUM)" | bc'
1$ seq 10 | parallel -j4 'echo "scale=10000;sqrt({})" | \
bc > sqrt-{}.dat'
2$ pexec -p "$(ls myfiles*.ext)" -i %s -o %s.sort -- sort
2$ ls myfiles*.ext | parallel sort {} ">{}.sort"
3$ pexec -f image.list -n auto -e B -u star.log -c -- \
'fistar $B.fits -f 100 -F id,x,y,flux -o $B.star'
3$ parallel -a image.list \
'fistar {}.fits -f 100 -F id,x,y,flux -o {}.star' 2>star.log
4$ pexec -r *.png -e IMG -c -o - -- \
'convert $IMG ${IMG%.png}.jpeg ; "echo $IMG: done"'
4$ ls *.png | parallel 'convert {} {.}.jpeg; echo {}: done'
5$ pexec -r *.png -i %s -o %s.jpg -c 'pngtopnm | pnmtojpeg'
5$ ls *.png | parallel 'pngtopnm < {} | pnmtojpeg > {}.jpg'
6$ for p in *.png ; do echo ${p%.png} ; done | \
pexec -f - -i %s.png -o %s.jpg -c 'pngtopnm | pnmtojpeg'
6$ ls *.png | parallel 'pngtopnm < {} | pnmtojpeg > {.}.jpg'
7$ LIST=$(for p in *.png ; do echo ${p%.png} ; done)
pexec -r $LIST -i %s.png -o %s.jpg -c 'pngtopnm | pnmtojpeg'
7$ ls *.png | parallel 'pngtopnm < {} | pnmtojpeg > {.}.jpg'
8$ pexec -n 8 -r *.jpg -y unix -e IMG -c \
'pexec -j -m blockread -d $IMG | \
jpegtopnm | pnmscale 0.5 | pnmtojpeg | \
pexec -j -m blockwrite -s th_$IMG'
8$ # Combining GNU B<parallel> and GNU B<sem>.
ls *jpg | parallel -j8 'sem --id blockread cat {} | jpegtopnm |' \
'pnmscale 0.5 | pnmtojpeg | sem --id blockwrite cat > th_{}'
# If reading and writing is done to the same disk, this may be
# faster as only one process will be either reading or writing:
ls *jpg | parallel -j8 'sem --id diskio cat {} | jpegtopnm |' \
'pnmscale 0.5 | pnmtojpeg | sem --id diskio cat > th_{}'
https://www.gnu.org/software/pexec/
DIFFERENCES BETWEEN xjobs AND GNU Parallel
xjobs is also a tool for running jobs in parallel. It only supports running jobs on your
local computer.
xjobs deals badly with special characters just like xargs. See the section DIFFERENCES
BETWEEN xargs AND GNU Parallel.
EXAMPLES FROM xjobs MANUAL
Here are the examples from xjobs's man page with the equivalent using GNU parallel:
1$ ls -1 *.zip | xjobs unzip
1$ ls *.zip | parallel unzip
2$ ls -1 *.zip | xjobs -n unzip
2$ ls *.zip | parallel unzip >/dev/null
3$ find . -name '*.bak' | xjobs gzip
3$ find . -name '*.bak' | parallel gzip
4$ ls -1 *.jar | sed 's/\(.*\)/\1 > \1.idx/' | xjobs jar tf
4$ ls *.jar | parallel jar tf {} '>' {}.idx
5$ xjobs -s script
5$ cat script | parallel
6$ mkfifo /var/run/my_named_pipe;
xjobs -s /var/run/my_named_pipe &
echo unzip 1.zip >> /var/run/my_named_pipe;
echo tar cf /backup/myhome.tar /home/me >> /var/run/my_named_pipe
6$ mkfifo /var/run/my_named_pipe;
cat /var/run/my_named_pipe | parallel &
echo unzip 1.zip >> /var/run/my_named_pipe;
echo tar cf /backup/myhome.tar /home/me >> /var/run/my_named_pipe
https://www.maier-komor.de/xjobs.html (Last checked: 2019-01)
DIFFERENCES BETWEEN prll AND GNU Parallel
prll is also a tool for running jobs in parallel. It does not support running jobs on
remote computers.
prll encourages using BASH aliases and BASH functions instead of scripts. GNU parallel
supports scripts directly, functions if they are exported using export -f, and aliases if
using env_parallel.
prll generates a lot of status information on stderr (standard error) which makes it
harder to use the stderr (standard error) output of the job directly as input for another
program.
EXAMPLES FROM prll's MANUAL
Here is the example from prll's man page with the equivalent using GNU parallel:
1$ prll -s 'mogrify -flip $1' *.jpg
1$ parallel mogrify -flip ::: *.jpg
https://github.com/exzombie/prll (Last checked: 2019-01)
DIFFERENCES BETWEEN dxargs AND GNU Parallel
dxargs is also a tool for running jobs in parallel.
dxargs does not deal well with more simultaneous jobs than SSHD's MaxStartups. dxargs is
only built for remote run jobs, but does not support transferring of files.
https://web.archive.org/web/20120518070250/http://www.
semicomplete.com/blog/geekery/distributed-xargs.html (Last checked: 2019-01)
DIFFERENCES BETWEEN mdm/middleman AND GNU Parallel
middleman(mdm) is also a tool for running jobs in parallel.
EXAMPLES FROM middleman's WEBSITE
Here are the shellscripts of https://web.archive.org/web/20110728064735/http://mdm.
berlios.de/usage.html ported to GNU parallel:
1$ seq 19 | parallel buffon -o - | sort -n > result
cat files | parallel cmd
find dir -execdir sem cmd {} \;
https://github.com/cklin/mdm (Last checked: 2019-01)
DIFFERENCES BETWEEN xapply AND GNU Parallel
xapply can run jobs in parallel on the local computer.
EXAMPLES FROM xapply's MANUAL
Here are the examples from xapply's man page with the equivalent using GNU parallel:
1$ xapply '(cd %1 && make all)' */
1$ parallel 'cd {} && make all' ::: */
2$ xapply -f 'diff %1 ../version5/%1' manifest | more
2$ parallel diff {} ../version5/{} < manifest | more
3$ xapply -p/dev/null -f 'diff %1 %2' manifest1 checklist1
3$ parallel --link diff {1} {2} :::: manifest1 checklist1
4$ xapply 'indent' *.c
4$ parallel indent ::: *.c
5$ find ~ksb/bin -type f ! -perm -111 -print | \
xapply -f -v 'chmod a+x' -
5$ find ~ksb/bin -type f ! -perm -111 -print | \
parallel -v chmod a+x
6$ find */ -... | fmt 960 1024 | xapply -f -i /dev/tty 'vi' -
6$ sh <(find */ -... | parallel -s 1024 echo vi)
6$ find */ -... | parallel -s 1024 -Xuj1 vi
7$ find ... | xapply -f -5 -i /dev/tty 'vi' - - - - -
7$ sh <(find ... | parallel -n5 echo vi)
7$ find ... | parallel -n5 -uj1 vi
8$ xapply -fn "" /etc/passwd
8$ parallel -k echo < /etc/passwd
9$ tr ':' '\012' < /etc/passwd | \
xapply -7 -nf 'chown %1 %6' - - - - - - -
9$ tr ':' '\012' < /etc/passwd | parallel -N7 chown {1} {6}
10$ xapply '[ -d %1/RCS ] || echo %1' */
10$ parallel '[ -d {}/RCS ] || echo {}' ::: */
11$ xapply -f '[ -f %1 ] && echo %1' List | ...
11$ parallel '[ -f {} ] && echo {}' < List | ...
https://www.databits.net/~ksb/msrc/local/bin/xapply/xapply.html
DIFFERENCES BETWEEN AIX apply AND GNU Parallel
apply can build command lines based on a template and arguments - very much like GNU
parallel. apply does not run jobs in parallel. apply does not use an argument separator
(like :::); instead the template must be the first argument.
EXAMPLES FROM IBM's KNOWLEDGE CENTER
Here are the examples from IBM's Knowledge Center and the corresponding command using GNU
parallel:
To obtain results similar to those of the ls command, enter:
1$ apply echo *
1$ parallel echo ::: *
To compare the file named a1 to the file named b1, and the file named a2 to the file named
b2, enter:
2$ apply -2 cmp a1 b1 a2 b2
2$ parallel -N2 cmp ::: a1 b1 a2 b2
To run the who command five times, enter:
3$ apply -0 who 1 2 3 4 5
3$ parallel -N0 who ::: 1 2 3 4 5
To link all files in the current directory to the directory /usr/joe, enter:
4$ apply 'ln %1 /usr/joe' *
4$ parallel ln {} /usr/joe ::: *
https://www-01.ibm.com/support/knowledgecenter/ ssw_aix_71/com.ibm.aix.cmds1/apply.htm
(Last checked: 2019-01)
DIFFERENCES BETWEEN paexec AND GNU Parallel
paexec can run jobs in parallel on both the local and remote computers.
paexec requires commands to print a blank line as the last output. This means you will
have to write a wrapper for most programs.
paexec has a job dependency facility so a job can depend on another job to be executed
successfully. Sort of a poor-man's make.
EXAMPLES FROM paexec's EXAMPLE CATALOG
Here are the examples from paexec's example catalog with the equivalent using GNU
parallel:
1_div_X_run
1$ ../../paexec -s -l -c "`pwd`/1_div_X_cmd" -n +1 <<EOF [...]
1$ parallel echo {} '|' `pwd`/1_div_X_cmd <<EOF [...]
all_substr_run
2$ ../../paexec -lp -c "`pwd`/all_substr_cmd" -n +3 <<EOF [...]
2$ parallel echo {} '|' `pwd`/all_substr_cmd <<EOF [...]
cc_wrapper_run
3$ ../../paexec -c "env CC=gcc CFLAGS=-O2 `pwd`/cc_wrapper_cmd" \
-n 'host1 host2' \
-t '/usr/bin/ssh -x' <<EOF [...]
3$ parallel echo {} '|' "env CC=gcc CFLAGS=-O2 `pwd`/cc_wrapper_cmd" \
-S host1,host2 <<EOF [...]
# This is not exactly the same, but avoids the wrapper
parallel gcc -O2 -c -o {.}.o {} \
-S host1,host2 <<EOF [...]
toupper_run
4$ ../../paexec -lp -c "`pwd`/toupper_cmd" -n +10 <<EOF [...]
4$ parallel echo {} '|' ./toupper_cmd <<EOF [...]
# Without the wrapper:
parallel echo {} '| awk {print\ toupper\(\$0\)}' <<EOF [...]
https://github.com/cheusov/paexec
DIFFERENCES BETWEEN map(sitaramc) AND GNU Parallel
Summary (see legend above):
I1 - - I4 - - (I7)
M1 (M2) M3 (M4) M5 M6
- O2 O3 - O5 - - N/A N/A O10
E1 - - - - - -
- - - - - - - - -
- -
(I7): Only under special circumstances. See below.
