| PARALLEL(1) | parallel | PARALLEL(1) |
parallel - build and execute shell command lines from standard input in parallel
parallel [options] [command [arguments]] < list_of_arguments
parallel [options] [command [arguments]] ( ::: arguments | :::+ arguments | :::: argfile(s) | ::::+ argfile(s) ) ...
parallel --semaphore [options] command
#!/usr/bin/parallel --shebang [options] [command [arguments]]
GNU parallel is a shell tool for executing jobs in parallel using one or more computers. A job can be a single command or a small script that has to be run for each of the lines in the input. The typical input is a list of files, a list of hosts, a list of users, a list of URLs, or a list of tables. A job can also be a command that reads from a pipe. GNU parallel can then split the input into blocks and pipe a block into each command in parallel.
If you use xargs and tee today you will find GNU parallel very easy to use as GNU parallel is written to have the same options as xargs. If you write loops in shell, you will find GNU parallel may be able to replace most of the loops and make them run faster by running several jobs in parallel.
GNU parallel makes sure output from the commands is the same output as you would get had you run the commands sequentially. This makes it possible to use output from GNU parallel as input for other programs.
For each line of input GNU parallel will execute command with the line as arguments. If no command is given, the line of input is executed. Several lines will be run in parallel. GNU parallel can often be used as a substitute for xargs or cat | bash.
Start by watching the intro videos for a quick introduction: http://www.youtube.com/playlist?list=PL284C9FF2488BC6D1
Then look at the EXAMPLEs after the list of OPTIONS. That will give you an idea of what GNU parallel is capable of.
Then spend an hour walking through the tutorial (man parallel_tutorial). Your command line will love you for it.
Finally you may want to look at the rest of this manual if you have special needs not already covered.
If you want to know the design decisions behind GNU parallel, try: man parallel_design. This is also a good intro if you intend to change GNU parallel.
If command is given, GNU parallel solve the same tasks as xargs. If command is not given GNU parallel will behave similar to cat | sh.
The command must be an executable, a script, a composed command, or a function.
Bash functions: export -f the function first or use env_parallel.
Bash aliases: Use env_parallel.
Ksh functions and aliases: Use env_parallel.
Zsh functions and aliases: Use env_parallel.
Fish functions and aliases: Use env_parallel.
Ksh functions and aliases: Use env_parallel.
Pdksh functions and aliases: Use env_parallel.
The command cannot contain the character \257 (macron: X).
The replacement string {} can be changed with -I.
If the command line contains no replacement strings then {} will be appended to the command line.
The replacement string {.} can be changed with --er.
To understand replacement strings see {}.
The replacement string {/} can be changed with --basenamereplace.
To understand replacement strings see {}.
The replacement string {//} can be changed with --dirnamereplace.
To understand replacement strings see {}.
The replacement string {/.} can be changed with --basenameextensionreplace.
To understand replacement strings see {}.
The replacement string {#} can be changed with --seqreplace.
To understand replacement strings see {}.
The replacement string {%} can be changed with --slotreplace.
To understand replacement strings see {}.
To understand replacement strings see {}.
This positional replacement string will be replaced by the input from input source n (when used with -a or ::::) or with the n'th argument (when used with -N). The input will have the extension removed.
To understand positional replacement strings see {n}.
This positional replacement string will be replaced by the input from input source n (when used with -a or ::::) or with the n'th argument (when used with -N). The input will have the directory (if any) removed.
To understand positional replacement strings see {n}.
This positional replacement string will be replaced by the dir of the input from input source n (when used with -a or ::::) or with the n'th argument (when used with -N). See dirname(1).
To understand positional replacement strings see {n}.
This positional replacement string will be replaced by the input from input source n (when used with -a or ::::) or with the n'th argument (when used with -N). The input will have the directory (if any) and extension removed.
To understand positional replacement strings see {n}.
Example:
seq 10 | parallel echo {} + 1 is {= '$_++' =}
parallel csh -c {= '$_="mkdir ".Q($_)' =} ::: '12" dir'
seq 50 | parallel echo job {#} of {= '$_=total_jobs()' =}
See also: --rpl --parens
See also: {=perl expression=} {n}.