(M2+M4): Only if there is a single replacement string.
map rejects input with special characters:
echo "The Cure" > My\ brother\'s\ 12\"\ records
ls | map 'echo %; wc %'
It works with GNU parallel:
ls | parallel 'echo {}; wc {}'
Under some circumstances it also works with map:
ls | map 'echo % works %'
But tiny changes make it reject the input with special characters:
ls | map 'echo % does not work "%"'
This means that many UTF-8 characters will be rejected. This is by design. From the web
page: "As such, programs that quietly handle them, with no warnings at all, are doing
their users a disservice."
map delays each job by 0.01 s. This can be emulated by using parallel --delay 0.01.
map prints '+' on stderr when a job starts, and '-' when a job finishes. This cannot be
disabled. parallel has --bar if you need to see progress.
map's replacement strings (% %D %B %E) can be simulated in GNU parallel by putting this in
~/.parallel/config:
--rpl '%'
--rpl '%D $_=Q(::dirname($_));'
--rpl '%B s:.*/::;s:\.[^/.]+$::;'
--rpl '%E s:.*\.::'
map does not have an argument separator on the command line, but uses the first argument
as command. This makes quoting harder which again may affect readability. Compare:
map -p 2 'perl -ne '"'"'/^\S+\s+\S+$/ and print $ARGV,"\n"'"'" *
parallel -q perl -ne '/^\S+\s+\S+$/ and print $ARGV,"\n"' ::: *
map can do multiple arguments with context replace, but not without context replace:
parallel --xargs echo 'BEGIN{'{}'}END' ::: 1 2 3
map "echo 'BEGIN{'%'}END'" 1 2 3
map has no support for grouping. So this gives the wrong results:
parallel perl -e '\$a=\"1{}\"x10000000\;print\ \$a,\"\\n\"' '>' {} \
::: a b c d e f
ls -l a b c d e f
parallel -kP4 -n1 grep 1 ::: a b c d e f > out.par
map -n1 -p 4 'grep 1' a b c d e f > out.map-unbuf
map -n1 -p 4 'grep --line-buffered 1' a b c d e f > out.map-linebuf
map -n1 -p 1 'grep --line-buffered 1' a b c d e f > out.map-serial
ls -l out*
md5sum out*
EXAMPLES FROM map's WEBSITE
Here are the examples from map's web page with the equivalent using GNU parallel:
1$ ls *.gif | map convert % %B.png # default max-args: 1
1$ ls *.gif | parallel convert {} {.}.png
2$ map "mkdir %B; tar -C %B -xf %" *.tgz # default max-args: 1
2$ parallel 'mkdir {.}; tar -C {.} -xf {}' ::: *.tgz
3$ ls *.gif | map cp % /tmp # default max-args: 100
3$ ls *.gif | parallel -X cp {} /tmp
4$ ls *.tar | map -n 1 tar -xf %
4$ ls *.tar | parallel tar -xf
5$ map "cp % /tmp" *.tgz
5$ parallel cp {} /tmp ::: *.tgz
6$ map "du -sm /home/%/mail" alice bob carol
6$ parallel "du -sm /home/{}/mail" ::: alice bob carol
or if you prefer running a single job with multiple args:
6$ parallel -Xj1 "du -sm /home/{}/mail" ::: alice bob carol
7$ cat /etc/passwd | map -d: 'echo user %1 has shell %7'
7$ cat /etc/passwd | parallel --colsep : 'echo user {1} has shell {7}'
8$ export MAP_MAX_PROCS=$(( `nproc` / 2 ))
8$ export PARALLEL=-j50%
https://github.com/sitaramc/map (Last checked: 2020-05)
DIFFERENCES BETWEEN ladon AND GNU Parallel
ladon can run multiple jobs on files in parallel.
ladon only works on files and the only way to specify files is using a quoted glob string
(such as \*.jpg). It is not possible to list the files manually.
As replacement strings it uses FULLPATH DIRNAME BASENAME EXT RELDIR RELPATH
These can be simulated using GNU parallel by putting this in ~/.parallel/config:
--rpl 'FULLPATH $_=Q($_);chomp($_=qx{readlink -f $_});'
--rpl 'DIRNAME $_=Q(::dirname($_));chomp($_=qx{readlink -f $_});'
--rpl 'BASENAME s:.*/::;s:\.[^/.]+$::;'
--rpl 'EXT s:.*\.::'
--rpl 'RELDIR $_=Q($_);chomp(($_,$c)=qx{readlink -f $_;pwd});
s:\Q$c/\E::;$_=::dirname($_);'
--rpl 'RELPATH $_=Q($_);chomp(($_,$c)=qx{readlink -f $_;pwd});
s:\Q$c/\E::;'
ladon deals badly with filenames containing " and newline, and it fails for output larger
than 200k:
ladon '*' -- seq 36000 | wc
EXAMPLES FROM ladon MANUAL
It is assumed that the '--rpl's above are put in ~/.parallel/config and that it is run
under a shell that supports '**' globbing (such as zsh):
1$ ladon "**/*.txt" -- echo RELPATH
1$ parallel echo RELPATH ::: **/*.txt
2$ ladon "~/Documents/**/*.pdf" -- shasum FULLPATH >hashes.txt
2$ parallel shasum FULLPATH ::: ~/Documents/**/*.pdf >hashes.txt
3$ ladon -m thumbs/RELDIR "**/*.jpg" -- convert FULLPATH \
-thumbnail 100x100^ -gravity center -extent 100x100 \
thumbs/RELPATH
3$ parallel mkdir -p thumbs/RELDIR\; convert FULLPATH
-thumbnail 100x100^ -gravity center -extent 100x100 \
thumbs/RELPATH ::: **/*.jpg
4$ ladon "~/Music/*.wav" -- lame -V 2 FULLPATH DIRNAME/BASENAME.mp3
4$ parallel lame -V 2 FULLPATH DIRNAME/BASENAME.mp3 ::: ~/Music/*.wav
https://github.com/danielgtaylor/ladon (Last checked: 2019-01)
DIFFERENCES BETWEEN jobflow AND GNU Parallel
jobflow can run multiple jobs in parallel.
Just like xargs output from jobflow jobs running in parallel mix together by default.
jobflow can buffer into files (placed in /run/shm), but these are not cleaned up if
jobflow dies unexpectedly (e.g. by Ctrl-C). If the total output is big (in the order of
RAM+swap) it can cause the system to slow to a crawl and eventually run out of memory.
jobflow gives no error if the command is unknown, and like xargs redirection and composed
commands require wrapping with bash -c.
Input lines can at most be 4096 bytes. You can at most have 16 {}'s in the command
template. More than that either crashes the program or simple does not execute the
command.
jobflow has no equivalent for --pipe, or --sshlogin.
jobflow makes it possible to set resource limits on the running jobs. This can be emulated
by GNU parallel using bash's ulimit:
jobflow -limits=mem=100M,cpu=3,fsize=20M,nofiles=300 myjob
parallel 'ulimit -v 102400 -t 3 -f 204800 -n 300 myjob'
EXAMPLES FROM jobflow README
1$ cat things.list | jobflow -threads=8 -exec ./mytask {}
1$ cat things.list | parallel -j8 ./mytask {}
2$ seq 100 | jobflow -threads=100 -exec echo {}
2$ seq 100 | parallel -j100 echo {}
3$ cat urls.txt | jobflow -threads=32 -exec wget {}
3$ cat urls.txt | parallel -j32 wget {}
4$ find . -name '*.bmp' | \
jobflow -threads=8 -exec bmp2jpeg {.}.bmp {.}.jpg
4$ find . -name '*.bmp' | \
parallel -j8 bmp2jpeg {.}.bmp {.}.jpg
https://github.com/rofl0r/jobflow
DIFFERENCES BETWEEN gargs AND GNU Parallel
gargs can run multiple jobs in parallel.
Older versions cache output in memory. This causes it to be extremely slow when the output
is larger than the physical RAM, and can cause the system to run out of memory.
See more details on this in man parallel_design.
Newer versions cache output in files, but leave files in $TMPDIR if it is killed.
Output to stderr (standard error) is changed if the command fails.
EXAMPLES FROM gargs WEBSITE
1$ seq 12 -1 1 | gargs -p 4 -n 3 "sleep {0}; echo {1} {2}"
1$ seq 12 -1 1 | parallel -P 4 -n 3 "sleep {1}; echo {2} {3}"
2$ cat t.txt | gargs --sep "\s+" \
-p 2 "echo '{0}:{1}-{2}' full-line: \'{}\'"
2$ cat t.txt | parallel --colsep "\\s+" \
-P 2 "echo '{1}:{2}-{3}' full-line: \'{}\'"
https://github.com/brentp/gargs
DIFFERENCES BETWEEN orgalorg AND GNU Parallel
orgalorg can run the same job on multiple machines. This is related to --onall and
--nonall.
orgalorg supports entering the SSH password - provided it is the same for all servers. GNU
parallel advocates using ssh-agent instead, but it is possible to emulate orgalorg's
behavior by setting SSHPASS and by using --ssh "sshpass ssh".
To make the emulation easier, make a simple alias:
alias par_emul="parallel -j0 --ssh 'sshpass ssh' --nonall --tag --lb"
If you want to supply a password run:
SSHPASS=`ssh-askpass`
or set the password directly:
SSHPASS=P4$$w0rd!
If the above is set up you can then do:
orgalorg -o frontend1 -o frontend2 -p -C uptime
par_emul -S frontend1 -S frontend2 uptime
orgalorg -o frontend1 -o frontend2 -p -C top -bid 1
par_emul -S frontend1 -S frontend2 top -bid 1
orgalorg -o frontend1 -o frontend2 -p -er /tmp -n \
'md5sum /tmp/bigfile' -S bigfile
par_emul -S frontend1 -S frontend2 --basefile bigfile \
--workdir /tmp md5sum /tmp/bigfile
orgalorg has a progress indicator for the transferring of a file. GNU parallel does not.
https://github.com/reconquest/orgalorg
DIFFERENCES BETWEEN Rust parallel AND GNU Parallel
Rust parallel focuses on speed. It is almost as fast as xargs, but not as fast as
parallel-bash. It implements a few features from GNU parallel, but lacks many functions.
All these fail:
# Read arguments from file
parallel -a file echo
# Changing the delimiter
parallel -d _ echo ::: a_b_c_
These do something different from GNU parallel
# -q to protect quoted $ and space
parallel -q perl -e '$a=shift; print "$a"x10000000' ::: a b c
# Generation of combination of inputs
parallel echo {1} {2} ::: red green blue ::: S M L XL XXL
# {= perl expression =} replacement string
parallel echo '{= s/new/old/ =}' ::: my.new your.new
# --pipe
seq 100000 | parallel --pipe wc
# linked arguments
parallel echo ::: S M L :::+ sml med lrg ::: R G B :::+ red grn blu
# Run different shell dialects
zsh -c 'parallel echo \={} ::: zsh && true'
csh -c 'parallel echo \$\{\} ::: shell && true'
bash -c 'parallel echo \$\({}\) ::: pwd && true'
# Rust parallel does not start before the last argument is read
(seq 10; sleep 5; echo 2) | time parallel -j2 'sleep 2; echo'
tail -f /var/log/syslog | parallel echo
Most of the examples from the book GNU Parallel 2018 do not work, thus Rust parallel is
not close to being a compatible replacement.
Rust parallel has no remote facilities.
It uses /tmp/parallel for tmp files and does not clean up if terminated abruptly. If
another user on the system uses Rust parallel, then /tmp/parallel will have the wrong
permissions and Rust parallel will fail. A malicious user can setup the right permissions
and symlink the output file to one of the user's files and next time the user uses Rust
parallel it will overwrite this file.
attacker$ mkdir /tmp/parallel
attacker$ chmod a+rwX /tmp/parallel
# Symlink to the file the attacker wants to zero out
attacker$ ln -s ~victim/.important-file /tmp/parallel/stderr_1
victim$ seq 1000 | parallel echo
# This file is now overwritten with stderr from 'echo'
victim$ cat ~victim/.important-file
If /tmp/parallel runs full during the run, Rust parallel does not report this, but
finishes with success - thereby risking data loss.
https://github.com/mmstick/parallel
DIFFERENCES BETWEEN Rush AND GNU Parallel
rush (https://github.com/shenwei356/rush) is written in Go and based on gargs.
Just like GNU parallel rush buffers in temporary files. But opposite GNU parallel rush
does not clean up, if the process dies abnormally.
rush has some string manipulations that can be emulated by putting this into
~/.parallel/config (/ is used instead of %, and % is used instead of ^ as that is closer
to bash's ${var%postfix}):
--rpl '{:} s:(\.[^/]+)*$::'
--rpl '{:%([^}]+?)} s:$$1(\.[^/]+)*$::'
--rpl '{/:%([^}]*?)} s:.*/(.*)$$1(\.[^/]+)*$:$1:'
--rpl '{/:} s:(.*/)?([^/.]+)(\.[^/]+)*$:$2:'
--rpl '{@(.*?)} /$$1/ and $_=$1;'
EXAMPLES FROM rush's WEBSITE
Here are the examples from rush's website with the equivalent command in GNU parallel.
1. Simple run, quoting is not necessary
1$ seq 1 3 | rush echo {}
1$ seq 1 3 | parallel echo {}
2. Read data from file (`-i`)
2$ rush echo {} -i data1.txt -i data2.txt
2$ cat data1.txt data2.txt | parallel echo {}
3. Keep output order (`-k`)
3$ seq 1 3 | rush 'echo {}' -k
3$ seq 1 3 | parallel -k echo {}
4. Timeout (`-t`)
4$ time seq 1 | rush 'sleep 2; echo {}' -t 1
4$ time seq 1 | parallel --timeout 1 'sleep 2; echo {}'
5. Retry (`-r`)
5$ seq 1 | rush 'python unexisted_script.py' -r 1
5$ seq 1 | parallel --retries 2 'python unexisted_script.py'
Use -u to see it is really run twice:
5$ seq 1 | parallel -u --retries 2 'python unexisted_script.py'
6. Dirname (`{/}`) and basename (`{%}`) and remove custom suffix (`{^suffix}`)
6$ echo dir/file_1.txt.gz | rush 'echo {/} {%} {^_1.txt.gz}'
6$ echo dir/file_1.txt.gz |
parallel --plus echo {//} {/} {%_1.txt.gz}
7. Get basename, and remove last (`{.}`) or any (`{:}`) extension
7$ echo dir.d/file.txt.gz | rush 'echo {.} {:} {%.} {%:}'
7$ echo dir.d/file.txt.gz | parallel 'echo {.} {:} {/.} {/:}'
8. Job ID, combine fields index and other replacement strings
8$ echo 12 file.txt dir/s_1.fq.gz |
rush 'echo job {#}: {2} {2.} {3%:^_1}'
8$ echo 12 file.txt dir/s_1.fq.gz |
parallel --colsep ' ' 'echo job {#}: {2} {2.} {3/:%_1}'
9. Capture submatch using regular expression (`{@regexp}`)
9$ echo read_1.fq.gz | rush 'echo {@(.+)_\d}'
9$ echo read_1.fq.gz | parallel 'echo {@(.+)_\d}'
10. Custom field delimiter (`-d`)
10$ echo a=b=c | rush 'echo {1} {2} {3}' -d =
10$ echo a=b=c | parallel -d = echo {1} {2} {3}
11. Send multi-lines to every command (`-n`)
11$ seq 5 | rush -n 2 -k 'echo "{}"; echo'
11$ seq 5 |
parallel -n 2 -k \
'echo {=-1 $_=join"\n",@arg[1..$#arg] =}; echo'
11$ seq 5 | rush -n 2 -k 'echo "{}"; echo' -J ' '
11$ seq 5 | parallel -n 2 -k 'echo {}; echo'
12. Custom record delimiter (`-D`), note that empty records are not used.
12$ echo a b c d | rush -D " " -k 'echo {}'
12$ echo a b c d | parallel -d " " -k 'echo {}'
12$ echo abcd | rush -D "" -k 'echo {}'
Cannot be done by GNU Parallel
12$ cat fasta.fa
>seq1
tag
>seq2
cat
gat
>seq3
attac
a
cat
12$ cat fasta.fa | rush -D ">" \
'echo FASTA record {#}: name: {1} sequence: {2}' -k -d "\n"
# rush fails to join the multiline sequences
12$ cat fasta.fa | (read -n1 ignore_first_char;
parallel -d '>' --colsep '\n' echo FASTA record {#}: \
name: {1} sequence: '{=2 $_=join"",@arg[2..$#arg]=}'
)
13. Assign value to variable, like `awk -v` (`-v`)
13$ seq 1 |
rush 'echo Hello, {fname} {lname}!' -v fname=Wei -v lname=Shen
13$ seq 1 |
parallel -N0 \
'fname=Wei; lname=Shen; echo Hello, ${fname} ${lname}!'
13$ for var in a b; do \
13$ seq 1 3 | rush -k -v var=$var 'echo var: {var}, data: {}'; \
13$ done
In GNU parallel you would typically do:
13$ seq 1 3 | parallel -k echo var: {1}, data: {2} ::: a b :::: -
If you really want the var:
13$ seq 1 3 |
parallel -k var={1} ';echo var: $var, data: {}' ::: a b :::: -
If you really want the for-loop:
13$ for var in a b; do
export var;
seq 1 3 | parallel -k 'echo var: $var, data: {}';
done
Contrary to rush this also works if the value is complex like:
My brother's 12" records
14. Preset variable (`-v`), avoid repeatedly writing verbose replacement strings
14$ # naive way
echo read_1.fq.gz | rush 'echo {:^_1} {:^_1}_2.fq.gz'
14$ echo read_1.fq.gz | parallel 'echo {:%_1} {:%_1}_2.fq.gz'
14$ # macro + removing suffix
echo read_1.fq.gz |
rush -v p='{:^_1}' 'echo {p} {p}_2.fq.gz'
14$ echo read_1.fq.gz |
parallel 'p={:%_1}; echo $p ${p}_2.fq.gz'
14$ # macro + regular expression
echo read_1.fq.gz | rush -v p='{@(.+?)_\d}' 'echo {p} {p}_2.fq.gz'
14$ echo read_1.fq.gz | parallel 'p={@(.+?)_\d}; echo $p ${p}_2.fq.gz'
Contrary to rush GNU parallel works with complex values:
14$ echo "My brother's 12\"read_1.fq.gz" |
parallel 'p={@(.+?)_\d}; echo $p ${p}_2.fq.gz'
15. Interrupt jobs by `Ctrl-C`, rush will stop unfinished commands and exit.
15$ seq 1 20 | rush 'sleep 1; echo {}'
^C
15$ seq 1 20 | parallel 'sleep 1; echo {}'
^C
16. Continue/resume jobs (`-c`). When some jobs failed (by execution failure, timeout, or
canceling by user with `Ctrl + C`), please switch flag `-c/--continue` on and run again,
so that `rush` can save successful commands and ignore them in NEXT run.
16$ seq 1 3 | rush 'sleep {}; echo {}' -t 3 -c
cat successful_cmds.rush
seq 1 3 | rush 'sleep {}; echo {}' -t 3 -c
16$ seq 1 3 | parallel --joblog mylog --timeout 2 \
'sleep {}; echo {}'
cat mylog
seq 1 3 | parallel --joblog mylog --retry-failed \
'sleep {}; echo {}'
Multi-line jobs:
16$ seq 1 3 | rush 'sleep {}; echo {}; \
echo finish {}' -t 3 -c -C finished.rush
cat finished.rush
seq 1 3 | rush 'sleep {}; echo {}; \
echo finish {}' -t 3 -c -C finished.rush
16$ seq 1 3 |
parallel --joblog mylog --timeout 2 'sleep {}; echo {}; \
echo finish {}'
cat mylog
seq 1 3 |
parallel --joblog mylog --retry-failed 'sleep {}; echo {}; \
echo finish {}'
17. A comprehensive example: downloading 1K+ pages given by three URL list files using
`phantomjs save_page.js` (some page contents are dynamically generated by Javascript, so
`wget` does not work). Here I set max jobs number (`-j`) as `20`, each job has a max
running time (`-t`) of `60` seconds and `3` retry changes (`-r`). Continue flag `-c` is
also switched on, so we can continue unfinished jobs. Luckily, it's accomplished in one
run :)
17$ for f in $(seq 2014 2016); do \
/bin/rm -rf $f; mkdir -p $f; \
cat $f.html.txt | rush -v d=$f -d = \
'phantomjs save_page.js "{}" > {d}/{3}.html' \
-j 20 -t 60 -r 3 -c; \
done
GNU parallel can append to an existing joblog with '+':
17$ rm mylog
for f in $(seq 2014 2016); do
/bin/rm -rf $f; mkdir -p $f;
cat $f.html.txt |
parallel -j20 --timeout 60 --retries 4 --joblog +mylog \
--colsep = \
phantomjs save_page.js {1}={2}={3} '>' $f/{3}.html
done
18. A bioinformatics example: mapping with `bwa`, and processing result with `samtools`:
18$ ref=ref/xxx.fa
threads=25
ls -d raw.cluster.clean.mapping/* \
| rush -v ref=$ref -v j=$threads -v p='{}/{%}' \
'bwa mem -t {j} -M -a {ref} {p}_1.fq.gz {p}_2.fq.gz >{p}.sam;\
samtools view -bS {p}.sam > {p}.bam; \
samtools sort -T {p}.tmp -@ {j} {p}.bam -o {p}.sorted.bam; \
samtools index {p}.sorted.bam; \
samtools flagstat {p}.sorted.bam > {p}.sorted.bam.flagstat; \
/bin/rm {p}.bam {p}.sam;' \
-j 2 --verbose -c -C mapping.rush
GNU parallel would use a function:
18$ ref=ref/xxx.fa
export ref
thr=25
export thr
bwa_sam() {
p="$1"
bam="$p".bam
sam="$p".sam
sortbam="$p".sorted.bam
bwa mem -t $thr -M -a $ref ${p}_1.fq.gz ${p}_2.fq.gz > "$sam"
samtools view -bS "$sam" > "$bam"
samtools sort -T ${p}.tmp -@ $thr "$bam" -o "$sortbam"
samtools index "$sortbam"
samtools flagstat "$sortbam" > "$sortbam".flagstat
/bin/rm "$bam" "$sam"
}
export -f bwa_sam
ls -d raw.cluster.clean.mapping/* |
parallel -j 2 --verbose --joblog mylog bwa_sam
Other rush features
rush has:
• awk -v like custom defined variables (-v)
With GNU parallel you would simply set a shell variable:
parallel 'v={}; echo "$v"' ::: foo
echo foo | rush -v v={} 'echo {v}'
Also rush does not like special chars. So these do not work:
echo does not work | rush -v v=\" 'echo {v}'
echo "My brother's 12\" records" | rush -v v={} 'echo {v}'
Whereas the corresponding GNU parallel version works:
parallel 'v=\"; echo "$v"' ::: works
parallel 'v={}; echo "$v"' ::: "My brother's 12\" records"
• Exit on first error(s) (-e)
This is called --halt now,fail=1 (or shorter: --halt 2) when used with GNU parallel.
• Settable records sending to every command (-n, default 1)
This is also called -n in GNU parallel.
• Practical replacement strings
{:} remove any extension
With GNU parallel this can be emulated by:
parallel --plus echo '{/\..*/}' ::: foo.ext.bar.gz
{^suffix}, remove suffix
With GNU parallel this can be emulated by:
parallel --plus echo '{%.bar.gz}' ::: foo.ext.bar.gz
{@regexp}, capture submatch using regular expression
With GNU parallel this can be emulated by:
parallel --rpl '{@(.*?)} /$$1/ and $_=$1;' \
echo '{@\d_(.*).gz}' ::: 1_foo.gz
{%.}, {%:}, basename without extension
With GNU parallel this can be emulated by:
parallel echo '{= s:.*/::;s/\..*// =}' ::: dir/foo.bar.gz
And if you need it often, you define a --rpl in $HOME/.parallel/config:
--rpl '{%.} s:.*/::;s/\..*//'
--rpl '{%:} s:.*/::;s/\..*//'
Then you can use them as:
parallel echo {%.} {%:} ::: dir/foo.bar.gz
• Preset variable (macro)
E.g.
echo foosuffix | rush -v p={^suffix} 'echo {p}_new_suffix'
With GNU parallel this can be emulated by:
echo foosuffix |
parallel --plus 'p={%suffix}; echo ${p}_new_suffix'
Opposite rush GNU parallel works fine if the input contains double space, ' and ":
echo "1'6\" foosuffix" |
parallel --plus 'p={%suffix}; echo "${p}"_new_suffix'
• Commands of multi-lines
While you can use multi-lined commands in GNU parallel, to improve readability GNU
parallel discourages the use of multi-line commands. In most cases it can be written
as a function:
seq 1 3 |
parallel --timeout 2 --joblog my.log 'sleep {}; echo {}; \
echo finish {}'
Could be written as:
doit() {
sleep "$1"
echo "$1"
echo finish "$1"
}
export -f doit
seq 1 3 | parallel --timeout 2 --joblog my.log doit
The failed commands can be resumed with:
seq 1 3 |
parallel --resume-failed --joblog my.log 'sleep {}; echo {};\
echo finish {}'
https://github.com/shenwei356/rush
DIFFERENCES BETWEEN ClusterSSH AND GNU Parallel
ClusterSSH solves a different problem than GNU parallel.
ClusterSSH opens a terminal window for each computer and using a master window you can run
the same command on all the computers. This is typically used for administrating several
computers that are almost identical.
GNU parallel runs the same (or different) commands with different arguments in parallel
possibly using remote computers to help computing. If more than one computer is listed in
-S GNU parallel may only use one of these (e.g. if there are 8 jobs to be run and one
computer has 8 cores).
GNU parallel can be used as a poor-man's version of ClusterSSH:
parallel --nonall -S server-a,server-b do_stuff foo bar
https://github.com/duncs/clusterssh
DIFFERENCES BETWEEN coshell AND GNU Parallel
coshell only accepts full commands on standard input. Any quoting needs to be done by the
user.
Commands are run in sh so any bash/tcsh/zsh specific syntax will not work.
Output can be buffered by using -d. Output is buffered in memory, so big output can cause
swapping and therefore be terrible slow or even cause out of memory.
https://github.com/gdm85/coshell (Last checked: 2019-01)
DIFFERENCES BETWEEN spread AND GNU Parallel
spread runs commands on all directories.