The following are equivalent:
(echo file1; echo file2) | parallel gzip
parallel gzip ::: file1 file2
parallel gzip {} ::: file1 file2
parallel --arg-sep ,, gzip {} ,, file1 file2
parallel --arg-sep ,, gzip ,, file1 file2
parallel ::: "gzip file1" "gzip file2"
To avoid treating ::: as special use --arg-sep to set the argument separator to something else. See also --arg-sep.
If multiple ::: are given, each group will be treated as an input source, and all combinations of input sources will be generated. E.g. ::: 1 2 ::: a b c will result in the combinations (1,a) (1,b) (1,c) (2,a) (2,b) (2,c). This is useful for replacing nested for-loops.
::: and :::: can be mixed. So these are equivalent:
parallel echo {1} {2} {3} ::: 6 7 ::: 4 5 ::: 1 2 3
parallel echo {1} {2} {3} :::: <(seq 6 7) <(seq 4 5) \
:::: <(seq 1 3)
parallel -a <(seq 6 7) echo {1} {2} {3} :::: <(seq 4 5) \
:::: <(seq 1 3)
parallel -a <(seq 6 7) -a <(seq 4 5) echo {1} {2} {3} \
::: 1 2 3
seq 6 7 | parallel -a - -a <(seq 4 5) echo {1} {2} {3} \
::: 1 2 3
seq 4 5 | parallel echo {1} {2} {3} :::: <(seq 6 7) - \
::: 1 2 3
Contrary to --link, values do not wrap: The shortest input source determines the length.
Example:
parallel echo ::: a b c :::+ 1 2 3 ::: X Y :::+ 11 22
::: and :::: can be mixed.
See -a, ::: and --link.
Contrary to --link, values do not wrap: The shortest input source determines the length.
If multiple -a are given, each input-file will be treated as an input source, and all combinations of input sources will be generated. E.g. The file foo contains 1 2, the file bar contains a b c. -a foo -a bar will result in the combinations (1,a) (1,b) (1,c) (2,a) (2,b) (2,c). This is useful for replacing nested for-loops.
See also --link and {n}.
See also: ::::.
Also useful if you command uses ::: but you still want to read arguments from stdin (standard input): Simply change --arg-sep to a string that is not in the command line.
See also: :::.
It is compatible with zenity:
seq 1000 | parallel -j30 --bar '(echo {};sleep 0.1)' \
2> >(zenity --progress --auto-kill) | wc
See also: --fg, man sem.
Implies --semaphore.
If it is impossible for you to run --bibtex you can use --will-cite.
If you use --will-cite in scripts to be run by others you are making it harder for others to see the citation notice. The development of GNU parallel is indirectly financed through citations, so if your users do not know they should cite then you are making it harder to finance development. However, if you pay 10000 EUR, you should feel free to use --will-cite in scripts.
GNU parallel tries to meet the block size but can be off by the length of one record. For performance reasons size should be bigger than a two records. GNU parallel will warn you and automatically increase the size if you choose a size that is too small.
If you use -N, --block-size should be bigger than N+1 records.
size defaults to 1M.
When using --pipepart a negative block size is not interpreted as a blocksize but as the number of blocks each jobslot should have. So this will run 10*5 = 50 jobs in total:
parallel --pipepart -a myfile --block -10 -j5 wc
This is an efficient alternative to --round-robin because data is never read by GNU parallel, but you can still have very few jobslots process a large amount of data.
See --pipe and --pipepart for use of this.
Implies --pipe unless --pipepart is used.
See also --fifo.
find log -name '*gz' | parallel \
--sshlogin server.example.com --transferfile {} \
--return {.}.bz2 --cleanup "zcat {} | bzip -9 >{.}.bz2"
With --transferfile {} the file transferred to the remote computer will be removed on the remote computer. Directories created will not be removed - even if they are empty.
With --return the file transferred from the remote computer will be removed on the remote computer. Directories created will not be removed - even if they are empty.