It can be emulated with GNU parallel using this Bash function:
spread() {
_cmds() {
perl -e '$"=" && ";print "@ARGV"' "cd {}" "$@"
}
parallel $(_cmds "$@")'|| echo exit status $?' ::: */
}
This works except for the --exclude option.
(Last checked: 2017-11)
DIFFERENCES BETWEEN pyargs AND GNU Parallel
pyargs deals badly with input containing spaces. It buffers stdout, but not stderr. It
buffers in RAM. {} does not work as replacement string. It does not support running
functions.
pyargs does not support composed commands if run with --lines, and fails on pyargs
traceroute gnu.org fsf.org.
Examples
seq 5 | pyargs -P50 -L seq
seq 5 | parallel -P50 --lb seq
seq 5 | pyargs -P50 --mark -L seq
seq 5 | parallel -P50 --lb \
--tagstring OUTPUT'[{= $_=$job->replaced()=}]' seq
# Similar, but not precisely the same
seq 5 | parallel -P50 --lb --tag seq
seq 5 | pyargs -P50 --mark command
# Somewhat longer with GNU Parallel due to the special
# --mark formatting
cmd="$(echo "command" | parallel --shellquote)"
wrap_cmd() {
echo "MARK $cmd $@================================" >&3
echo "OUTPUT START[$cmd $@]:"
eval $cmd "$@"
echo "OUTPUT END[$cmd $@]"
}
(seq 5 | env_parallel -P2 wrap_cmd) 3>&1
# Similar, but not exactly the same
seq 5 | parallel -t --tag command
(echo '1 2 3';echo 4 5 6) | pyargs --stream seq
(echo '1 2 3';echo 4 5 6) | perl -pe 's/\n/ /' |
parallel -r -d' ' seq
# Similar, but not exactly the same
parallel seq ::: 1 2 3 4 5 6
https://github.com/robertblackwell/pyargs (Last checked: 2019-01)
DIFFERENCES BETWEEN concurrently AND GNU Parallel
concurrently runs jobs in parallel.
The output is prepended with the job number, and may be incomplete:
$ concurrently 'seq 100000' | (sleep 3;wc -l)
7165
When pretty printing it caches output in memory. Output mixes by using test MIX below
whether or not output is cached.
There seems to be no way of making a template command and have concurrently fill that with
different args. The full commands must be given on the command line.
There is also no way of controlling how many jobs should be run in parallel at a time -
i.e. "number of jobslots". Instead all jobs are simply started in parallel.
https://github.com/kimmobrunfeldt/concurrently (Last checked: 2019-01)
DIFFERENCES BETWEEN map(soveran) AND GNU Parallel
map does not run jobs in parallel by default. The README suggests using:
... | map t 'sleep $t && say done &'
But this fails if more jobs are run in parallel than the number of available processes.
Since there is no support for parallelization in map itself, the output also mixes:
seq 10 | map i 'echo start-$i && sleep 0.$i && echo end-$i &'
The major difference is that GNU parallel is built for parallelization and map is not. So
GNU parallel has lots of ways of dealing with the issues that parallelization raises:
• Keep the number of processes manageable
• Make sure output does not mix
• Make Ctrl-C kill all running processes
EXAMPLES FROM maps WEBSITE
Here are the 5 examples converted to GNU Parallel:
1$ ls *.c | map f 'foo $f'
1$ ls *.c | parallel foo
2$ ls *.c | map f 'foo $f; bar $f'
2$ ls *.c | parallel 'foo {}; bar {}'
3$ cat urls | map u 'curl -O $u'
3$ cat urls | parallel curl -O
4$ printf "1\n1\n1\n" | map t 'sleep $t && say done'
4$ printf "1\n1\n1\n" | parallel 'sleep {} && say done'
4$ parallel 'sleep {} && say done' ::: 1 1 1
5$ printf "1\n1\n1\n" | map t 'sleep $t && say done &'
5$ printf "1\n1\n1\n" | parallel -j0 'sleep {} && say done'
5$ parallel -j0 'sleep {} && say done' ::: 1 1 1
https://github.com/soveran/map (Last checked: 2019-01)
DIFFERENCES BETWEEN loop AND GNU Parallel
loop mixes stdout and stderr:
loop 'ls /no-such-file' >/dev/null
loop's replacement string $ITEM does not quote strings:
echo 'two spaces' | loop 'echo $ITEM'
loop cannot run functions:
myfunc() { echo joe; }
export -f myfunc
loop 'myfunc this fails'
EXAMPLES FROM loop's WEBSITE
Some of the examples from https://github.com/Miserlou/Loop/ can be emulated with GNU
parallel:
# A couple of functions will make the code easier to read
$ loopy() {
yes | parallel -uN0 -j1 "$@"
}
$ export -f loopy
$ time_out() {
parallel -uN0 -q --timeout "$@" ::: 1
}
$ match() {
perl -0777 -ne 'grep /'"$1"'/,$_ and print or exit 1'
}
$ export -f match
$ loop 'ls' --every 10s
$ loopy --delay 10s ls
$ loop 'touch $COUNT.txt' --count-by 5
$ loopy touch '{= $_=seq()*5 =}'.txt
$ loop --until-contains 200 -- \
./get_response_code.sh --site mysite.biz`
$ loopy --halt now,success=1 \
'./get_response_code.sh --site mysite.biz | match 200'
$ loop './poke_server' --for-duration 8h
$ time_out 8h loopy ./poke_server
$ loop './poke_server' --until-success
$ loopy --halt now,success=1 ./poke_server
$ cat files_to_create.txt | loop 'touch $ITEM'
$ cat files_to_create.txt | parallel touch {}
$ loop 'ls' --for-duration 10min --summary
# --joblog is somewhat more verbose than --summary
$ time_out 10m loopy --joblog my.log ./poke_server; cat my.log
$ loop 'echo hello'
$ loopy echo hello
$ loop 'echo $COUNT'
# GNU Parallel counts from 1
$ loopy echo {#}
# Counting from 0 can be forced
$ loopy echo '{= $_=seq()-1 =}'
$ loop 'echo $COUNT' --count-by 2
$ loopy echo '{= $_=2*(seq()-1) =}'
$ loop 'echo $COUNT' --count-by 2 --offset 10
$ loopy echo '{= $_=10+2*(seq()-1) =}'
$ loop 'echo $COUNT' --count-by 1.1
# GNU Parallel rounds 3.3000000000000003 to 3.3
$ loopy echo '{= $_=1.1*(seq()-1) =}'
$ loop 'echo $COUNT $ACTUALCOUNT' --count-by 2
$ loopy echo '{= $_=2*(seq()-1) =} {#}'
$ loop 'echo $COUNT' --num 3 --summary
# --joblog is somewhat more verbose than --summary
$ seq 3 | parallel --joblog my.log echo; cat my.log
$ loop 'ls -foobarbatz' --num 3 --summary
# --joblog is somewhat more verbose than --summary
$ seq 3 | parallel --joblog my.log -N0 ls -foobarbatz; cat my.log
$ loop 'echo $COUNT' --count-by 2 --num 50 --only-last
# Can be emulated by running 2 jobs
$ seq 49 | parallel echo '{= $_=2*(seq()-1) =}' >/dev/null
$ echo 50| parallel echo '{= $_=2*(seq()-1) =}'
$ loop 'date' --every 5s
$ loopy --delay 5s date
$ loop 'date' --for-duration 8s --every 2s
$ time_out 8s loopy --delay 2s date
$ loop 'date -u' --until-time '2018-05-25 20:50:00' --every 5s
$ seconds=$((`date -d 2019-05-25T20:50:00 +%s` - `date +%s`))s
$ time_out $seconds loopy --delay 5s date -u
$ loop 'echo $RANDOM' --until-contains "666"
$ loopy --halt now,success=1 'echo $RANDOM | match 666'
$ loop 'if (( RANDOM % 2 )); then
(echo "TRUE"; true);
else
(echo "FALSE"; false);
fi' --until-success
$ loopy --halt now,success=1 'if (( $RANDOM % 2 )); then
(echo "TRUE"; true);
else
(echo "FALSE"; false);
fi'
$ loop 'if (( RANDOM % 2 )); then
(echo "TRUE"; true);
else
(echo "FALSE"; false);
fi' --until-error
$ loopy --halt now,fail=1 'if (( $RANDOM % 2 )); then
(echo "TRUE"; true);
else
(echo "FALSE"; false);
fi'
$ loop 'date' --until-match "(\d{4})"
$ loopy --halt now,success=1 'date | match [0-9][0-9][0-9][0-9]'
$ loop 'echo $ITEM' --for red,green,blue
$ parallel echo ::: red green blue
$ cat /tmp/my-list-of-files-to-create.txt | loop 'touch $ITEM'
$ cat /tmp/my-list-of-files-to-create.txt | parallel touch
$ ls | loop 'cp $ITEM $ITEM.bak'; ls
$ ls | parallel cp {} {}.bak; ls
$ loop 'echo $ITEM | tr a-z A-Z' -i
$ parallel 'echo {} | tr a-z A-Z'
# Or more efficiently:
$ parallel --pipe tr a-z A-Z
$ loop 'echo $ITEM' --for "`ls`"
$ parallel echo {} ::: "`ls`"
$ ls | loop './my_program $ITEM' --until-success;
$ ls | parallel --halt now,success=1 ./my_program {}
$ ls | loop './my_program $ITEM' --until-fail;
$ ls | parallel --halt now,fail=1 ./my_program {}
$ ./deploy.sh;
loop 'curl -sw "%{http_code}" http://coolwebsite.biz' \
--every 5s --until-contains 200;
./announce_to_slack.sh
$ ./deploy.sh;
loopy --delay 5s --halt now,success=1 \
'curl -sw "%{http_code}" http://coolwebsite.biz | match 200';
./announce_to_slack.sh
$ loop "ping -c 1 mysite.com" --until-success; ./do_next_thing
$ loopy --halt now,success=1 ping -c 1 mysite.com; ./do_next_thing
$ ./create_big_file -o my_big_file.bin;
loop 'ls' --until-contains 'my_big_file.bin';
./upload_big_file my_big_file.bin
# inotifywait is a better tool to detect file system changes.
# It can even make sure the file is complete
# so you are not uploading an incomplete file
$ inotifywait -qmre MOVED_TO -e CLOSE_WRITE --format %w%f . |
grep my_big_file.bin
$ ls | loop 'cp $ITEM $ITEM.bak'
$ ls | parallel cp {} {}.bak
$ loop './do_thing.sh' --every 15s --until-success --num 5
$ parallel --retries 5 --delay 15s ::: ./do_thing.sh
https://github.com/Miserlou/Loop/ (Last checked: 2018-10)
DIFFERENCES BETWEEN lorikeet AND GNU Parallel
lorikeet can run jobs in parallel. It does this based on a dependency graph described in a
file, so this is similar to make.
https://github.com/cetra3/lorikeet (Last checked: 2018-10)
DIFFERENCES BETWEEN spp AND GNU Parallel
spp can run jobs in parallel. spp does not use a command template to generate the jobs,
but requires jobs to be in a file. Output from the jobs mix.
https://github.com/john01dav/spp (Last checked: 2019-01)
DIFFERENCES BETWEEN paral AND GNU Parallel
paral prints a lot of status information and stores the output from the commands run into
files. This means it cannot be used the middle of a pipe like this
paral "echo this" "echo does not" "echo work" | wc
Instead it puts the output into files named like out_#_command.out.log. To get a very
similar behaviour with GNU parallel use --results
'out_{#}_{=s/[^\sa-z_0-9]//g;s/\s+/_/g=}.log' --eta
paral only takes arguments on the command line and each argument should be a full command.
Thus it does not use command templates.
This limits how many jobs it can run in total, because they all need to fit on a single
command line.
paral has no support for running jobs remotely.
EXAMPLES FROM README.markdown
The examples from README.markdown and the corresponding command run with GNU parallel
(--results 'out_{#}_{=s/[^\sa-z_0-9]//g;s/\s+/_/g=}.log' --eta is omitted from the GNU
parallel command):
1$ paral "command 1" "command 2 --flag" "command arg1 arg2"
1$ parallel ::: "command 1" "command 2 --flag" "command arg1 arg2"
2$ paral "sleep 1 && echo c1" "sleep 2 && echo c2" \
"sleep 3 && echo c3" "sleep 4 && echo c4" "sleep 5 && echo c5"
2$ parallel ::: "sleep 1 && echo c1" "sleep 2 && echo c2" \
"sleep 3 && echo c3" "sleep 4 && echo c4" "sleep 5 && echo c5"
# Or shorter:
parallel "sleep {} && echo c{}" ::: {1..5}
3$ paral -n=0 "sleep 5 && echo c5" "sleep 4 && echo c4" \
"sleep 3 && echo c3" "sleep 2 && echo c2" "sleep 1 && echo c1"
3$ parallel ::: "sleep 5 && echo c5" "sleep 4 && echo c4" \
"sleep 3 && echo c3" "sleep 2 && echo c2" "sleep 1 && echo c1"
# Or shorter:
parallel -j0 "sleep {} && echo c{}" ::: 5 4 3 2 1
4$ paral -n=1 "sleep 5 && echo c5" "sleep 4 && echo c4" \
"sleep 3 && echo c3" "sleep 2 && echo c2" "sleep 1 && echo c1"
4$ parallel -j1 "sleep {} && echo c{}" ::: 5 4 3 2 1
5$ paral -n=2 "sleep 5 && echo c5" "sleep 4 && echo c4" \
"sleep 3 && echo c3" "sleep 2 && echo c2" "sleep 1 && echo c1"
5$ parallel -j2 "sleep {} && echo c{}" ::: 5 4 3 2 1
6$ paral -n=5 "sleep 5 && echo c5" "sleep 4 && echo c4" \
"sleep 3 && echo c3" "sleep 2 && echo c2" "sleep 1 && echo c1"
6$ parallel -j5 "sleep {} && echo c{}" ::: 5 4 3 2 1
7$ paral -n=1 "echo a && sleep 0.5 && echo b && sleep 0.5 && \
echo c && sleep 0.5 && echo d && sleep 0.5 && \
echo e && sleep 0.5 && echo f && sleep 0.5 && \
echo g && sleep 0.5 && echo h"
7$ parallel ::: "echo a && sleep 0.5 && echo b && sleep 0.5 && \
echo c && sleep 0.5 && echo d && sleep 0.5 && \
echo e && sleep 0.5 && echo f && sleep 0.5 && \
echo g && sleep 0.5 && echo h"
https://github.com/amattn/paral (Last checked: 2019-01)
DIFFERENCES BETWEEN concurr AND GNU Parallel
concurr is built to run jobs in parallel using a client/server model.
EXAMPLES FROM README.md
The examples from README.md:
1$ concurr 'echo job {#} on slot {%}: {}' : arg1 arg2 arg3 arg4
1$ parallel 'echo job {#} on slot {%}: {}' ::: arg1 arg2 arg3 arg4
2$ concurr 'echo job {#} on slot {%}: {}' :: file1 file2 file3
2$ parallel 'echo job {#} on slot {%}: {}' :::: file1 file2 file3
3$ concurr 'echo {}' < input_file
3$ parallel 'echo {}' < input_file
4$ cat file | concurr 'echo {}'
4$ cat file | parallel 'echo {}'
concurr deals badly empty input files and with output larger than 64 KB.
https://github.com/mmstick/concurr (Last checked: 2019-01)
DIFFERENCES BETWEEN lesser-parallel AND GNU Parallel
lesser-parallel is the inspiration for parallel --embed. Both lesser-parallel and parallel
--embed define bash functions that can be included as part of a bash script to run jobs in
parallel.
lesser-parallel implements a few of the replacement strings, but hardly any options,
whereas parallel --embed gives you the full GNU parallel experience.
https://github.com/kou1okada/lesser-parallel (Last checked: 2019-01)
DIFFERENCES BETWEEN npm-parallel AND GNU Parallel
npm-parallel can run npm tasks in parallel.
There are no examples and very little documentation, so it is hard to compare to GNU
parallel.
https://github.com/spion/npm-parallel (Last checked: 2019-01)
DIFFERENCES BETWEEN machma AND GNU Parallel
machma runs tasks in parallel. It gives time stamped output. It buffers in RAM.
EXAMPLES FROM README.md
The examples from README.md:
1$ # Put shorthand for timestamp in config for the examples
echo '--rpl '\
\''{time} $_=::strftime("%Y-%m-%d %H:%M:%S",localtime())'\' \
> ~/.parallel/machma
echo '--line-buffer --tagstring "{#} {time} {}"' \
>> ~/.parallel/machma
2$ find . -iname '*.jpg' |
machma -- mogrify -resize 1200x1200 -filter Lanczos {}
find . -iname '*.jpg' |
parallel --bar -Jmachma mogrify -resize 1200x1200 \
-filter Lanczos {}
3$ cat /tmp/ips | machma -p 2 -- ping -c 2 -q {}
3$ cat /tmp/ips | parallel -j2 -Jmachma ping -c 2 -q {}
4$ cat /tmp/ips |
machma -- sh -c 'ping -c 2 -q $0 > /dev/null && echo alive' {}
4$ cat /tmp/ips |
parallel -Jmachma 'ping -c 2 -q {} > /dev/null && echo alive'
5$ find . -iname '*.jpg' |
machma --timeout 5s -- mogrify -resize 1200x1200 \
-filter Lanczos {}
5$ find . -iname '*.jpg' |
parallel --timeout 5s --bar mogrify -resize 1200x1200 \
-filter Lanczos {}
6$ find . -iname '*.jpg' -print0 |
machma --null -- mogrify -resize 1200x1200 -filter Lanczos {}
6$ find . -iname '*.jpg' -print0 |
parallel --null --bar mogrify -resize 1200x1200 \
-filter Lanczos {}
https://github.com/fd0/machma (Last checked: 2019-06)
DIFFERENCES BETWEEN interlace AND GNU Parallel
Summary (see legend above):
- I2 I3 I4 - - -
M1 - M3 - - M6
- O2 O3 - - - - x x
E1 E2 - - - - -
- - - - - - - - -
- -
interlace is built for network analysis to run network tools in parallel.
interface does not buffer output, so output from different jobs mixes.
The overhead for each target is O(n*n), so with 1000 targets it becomes very slow with an
overhead in the order of 500ms/target.
EXAMPLES FROM interlace's WEBSITE
Using prips most of the examples from https://github.com/codingo/Interlace can be run with
GNU parallel:
Blocker
commands.txt:
mkdir -p _output_/_target_/scans/
_blocker_
nmap _target_ -oA _output_/_target_/scans/_target_-nmap
interlace -tL ./targets.txt -cL commands.txt -o $output
parallel -a targets.txt \
mkdir -p $output/{}/scans/\; nmap {} -oA $output/{}/scans/{}-nmap
Blocks
commands.txt:
_block:nmap_
mkdir -p _target_/output/scans/
nmap _target_ -oN _target_/output/scans/_target_-nmap
_block:nmap_
nikto --host _target_
interlace -tL ./targets.txt -cL commands.txt
_nmap() {
mkdir -p $1/output/scans/
nmap $1 -oN $1/output/scans/$1-nmap
}
export -f _nmap
parallel ::: _nmap "nikto --host" :::: targets.txt
Run Nikto Over Multiple Sites
interlace -tL ./targets.txt -threads 5 \
-c "nikto --host _target_ > ./_target_-nikto.txt" -v
parallel -a targets.txt -P5 nikto --host {} \> ./{}_-nikto.txt
Run Nikto Over Multiple Sites and Ports
interlace -tL ./targets.txt -threads 5 -c \
"nikto --host _target_:_port_ > ./_target_-_port_-nikto.txt" \
-p 80,443 -v
parallel -P5 nikto --host {1}:{2} \> ./{1}-{2}-nikto.txt \
:::: targets.txt ::: 80 443
Run a List of Commands against Target Hosts
commands.txt:
nikto --host _target_:_port_ > _output_/_target_-nikto.txt
sslscan _target_:_port_ > _output_/_target_-sslscan.txt
testssl.sh _target_:_port_ > _output_/_target_-testssl.txt
interlace -t example.com -o ~/Engagements/example/ \
-cL ./commands.txt -p 80,443
parallel --results ~/Engagements/example/{2}:{3}{1} {1} {2}:{3} \
::: "nikto --host" sslscan testssl.sh ::: example.com ::: 80 443
CIDR notation with an application that doesn't support it
interlace -t 192.168.12.0/24 -c "vhostscan _target_ \
-oN _output_/_target_-vhosts.txt" -o ~/scans/ -threads 50
prips 192.168.12.0/24 |
parallel -P50 vhostscan {} -oN ~/scans/{}-vhosts.txt
Glob notation with an application that doesn't support it
interlace -t 192.168.12.* -c "vhostscan _target_ \
-oN _output_/_target_-vhosts.txt" -o ~/scans/ -threads 50
# Glob is not supported in prips
prips 192.168.12.0/24 |
parallel -P50 vhostscan {} -oN ~/scans/{}-vhosts.txt
Dash (-) notation with an application that doesn't support it
interlace -t 192.168.12.1-15 -c \
"vhostscan _target_ -oN _output_/_target_-vhosts.txt" \
-o ~/scans/ -threads 50
# Dash notation is not supported in prips
prips 192.168.12.1 192.168.12.15 |
parallel -P50 vhostscan {} -oN ~/scans/{}-vhosts.txt
Threading Support for an application that doesn't support it
interlace -tL ./target-list.txt -c \
"vhostscan -t _target_ -oN _output_/_target_-vhosts.txt" \
-o ~/scans/ -threads 50
cat ./target-list.txt |
parallel -P50 vhostscan -t {} -oN ~/scans/{}-vhosts.txt
alternatively
./vhosts-commands.txt:
vhostscan -t $target -oN _output_/_target_-vhosts.txt
interlace -cL ./vhosts-commands.txt -tL ./target-list.txt \
-threads 50 -o ~/scans
./vhosts-commands.txt:
vhostscan -t "$1" -oN "$2"
parallel -P50 ./vhosts-commands.txt {} ~/scans/{}-vhosts.txt \
:::: ./target-list.txt
Exclusions
interlace -t 192.168.12.0/24 -e 192.168.12.0/26 -c \
"vhostscan _target_ -oN _output_/_target_-vhosts.txt" \
-o ~/scans/ -threads 50
prips 192.168.12.0/24 | grep -xv -Ff <(prips 192.168.12.0/26) |
parallel -P50 vhostscan {} -oN ~/scans/{}-vhosts.txt
Run Nikto Using Multiple Proxies
interlace -tL ./targets.txt -pL ./proxies.txt -threads 5 -c \
"nikto --host _target_:_port_ -useproxy _proxy_ > \
./_target_-_port_-nikto.txt" -p 80,443 -v
parallel -j5 \
"nikto --host {1}:{2} -useproxy {3} > ./{1}-{2}-nikto.txt" \
:::: ./targets.txt ::: 80 443 :::: ./proxies.txt
https://github.com/codingo/Interlace (Last checked: 2019-09)
DIFFERENCES BETWEEN otonvm Parallel AND GNU Parallel
I have been unable to get the code to run at all. It seems unfinished.
https://github.com/otonvm/Parallel (Last checked: 2019-02)
DIFFERENCES BETWEEN k-bx par AND GNU Parallel
par requires Haskell to work. This limits the number of platforms this can work on.
par does line buffering in memory. The memory usage is 3x the longest line (compared to 1x
for parallel --lb). Commands must be given as arguments. There is no template.