--cleanup is ignored when not used with --transferfile or --return.
--colsep implies --trim rl.
regexp is a Perl Regular Expression: http://perldoc.perl.org/perlre.html
GNU parallel will try pzstd, lbzip2, pbzip2, zstd, pigz, lz4, lzop, plzip, lzip, lrz, gzip, pxz, lzma, bzip2, xz, clzip, in that order, and use the first available.
In Bash var can also be a Bash function - just remember to export -f the function, see command.
The variable '_' is special. It will copy all exported environment variables except for the ones mentioned in ~/.parallel/ignored_vars.
To copy the full environment (both exported and not exported variables, arrays, and functions) use env_parallel.
See also: --record-env.
The estimate is based on the runtime of finished jobs, so the first estimate will only be shown when the first job has finished.
Implies --progress.
See also: --bar, --progress.
Implies --semaphore.
See also --bg, man sem.
Beware: If data is not read from the fifo, the job will block forever.
Implies --pipe unless --pipepart is used.
See also --cat.
For performance reasons, this check is performed only at the start and every time --sshloginfile is changed. If an host goes down after the first check, it will go undetected until --sshloginfile is changed; --retries can be used to mitigate this.
Currently you can not put --filter-hosts in a profile, $PARALLEL, /etc/parallel/config or similar. This is because GNU parallel uses GNU parallel to compute this, so you will get an infinite loop. This will likely be fixed in a later release.
--group is the default. Can be reversed with -u.
See also: --line-buffer --ungroup
val defaults to never, which runs all jobs no matter what.
val can also take on the form of when,why.
when can be 'now' which means kill all running jobs and halt immediately, or it can be 'soon' which means wait for all running jobs to complete, but start no new jobs.
why can be 'fail=X', 'fail=Y%', 'success=X', or 'success=Y%' where X is the number of jobs that has to fail or succeed before halting, and Y is the percentage of jobs that has to fail or succeed before halting.
Example:
For backwards compability these also work:
For --pipe the matched header will be prepended to each output.
--header : is an alias for --header '.*\n'.
If regexp is a number, it is a fixed number of lines.
Example:
parallel --hostgroups \
--sshlogin @grp1/myserver1 -S @grp1+grp2/myserver2 \
--sshlogin @grp3/myserver3 \
echo ::: my_grp1_arg@grp1 arg_for_grp2@grp2 third_arg@grp1+grp3
my_grp1_arg may be run on either myserver1 or myserver2, third_arg may be run on either myserver1 or myserver3, but arg_for_grp2 will only be run on myserver2.
See also: --sshlogin.
For --pipe bytes transferred and bytes returned are number of input and output of bytes.
To convert the times into ISO-8601 strict do:
perl -a -F"\t" -ne \
'chomp($F[2]=`date -d \@$F[2] +%FT%T`); print join("\t",@F)'
See also --resume --resume-failed.
If --semaphore is set, the default is 1 thus making a mutex.
parallel -j4 sleep {}\; echo {} ::: 2 1 4 3
parallel -j4 -k sleep {}\; echo {} ::: 2 1 4 3
If used with --onall or --nonall the output will grouped by sshlogin in sorted order.
When used otherwise: Use at most max-lines nonblank input lines per command line. Trailing blanks cause an input line to be logically continued on the next input line.
-L 0 means read one line, but insert 0 arguments on the command line.
Implies -X unless -m, --xargs, or --pipe is set.
When used otherwise: Synonym for the -L option. Unlike -L, the max-lines argument is optional. If max-lines is not specified, it defaults to one. The -l option is deprecated since the POSIX standard specifies -L instead.
-l 0 is an alias for -l 1.
Implies -X unless -m, --xargs, or --pipe is set.
--line-buffer takes more CPU power than than both --group and --ungroup, but can be faster than --group if the CPU is not the limiting factor.