These are the examples from https://github.com/k-bx/par with the corresponding GNU
parallel command.
par "echo foo; sleep 1; echo foo; sleep 1; echo foo" \
"echo bar; sleep 1; echo bar; sleep 1; echo bar" && echo "success"
parallel --lb ::: "echo foo; sleep 1; echo foo; sleep 1; echo foo" \
"echo bar; sleep 1; echo bar; sleep 1; echo bar" && echo "success"
par "echo foo; sleep 1; foofoo" \
"echo bar; sleep 1; echo bar; sleep 1; echo bar" && echo "success"
parallel --lb --halt 1 ::: "echo foo; sleep 1; foofoo" \
"echo bar; sleep 1; echo bar; sleep 1; echo bar" && echo "success"
par "PARPREFIX=[fooechoer] echo foo" "PARPREFIX=[bar] echo bar"
parallel --lb --colsep , --tagstring {1} {2} \
::: "[fooechoer],echo foo" "[bar],echo bar"
par --succeed "foo" "bar" && echo 'wow'
parallel "foo" "bar"; true && echo 'wow'
https://github.com/k-bx/par (Last checked: 2019-02)
DIFFERENCES BETWEEN parallelshell AND GNU Parallel
parallelshell does not allow for composed commands:
# This does not work
parallelshell 'echo foo;echo bar' 'echo baz;echo quuz'
Instead you have to wrap that in a shell:
parallelshell 'sh -c "echo foo;echo bar"' 'sh -c "echo baz;echo quuz"'
It buffers output in RAM. All commands must be given on the command line and all commands
are started in parallel at the same time. This will cause the system to freeze if there
are so many jobs that there is not enough memory to run them all at the same time.
https://github.com/keithamus/parallelshell (Last checked: 2019-02)
https://github.com/darkguy2008/parallelshell (Last checked: 2019-03)
DIFFERENCES BETWEEN shell-executor AND GNU Parallel
shell-executor does not allow for composed commands:
# This does not work
sx 'echo foo;echo bar' 'echo baz;echo quuz'
Instead you have to wrap that in a shell:
sx 'sh -c "echo foo;echo bar"' 'sh -c "echo baz;echo quuz"'
It buffers output in RAM. All commands must be given on the command line and all commands
are started in parallel at the same time. This will cause the system to freeze if there
are so many jobs that there is not enough memory to run them all at the same time.
https://github.com/royriojas/shell-executor (Last checked: 2019-02)
DIFFERENCES BETWEEN non-GNU par AND GNU Parallel
par buffers in memory to avoid mixing of jobs. It takes 1s per 1 million output lines.
par needs to have all commands before starting the first job. The jobs are read from stdin
(standard input) so any quoting will have to be done by the user.
Stdout (standard output) is prepended with o:. Stderr (standard error) is sendt to stdout
(standard output) and prepended with e:.
For short jobs with little output par is 20% faster than GNU parallel and 60% slower than
xargs.
https://github.com/UnixJunkie/PAR
https://savannah.nongnu.org/projects/par (Last checked: 2019-02)
DIFFERENCES BETWEEN fd AND GNU Parallel
fd does not support composed commands, so commands must be wrapped in sh -c.
It buffers output in RAM.
It only takes file names from the filesystem as input (similar to find).
https://github.com/sharkdp/fd (Last checked: 2019-02)
DIFFERENCES BETWEEN lateral AND GNU Parallel
lateral is very similar to sem: It takes a single command and runs it in the background.
The design means that output from parallel running jobs may mix. If it dies unexpectly it
leaves a socket in ~/.lateral/socket.PID.
lateral deals badly with too long command lines. This makes the lateral server crash:
lateral run echo `seq 100000| head -c 1000k`
Any options will be read by lateral so this does not work (lateral interprets the -l):
lateral run ls -l
Composed commands do not work:
lateral run pwd ';' ls
Functions do not work:
myfunc() { echo a; }
export -f myfunc
lateral run myfunc
Running emacs in the terminal causes the parent shell to die:
echo '#!/bin/bash' > mycmd
echo emacs -nw >> mycmd
chmod +x mycmd
lateral start
lateral run ./mycmd
Here are the examples from https://github.com/akramer/lateral with the corresponding GNU
sem and GNU parallel commands:
1$ lateral start
for i in $(cat /tmp/names); do
lateral run -- some_command $i
done
lateral wait
1$ for i in $(cat /tmp/names); do
sem some_command $i
done
sem --wait
1$ parallel some_command :::: /tmp/names
2$ lateral start
for i in $(seq 1 100); do
lateral run -- my_slow_command < workfile$i > /tmp/logfile$i
done
lateral wait
2$ for i in $(seq 1 100); do
sem my_slow_command < workfile$i > /tmp/logfile$i
done
sem --wait
2$ parallel 'my_slow_command < workfile{} > /tmp/logfile{}' \
::: {1..100}
3$ lateral start -p 0 # yup, it will just queue tasks
for i in $(seq 1 100); do
lateral run -- command_still_outputs_but_wont_spam inputfile$i
done
# command output spam can commence
lateral config -p 10; lateral wait
3$ for i in $(seq 1 100); do
echo "command inputfile$i" >> joblist
done
parallel -j 10 :::: joblist
3$ echo 1 > /tmp/njobs
parallel -j /tmp/njobs command inputfile{} \
::: {1..100} &
echo 10 >/tmp/njobs
wait
https://github.com/akramer/lateral (Last checked: 2019-03)
DIFFERENCES BETWEEN with-this AND GNU Parallel
The examples from https://github.com/amritb/with-this.git and the corresponding GNU
parallel command:
with -v "$(cat myurls.txt)" "curl -L this"
parallel curl -L ::: myurls.txt
with -v "$(cat myregions.txt)" \
"aws --region=this ec2 describe-instance-status"
parallel aws --region={} ec2 describe-instance-status \
:::: myregions.txt
with -v "$(ls)" "kubectl --kubeconfig=this get pods"
ls | parallel kubectl --kubeconfig={} get pods
with -v "$(ls | grep config)" "kubectl --kubeconfig=this get pods"
ls | grep config | parallel kubectl --kubeconfig={} get pods
with -v "$(echo {1..10})" "echo 123"
parallel -N0 echo 123 ::: {1..10}
Stderr is merged with stdout. with-this buffers in RAM. It uses 3x the output size, so you
cannot have output larger than 1/3rd the amount of RAM. The input values cannot contain
spaces. Composed commands do not work.
with-this gives some additional information, so the output has to be cleaned before piping
it to the next command.
https://github.com/amritb/with-this.git (Last checked: 2019-03)
DIFFERENCES BETWEEN Tollef's parallel (moreutils) AND GNU Parallel
Summary (see legend above):
- - - I4 - - I7
- - M3 - - M6
- O2 O3 - O5 O6 - x x
E1 - - - - - E7
- x x x x x x x x
- -
EXAMPLES FROM Tollef's parallel MANUAL
Tollef parallel sh -c "echo hi; sleep 2; echo bye" -- 1 2 3
GNU parallel "echo hi; sleep 2; echo bye" ::: 1 2 3
Tollef parallel -j 3 ufraw -o processed -- *.NEF
GNU parallel -j 3 ufraw -o processed ::: *.NEF
Tollef parallel -j 3 -- ls df "echo hi"
GNU parallel -j 3 ::: ls df "echo hi"
(Last checked: 2019-08)
DIFFERENCES BETWEEN rargs AND GNU Parallel
Summary (see legend above):
I1 - - - - - I7
- - M3 M4 - -
- O2 O3 - O5 O6 - O8 -
E1 - - E4 - - -
- - - - - - - - -
- -
rargs has elegant ways of doing named regexp capture and field ranges.
With GNU parallel you can use --rpl to get a similar functionality as regexp capture
gives, and use join and @arg to get the field ranges. But the syntax is longer. This:
--rpl '{r(\d+)\.\.(\d+)} $_=join"$opt::colsep",@arg[$$1..$$2]'
would make it possible to use:
{1r3..6}
for field 3..6.
For full support of {n..m:s} including negative numbers use a dynamic replacement string
like this:
PARALLEL=--rpl\ \''{r((-?\d+)?)\.\.((-?\d+)?)((:([^}]*))?)}
$a = defined $$2 ? $$2 < 0 ? 1+$#arg+$$2 : $$2 : 1;
$b = defined $$4 ? $$4 < 0 ? 1+$#arg+$$4 : $$4 : $#arg+1;
$s = defined $$6 ? $$7 : " ";
$_ = join $s,@arg[$a..$b]'\'
export PARALLEL
You can then do:
head /etc/passwd | parallel --colsep : echo ..={1r..} ..3={1r..3} \
4..={1r4..} 2..4={1r2..4} 3..3={1r3..3} ..3:-={1r..3:-} \
..3:/={1r..3:/} -1={-1} -5={-5} -6={-6} -3..={1r-3..}
EXAMPLES FROM rargs MANUAL
ls *.bak | rargs -p '(.*)\.bak' mv {0} {1}
ls *.bak | parallel mv {} {.}
cat download-list.csv | rargs -p '(?P<url>.*),(?P<filename>.*)' wget {url} -O {filename}
cat download-list.csv | parallel --csv wget {1} -O {2}
# or use regexps:
cat download-list.csv |
parallel --rpl '{url} s/,.*//' --rpl '{filename} s/.*?,//' wget {url} -O {filename}
cat /etc/passwd | rargs -d: echo -e 'id: "{1}"\t name: "{5}"\t rest: "{6..::}"'
cat /etc/passwd |
parallel -q --colsep : echo -e 'id: "{1}"\t name: "{5}"\t rest: "{=6 $_=join":",@arg[6..$#arg]=}"'
https://github.com/lotabout/rargs (Last checked: 2020-01)
DIFFERENCES BETWEEN threader AND GNU Parallel
Summary (see legend above):
I1 - - - - - -
M1 - M3 - - M6
O1 - O3 - O5 - - N/A N/A
E1 - - E4 - - -
- - - - - - - - -
- -
Newline separates arguments, but newline at the end of file is treated as an empty
argument. So this runs 2 jobs:
echo two_jobs | threader -run 'echo "$THREADID"'
threader ignores stderr, so any output to stderr is lost. threader buffers in RAM, so
output bigger than the machine's virtual memory will cause the machine to crash.
https://github.com/voodooEntity/threader (Last checked: 2020-04)
DIFFERENCES BETWEEN runp AND GNU Parallel
Summary (see legend above):
I1 I2 - - - - -
M1 - (M3) - - M6
O1 O2 O3 - O5 O6 - N/A N/A -
E1 - - - - - -
- - - - - - - - -
- -
(M3): You can add a prefix and a postfix to the input, so it means you can only insert the
argument on the command line once.
runp runs 10 jobs in parallel by default. runp blocks if output of a command is > 64
Kbytes. Quoting of input is needed. It adds output to stderr (this can be prevented with
-q)
Examples as GNU Parallel
base='https://images-api.nasa.gov/search'
query='jupiter'
desc='planet'
type='image'
url="$base?q=$query&description=$desc&media_type=$type"
# Download the images in parallel using runp
curl -s $url | jq -r .collection.items[].href | \
runp -p 'curl -s' | jq -r .[] | grep large | \
runp -p 'curl -s -L -O'
time curl -s $url | jq -r .collection.items[].href | \
runp -g 1 -q -p 'curl -s' | jq -r .[] | grep large | \
runp -g 1 -q -p 'curl -s -L -O'
# Download the images in parallel
curl -s $url | jq -r .collection.items[].href | \
parallel curl -s | jq -r .[] | grep large | \
parallel curl -s -L -O
time curl -s $url | jq -r .collection.items[].href | \
parallel -j 1 curl -s | jq -r .[] | grep large | \
parallel -j 1 curl -s -L -O
Run some test commands (read from file)
# Create a file containing commands to run in parallel.
cat << EOF > /tmp/test-commands.txt
sleep 5
sleep 3
blah # this will fail
ls $PWD # PWD shell variable is used here
EOF
# Run commands from the file.
runp /tmp/test-commands.txt > /dev/null
parallel -a /tmp/test-commands.txt > /dev/null
Ping several hosts and see packet loss (read from stdin)
# First copy this line and press Enter
runp -p 'ping -c 5 -W 2' -s '| grep loss'
localhost
1.1.1.1
8.8.8.8
# Press Enter and Ctrl-D when done entering the hosts
# First copy this line and press Enter
parallel ping -c 5 -W 2 {} '| grep loss'
localhost
1.1.1.1
8.8.8.8
# Press Enter and Ctrl-D when done entering the hosts
Get directories' sizes (read from stdin)
echo -e "$HOME\n/etc\n/tmp" | runp -q -p 'sudo du -sh'
echo -e "$HOME\n/etc\n/tmp" | parallel sudo du -sh
# or:
parallel sudo du -sh ::: "$HOME" /etc /tmp
Compress files
find . -iname '*.txt' | runp -p 'gzip --best'
find . -iname '*.txt' | parallel gzip --best
Measure HTTP request + response time
export CURL="curl -w 'time_total: %{time_total}\n'"
CURL="$CURL -o /dev/null -s https://golang.org/"
perl -wE 'for (1..10) { say $ENV{CURL} }' |
runp -q # Make 10 requests
perl -wE 'for (1..10) { say $ENV{CURL} }' | parallel
# or:
parallel -N0 "$CURL" ::: {1..10}
Find open TCP ports
cat << EOF > /tmp/host-port.txt
localhost 22
localhost 80
localhost 81
127.0.0.1 443
127.0.0.1 444
scanme.nmap.org 22
scanme.nmap.org 23
scanme.nmap.org 443
EOF
1$ cat /tmp/host-port.txt |
runp -q -p 'netcat -v -w2 -z' 2>&1 | egrep '(succeeded!|open)$'
# --colsep is needed to split the line
1$ cat /tmp/host-port.txt |
parallel --colsep ' ' netcat -v -w2 -z 2>&1 |
egrep '(succeeded!|open)$'
# or use uq for unquoted:
1$ cat /tmp/host-port.txt |
parallel netcat -v -w2 -z {=uq=} 2>&1 |
egrep '(succeeded!|open)$'
https://github.com/jreisinger/runp (Last checked: 2020-04)
DIFFERENCES BETWEEN papply AND GNU Parallel
Summary (see legend above):
- - - I4 - - -
M1 - M3 - - M6
- - O3 - O5 - - N/A N/A O10
E1 - - E4 - - -
- - - - - - - - -
- -
papply does not print the output if the command fails:
$ papply 'echo %F; false' foo
"echo foo; false" did not succeed
papply's replacement strings (%F %d %f %n %e %z) can be simulated in GNU parallel by
putting this in ~/.parallel/config:
--rpl '%F'
--rpl '%d $_=Q(::dirname($_));'
--rpl '%f s:.*/::;'
--rpl '%n s:.*/::;s:\.[^/.]+$::;'
--rpl '%e s:.*\.:.:'
--rpl '%z $_=""'
papply buffers in RAM, and uses twice the amount of output. So output of 5 GB takes 10 GB
RAM.
The buffering is very CPU intensive: Buffering a line of 5 GB takes 40 seconds (compared
to 10 seconds with GNU parallel).
Examples as GNU Parallel
1$ papply gzip *.txt
1$ parallel gzip ::: *.txt
2$ papply "convert %F %n.jpg" *.png
2$ parallel convert {} {.}.jpg ::: *.png
https://pypi.org/project/papply/ (Last checked: 2020-04)
DIFFERENCES BETWEEN async AND GNU Parallel
Summary (see legend above):
- - - I4 - - I7
- - - - - M6
- O2 O3 - O5 O6 - N/A N/A O10
E1 - - E4 - E6 -
- - - - - - - - -
S1 S2
async is very similary to GNU parallel's --semaphore mode (aka sem). async requires the
user to start a server process.
The input is quoted like -q so you need bash -c "...;..." to run composed commands.
Examples as GNU Parallel
1$ S="/tmp/example_socket"
1$ ID=myid
2$ async -s="$S" server --start
2$ # GNU Parallel does not need a server to run
3$ for i in {1..20}; do
# prints command output to stdout
async -s="$S" cmd -- bash -c "sleep 1 && echo test $i"
done
3$ for i in {1..20}; do
# prints command output to stdout
sem --id "$ID" -j100% "sleep 1 && echo test $i"
# GNU Parallel will only print job when it is done
# If you need output from different jobs to mix
# use -u or --line-buffer
sem --id "$ID" -j100% --line-buffer "sleep 1 && echo test $i"
done
4$ # wait until all commands are finished
async -s="$S" wait
4$ sem --id "$ID" --wait
5$ # configure the server to run four commands in parallel
async -s="$S" server -j4
5$ export PARALLEL=-j4
6$ mkdir "/tmp/ex_dir"
for i in {21..40}; do
# redirects command output to /tmp/ex_dir/file*
async -s="$S" cmd -o "/tmp/ex_dir/file$i" -- \
bash -c "sleep 1 && echo test $i"
done
6$ mkdir "/tmp/ex_dir"
for i in {21..40}; do
# redirects command output to /tmp/ex_dir/file*
sem --id "$ID" --result '/tmp/my-ex/file-{=$_=""=}'"$i" \
"sleep 1 && echo test $i"
done
7$ sem --id "$ID" --wait
7$ async -s="$S" wait
8$ # stops server
async -s="$S" server --stop
8$ # GNU Parallel does not need to stop a server
https://github.com/ctbur/async/ (Last checked: 2020-11)
DIFFERENCES BETWEEN pardi AND GNU Parallel
Summary (see legend above):
I1 I2 - - - - I7
M1 - - - - M6
O1 O2 O3 O4 O5 - O7 - - O10
E1 - - E4 - - -
- - - - - - - - -
- -
pardi is very similar to parallel --pipe --cat: It reads blocks of data and not arguments.
So it cannot insert an argument in the command line. It puts the block into a temporary
file, and this file name (%IN) can be put in the command line. You can only use %IN once.
It can also run full command lines in parallel (like: cat file | parallel).
EXAMPLES FROM pardi test.sh
1$ time pardi -v -c 100 -i data/decoys.smi -ie .smi -oe .smi \
-o data/decoys_std_pardi.smi \
-w '(standardiser -i %IN -o %OUT 2>&1) > /dev/null'
1$ cat data/decoys.smi |
time parallel -N 100 --pipe --cat \
'(standardiser -i {} -o {#} 2>&1) > /dev/null; cat {#}; rm {#}' \
> data/decoys_std_pardi.smi
2$ pardi -n 1 -i data/test_in.types -o data/test_out.types \
-d 'r:^#atoms:' -w 'cat %IN > %OUT'
2$ cat data/test_in.types | parallel -n 1 -k --pipe --cat \
--regexp --recstart '^#atoms' 'cat {}' > data/test_out.types
3$ pardi -c 6 -i data/test_in.types -o data/test_out.types \
-d 'r:^#atoms:' -w 'cat %IN > %OUT'
3$ cat data/test_in.types | parallel -n 6 -k --pipe --cat \
--regexp --recstart '^#atoms' 'cat {}' > data/test_out.types
4$ pardi -i data/decoys.mol2 -o data/still_decoys.mol2 \
-d 's:@<TRIPOS>MOLECULE' -w 'cp %IN %OUT'
4$ cat data/decoys.mol2 |
parallel -n 1 --pipe --cat --recstart '@<TRIPOS>MOLECULE' \
'cp {} {#}; cat {#}; rm {#}' > data/still_decoys.mol2
5$ pardi -i data/decoys.mol2 -o data/decoys2.mol2 \
-d b:10000 -w 'cp %IN %OUT' --preserve
5$ cat data/decoys.mol2 |
parallel -k --pipe --block 10k --recend '' --cat \
'cat {} > {#}; cat {#}; rm {#}' > data/decoys2.mol2
https://github.com/UnixJunkie/pardi (Last checked: 2021-01)
DIFFERENCES BETWEEN bthread AND GNU Parallel
Summary (see legend above):
- - - I4 - - -
- - - - - M6
O1 - O3 - - - O7 O8 - -
E1 - - - - - -
- - - - - - - - -
- -
bthread takes around 1 sec per MB of output. The maximal output line length is 1073741759.
You cannot quote space in the command, so you cannot run composed commands like sh -c
"echo a; echo b".
https://gitlab.com/netikras/bthread (Last checked: 2021-01)
DIFFERENCES BETWEEN simple_gpu_scheduler AND GNU Parallel
Summary (see legend above):
I1 - - - - - I7
M1 - - - - M6
- O2 O3 - - O6 - x x O10
E1 - - - - - -
- - - - - - - - -
- -
EXAMPLES FROM simple_gpu_scheduler MANUAL
1$ simple_gpu_scheduler --gpus 0 1 2 < gpu_commands.txt
1$ parallel -j3 --shuf \
CUDA_VISIBLE_DEVICES='{=1 $_=slot()-1 =} {=uq;=}' < gpu_commands.txt
2$ simple_hypersearch "python3 train_dnn.py --lr {lr} --batch_size {bs}" \
-p lr 0.001 0.0005 0.0001 -p bs 32 64 128 |
simple_gpu_scheduler --gpus 0,1,2
2$ parallel --header : --shuf -j3 -v \
CUDA_VISIBLE_DEVICES='{=1 $_=slot()-1 =}' \
python3 train_dnn.py --lr {lr} --batch_size {bs} \
::: lr 0.001 0.0005 0.0001 ::: bs 32 64 128
3$ simple_hypersearch \
"python3 train_dnn.py --lr {lr} --batch_size {bs}" \
--n-samples 5 -p lr 0.001 0.0005 0.0001 -p bs 32 64 128 |
simple_gpu_scheduler --gpus 0,1,2
3$ parallel --header : --shuf \
CUDA_VISIBLE_DEVICES='{=1 $_=slot()-1; seq() > 5 and skip() =}' \
python3 train_dnn.py --lr {lr} --batch_size {bs} \
::: lr 0.001 0.0005 0.0001 ::: bs 32 64 128
4$ touch gpu.queue
tail -f -n 0 gpu.queue | simple_gpu_scheduler --gpus 0,1,2 &
echo "my_command_with | and stuff > logfile" >> gpu.queue
4$ touch gpu.queue
tail -f -n 0 gpu.queue |
parallel -j3 CUDA_VISIBLE_DEVICES='{=1 $_=slot()-1 =} {=uq;=}' &
# Needed to fill job slots once
seq 3 | parallel echo true >> gpu.queue
# Add jobs
echo "my_command_with | and stuff > logfile" >> gpu.queue
# Needed to flush output from completed jobs
seq 3 | parallel echo true >> gpu.queue
https://github.com/ExpectationMax/simple_gpu_scheduler (Last checked: 2021-01)
DIFFERENCES BETWEEN parasweep AND GNU Parallel
parasweep is a Python module for facilitating parallel parameter sweeps.
A parasweep job will normally take a text file as input. The text file contains arguments
for the job. Some of these arguments will be fixed and some of them will be changed by
parasweep.
It does this by having a template file such as template.txt:
Xval: {x}
Yval: {y}
FixedValue: 9
# x with 2 decimals
DecimalX: {x:.2f}
TenX: ${x*10}
RandomVal: {r}
and from this template it generates the file to be used by the job by replacing the
replacement strings.
Being a Python module parasweep integrates tighter with Python than GNU parallel. You get
the parameters directly in a Python data structure. With GNU parallel you can use the JSON
or CSV output format to get something similar, but you would have to read the output.
parasweep has a filtering method to ignore parameter combinations you do not need.
Instead of calling the jobs directly, parasweep can use Python's Distributed Resource
Management Application API to make jobs run with different cluster software.
GNU parallel --tmpl supports templates with replacement strings. Such as:
Xval: {x}
Yval: {y}
FixedValue: 9
# x with 2 decimals
DecimalX: {=x $_=sprintf("%.2f",$_) =}
TenX: {=x $_=$_*10 =}
RandomVal: {=1 $_=rand() =}
that can be used like:
parallel --header : --tmpl my.tmpl={#}.t myprog {#}.t \
::: x 1 2 3 ::: y 1 2 3
Filtering is supported as:
parallel --filter '{1} > {2}' echo ::: 1 2 3 ::: 1 2 3
https://github.com/eviatarbach/parasweep (Last checked: 2021-01)
DIFFERENCES BETWEEN parallel-bash AND GNU Parallel
Summary (see legend above):
I1 I2 - - - - -
- - M3 - - M6
- O2 O3 - O5 O6 - O8 x O10
E1 - - - - - -
- - - - - - - - -
- -
parallel-bash is written in pure bash. It is really fast (overhead of ~0.05 ms/job
compared to GNU parallel's ~3 ms/job). So if your jobs are extremely short lived, and you
can live with the quite limited command, this may be useful.
It works by making a queue for each process. Then the jobs are distributed to the queues
in a round robin fashion. Finally the queues are started in parallel. This works fine, if
you are lucky, but if not, all the long jobs may end up in the same queue, so you may see:
$ printf "%b\n" 1 1 1 4 1 1 1 4 1 1 1 4 |
time parallel -P4 sleep {}
(7 seconds)
$ printf "%b\n" 1 1 1 4 1 1 1 4 1 1 1 4 |
time ./parallel-bash.bash -p 4 -c sleep {}
(12 seconds)
Because it uses bash lists, the total number of jobs is limited to 167000..265000
depending on your environment. You get a segmentation fault, when you reach the limit.
Ctrl-C does not stop spawning new jobs. Ctrl-Z does not suspend running jobs.
EXAMPLES FROM parallel-bash
1$ some_input | parallel-bash -p 5 -c echo
1$ some_input | parallel -j 5 echo
2$ parallel-bash -p 5 -c echo < some_file
2$ parallel -j 5 echo < some_file
3$ parallel-bash -p 5 -c echo <<< 'some string'
3$ parallel -j 5 -c echo <<< 'some string'
4$ something | parallel-bash -p 5 -c echo {} {}
4$ something | parallel -j 5 echo {} {}
https://reposhub.com/python/command-line-tools/Akianonymus-parallel-bash.html (Last
checked: 2021-06)
DIFFERENCES BETWEEN bash-concurrent AND GNU Parallel
bash-concurrent is more an alternative to make than to GNU parallel. Its input is very
similar to a Makefile, where jobs depend on other jobs.
It has a nice progress indicator where you can see which jobs completed successfully,
which jobs are currently running, which jobs failed, and which jobs were skipped due to a
depending job failed. The indicator does not deal well with resizing the window.
Output is cached in tempfiles on disk, but is only shown if there is an error, so it is
not meant to be part of a UNIX pipeline. If bash-concurrent crashes these tempfiles are
not removed.
It uses an O(n*n) algorithm, so if you have 1000 independent jobs it takes 22 seconds to
start it.
https://github.com/themattrix/bash-concurrent (Last checked: 2021-02)
DIFFERENCES BETWEEN spawntool AND GNU Parallel
Summary (see legend above):
I1 - - - - - -
M1 - - - - M6
- O2 O3 - O5 O6 - x x O10
E1 - - - - - -
- - - - - - - - -
- -
spawn reads a full command line from stdin which it executes in parallel.
http://code.google.com/p/spawntool/ (Last checked: 2021-07)
DIFFERENCES BETWEEN go-pssh AND GNU Parallel
Summary (see legend above):
- - - - - - -
M1 - - - - -
O1 - - - - - - x x O10
E1 - - - - - -
R1 R2 - - - R6 - - -
- -
go-pssh does ssh in parallel to multiple machines. It runs the same command on multiple
machines similar to --nonall.
The hostnames must be given as IP-addresses (not as hostnames).
Output is sent to stdout (standard output) if command is successful, and to stderr
(standard error) if the command fails.
EXAMPLES FROM go-pssh
1$ go-pssh -l <ip>,<ip> -u <user> -p <port> -P <passwd> -c "<command>"
1$ parallel -S 'sshpass -p <passwd> ssh -p <port> <user>@<ip>' \
--nonall "<command>"
2$ go-pssh scp -f host.txt -u <user> -p <port> -P <password> \
-s /local/file_or_directory -d /remote/directory
2$ parallel --nonall --slf host.txt \
--basefile /local/file_or_directory/./ --wd /remote/directory
--ssh 'sshpass -p <password> ssh -p <port> -l <user>' true
3$ go-pssh scp -l <ip>,<ip> -u <user> -p <port> -P <password> \
-s /local/file_or_directory -d /remote/directory
3$ parallel --nonall -S <ip>,<ip> \
--basefile /local/file_or_directory/./ --wd /remote/directory
--ssh 'sshpass -p <password> ssh -p <port> -l <user>' true
https://github.com/xuchenCN/go-pssh (Last checked: 2021-07)
DIFFERENCES BETWEEN go-parallel AND GNU Parallel
Summary (see legend above):
I1 I2 - - - - I7
- - M3 - - M6
- O2 O3 - O5 - - x x - O10
E1 - - E4 - - -
- - - - - - - - -
- -
go-parallel uses Go templates for replacement strings. Quite similar to the {= perl expr
=} replacement string.
EXAMPLES FROM go-parallel
1$ go-parallel -a ./files.txt -t 'cp {{.Input}} {{.Input | dirname | dirname}}'
1$ parallel -a ./files.txt cp {} '{= $_=::dirname(::dirname($_)) =}'
2$ go-parallel -a ./files.txt -t 'mkdir -p {{.Input}} {{noExt .Input}}'
2$ parallel -a ./files.txt echo mkdir -p {} {.}
3$ go-parallel -a ./files.txt -t 'mkdir -p {{.Input}} {{.Input | basename | noExt}}'
3$ parallel -a ./files.txt echo mkdir -p {} {/.}
https://github.com/mylanconnolly/parallel (Last checked: 2021-07)
Todo
http://code.google.com/p/push/ (cannot compile)
https://github.com/krashanoff/parallel
https://github.com/Nukesor/pueue
https://arxiv.org/pdf/2012.15443.pdf KumQuat
https://arxiv.org/pdf/2007.09436.pdf PaSH: Light-touch Data-Parallel Shell Processing
https://github.com/JeiKeiLim/simple_distribute_job
https://github.com/reggi/pkgrun - not obvious how to use
https://github.com/benoror/better-npm-run - not obvious how to use
https://github.com/bahmutov/with-package
https://github.com/flesler/parallel
https://github.com/Julian/Verge
https://manpages.ubuntu.com/manpages/xenial/man1/tsp.1.html
https://vicerveza.homeunix.net/~viric/soft/ts/
https://github.com/chapmanjacobd/que
TESTING OTHER TOOLS
There are certain issues that are very common on parallelizing tools. Here are a few
stress tests. Be warned: If the tool is badly coded it may overload your machine.
MIX: Output mixes
Output from 2 jobs should not mix. If the output is not used, this does not matter; but if
the output is used then it is important that you do not get half a line from one job
followed by half a line from another job.
If the tool does not buffer, output will most likely mix now and then.
This test stresses whether output mixes.
#!/bin/bash
paralleltool="parallel -j0"
cat <<-EOF > mycommand
#!/bin/bash
# If a, b, c, d, e, and f mix: Very bad
perl -e 'print STDOUT "a"x3000_000," "'
perl -e 'print STDERR "b"x3000_000," "'
perl -e 'print STDOUT "c"x3000_000," "'
perl -e 'print STDERR "d"x3000_000," "'
perl -e 'print STDOUT "e"x3000_000," "'
perl -e 'print STDERR "f"x3000_000," "'
echo
echo >&2
EOF
chmod +x mycommand
# Run 30 jobs in parallel
seq 30 |
$paralleltool ./mycommand > >(tr -s abcdef) 2> >(tr -s abcdef >&2)
# 'a c e' and 'b d f' should always stay together
# and there should only be a single line per job
STDERRMERGE: Stderr is merged with stdout
Output from stdout and stderr should not be merged, but kept separated.
This test shows whether stdout is mixed with stderr.
#!/bin/bash
paralleltool="parallel -j0"
cat <<-EOF > mycommand
#!/bin/bash
echo stdout
echo stderr >&2
echo stdout
echo stderr >&2
EOF
chmod +x mycommand
# Run one job
echo |
$paralleltool ./mycommand > stdout 2> stderr
cat stdout
cat stderr
RAM: Output limited by RAM
Some tools cache output in RAM. This makes them extremely slow if the output is bigger
than physical memory and crash if the output is bigger than the virtual memory.
#!/bin/bash
paralleltool="parallel -j0"
cat <<'EOF' > mycommand
#!/bin/bash
# Generate 1 GB output
yes "`perl -e 'print \"c\"x30_000'`" | head -c 1G
EOF
chmod +x mycommand
# Run 20 jobs in parallel
# Adjust 20 to be > physical RAM and < free space on /tmp
seq 20 | time $paralleltool ./mycommand | wc -c
DISKFULL: Incomplete data if /tmp runs full
If caching is done on disk, the disk can run full during the run. Not all programs
discover this. GNU Parallel discovers it, if it stays full for at least 2 seconds.
#!/bin/bash
paralleltool="parallel -j0"
# This should be a dir with less than 100 GB free space
smalldisk=/tmp/shm/parallel
TMPDIR="$smalldisk"
export TMPDIR
max_output() {
# Force worst case scenario:
# Make GNU Parallel only check once per second
sleep 10
# Generate 100 GB to fill $TMPDIR
# Adjust if /tmp is bigger than 100 GB
yes | head -c 100G >$TMPDIR/$$
# Generate 10 MB output that will not be buffered due to full disk
perl -e 'print "X"x10_000_000' | head -c 10M
echo This part is missing from incomplete output
sleep 2
rm $TMPDIR/$$
echo Final output
}
export -f max_output
seq 10 | $paralleltool max_output | tr -s X
CLEANUP: Leaving tmp files at unexpected death
Some tools do not clean up tmp files if they are killed. If the tool buffers on disk, they
may not clean up, if they are killed.
#!/bin/bash
paralleltool=parallel
ls /tmp >/tmp/before
seq 10 | $paralleltool sleep &
pid=$!
# Give the tool time to start up
sleep 1
# Kill it without giving it a chance to cleanup
kill -9 $!
# Should be empty: No files should be left behind
diff <(ls /tmp) /tmp/before
SPCCHAR: Dealing badly with special file names.
It is not uncommon for users to create files like:
My brother's 12" *** record (costs $$$).jpg
Some tools break on this.
#!/bin/bash
paralleltool=parallel
touch "My brother's 12\" *** record (costs \$\$\$).jpg"
ls My*jpg | $paralleltool ls -l
COMPOSED: Composed commands do not work
Some tools require you to wrap composed commands into bash -c.
echo bar | $paralleltool echo foo';' echo {}
ONEREP: Only one replacement string allowed
Some tools can only insert the argument once.
echo bar | $paralleltool echo {} foo {}
INPUTSIZE: Length of input should not be limited
Some tools limit the length of the input lines artificially with no good reason. GNU
parallel does not:
perl -e 'print "foo."."x"x100_000_000' | parallel echo {.}
GNU parallel limits the command to run to 128 KB due to execve(1):
perl -e 'print "x"x131_000' | parallel echo {} | wc
NUMWORDS: Speed depends on number of words
Some tools become very slow if output lines have many words.
#!/bin/bash
paralleltool=parallel
cat <<-EOF > mycommand
#!/bin/bash
# 10 MB of lines with 1000 words
yes "`seq 1000`" | head -c 10M
EOF
chmod +x mycommand
# Run 30 jobs in parallel
seq 30 | time $paralleltool -j0 ./mycommand > /dev/null
4GB: Output with a line > 4GB should be OK
#!/bin/bash
paralleltool="parallel -j0"
cat <<-EOF > mycommand
#!/bin/bash
perl -e '\$a="a"x1000_000; for(1..5000) { print \$a }'
EOF
chmod +x mycommand
# Run 1 job
seq 1 | $paralleltool ./mycommand | LC_ALL=C wc
AUTHOR
When using GNU parallel for a publication please cite:
O. Tange (2011): GNU Parallel - The Command-Line Power Tool, ;login: The USENIX Magazine,
February 2011:42-47.
Copyright (C) 2007-10-18 Ole Tange, http://ole.tange.dk
Copyright (C) 2008-2010 Ole Tange, http://ole.tange.dk
Copyright (C) 2010-2021 Ole Tange, http://ole.tange.dk and Free Software Foundation, Inc.
Parts of the manual concerning xargs compatibility is inspired by the manual of xargs from
GNU findutils 4.4.2.
LICENSE
This program is free software; you can redistribute it and/or modify it under the terms of
the GNU General Public License as published by the Free Software Foundation; either
version 3 of the License, or at your option any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY;
without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this program.
If not, see <https://www.gnu.org/licenses/>.
Documentation license I
Permission is granted to copy, distribute and/or modify this documentation under the terms
of the GNU Free Documentation License, Version 1.3 or any later version published by the
Free Software Foundation; with no Invariant Sections, with no Front-Cover Texts, and with
no Back-Cover Texts. A copy of the license is included in the file
LICENSES/GFDL-1.3-or-later.txt.
Documentation license II
You are free:
to Share to copy, distribute and transmit the work
to Remix to adapt the work
Under the following conditions:
Attribution
You must attribute the work in the manner specified by the author or licensor
(but not in any way that suggests that they endorse you or your use of the work).
Share Alike
If you alter, transform, or build upon this work, you may distribute the
resulting work only under the same, similar or a compatible license.
With the understanding that:
Waiver Any of the above conditions can be waived if you get permission from the
copyright holder.
Public Domain
Where the work or any of its elements is in the public domain under applicable
law, that status is in no way affected by the license.
Other Rights
In no way are any of the following rights affected by the license:
• Your fair dealing or fair use rights, or other applicable copyright exceptions
and limitations;
• The author's moral rights;
• Rights other persons may have either in the work itself or in how the work is
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Notice For any reuse or distribution, you must make clear to others the license terms of
this work.
A copy of the full license is included in the file as LICENCES/CC-BY-SA-4.0.txt
DEPENDENCIES
GNU parallel uses Perl, and the Perl modules Getopt::Long, IPC::Open3, Symbol, IO::File,
POSIX, and File::Temp. For remote usage it also uses rsync with ssh.
SEE ALSO
find(1), xargs(1), make(1), pexec(1), ppss(1), xjobs(1), prll(1), dxargs(1), mdm(1)