See also: --group --ungroup
Compare these two:
parallel echo {1} {2} ::: 1 2 3 ::: a b c
parallel --link echo {1} {2} ::: 1 2 3 ::: a b c
Arguments will be recycled if one input source has more arguments than the others:
parallel --link echo {1} {2} {3} \
::: 1 2 ::: I II III ::: a b c d e f g
See also --header, :::+, ::::+.
If {} is not used the arguments will be appended to the line. If {} is used multiple times each {} will be replaced with all the arguments.
Support for --xargs with --sshlogin is limited and may fail.
See also -X for context replace. If in doubt use -X as that will most likely do what is needed.
If {} is not used the arguments will be appended to the line. If {} is used multiple times each {} will be replaced with all the arguments.
Support for -m with --sshlogin is limited and may fail.
See also -X for context replace. If in doubt use -X as that will most likely do what is needed.
If the jobs take up very different amount of RAM, GNU parallel will only start as many as there is memory for. If less than size bytes are free, no more jobs will be started. If less than 50% size bytes are free, the youngest job will be killed, and put back on the queue to be run later.
This is useful for scripts that depend on features only available from a certain version of GNU parallel.
This is useful for running the same command (e.g. uptime) on a list of servers.
When using --group the output will be grouped by each server, so all the output from one server will be grouped together.
--joblog will contain an entry for each job on each server, so there will be several job sequence 1.
See also: --results
The block size is determined by --block. The strings --recstart and --recend tell GNU parallel how a record starts and/or ends. The block read will have the final partial record removed before the block is passed on to the job. The partial record will be prepended to next block.
If --recstart is given this will be used to split at record start.
If --recend is given this will be used to split at record end.
If both --recstart and --recend are given both will have to match to find a split position.
If neither --recstart nor --recend are given --recend defaults to '\n'. To have no record separator use --recend "".
--files is often used with --pipe.
--pipe maxes out at around 1 GB/s input, and 100 MB/s output. If performance is important use --pipepart.
See also: --recstart, --recend, --fifo, --cat, --pipepart, --files.
--pipepart has a few limitations:
If using a block device with lot of NUL bytes, remember to set --recend ''.
{##} is the number of jobs to be run. It is incompatible with -X/-m/--xargs.
By sending GNU parallel SIGUSR2 you can toggle turning on/off --progress on a running GNU parallel process.
See also --eta.
-n 0 means read one argument, but insert 0 arguments on the command line.
Implies -X unless -m is set.
-N 0 means read one argument, but insert 0 arguments on the command line.
This will set the owner of the homedir to the user:
tr ':' '\n' < /etc/passwd | parallel -N7 chown {1} {6}
Implies -X unless -m or --pipe is set.
When used with --pipe -N is the number of records to read. This is somewhat slower than --block.
Another useful setting is ,,,, which would make both parenthesis ,,:
parallel --parens ,,,, echo foo is ,,s/I/O/g,, ::: FII
See also: --rpl {= perl expression =}
profilename corresponds to the file ~/.parallel/profilename.
You can give multiple profiles by repeating --profile. If parts of the profiles conflict, the later ones will be used.
Default: config
If used with --pipe this is slow.
The swap activity is only sampled every 10 seconds as the sampling takes 1 second to do.
Swap activity is computed as (swap-in)*(swap-out) which in practice is a good value: swapping out is not a problem, swapping in is not a problem, but both swapping in and out usually indicates a problem.
--memfree may give better results, so try using that first.
See also --env.
If --recend is given endstring will be used to split at record end.
If both --recstart and --recend are given the combined string endstringstartstring will have to match to find a split position. This is useful if either startstring or endstring match in the middle of a record.
If neither --recstart nor --recend are given then --recend defaults to '\n'. To have no record separator use --recend "".
--recstart and --recend are used with --pipe.
Use --regexp to interpret --recstart and --recend as regular expressions. This is slow, however.
Only used with --pipe.
CSV file output
If name ends in .csv/.tsv the output will be a CSV-file named name.
.csv gives a comma separated value file. .tsv gives a TAB separated value file.
-.csv/-.tsv are special: It will give the file on stdout (standard output).
Dir structure output
If name does not end in .csv/.tsv will be treated as a dir.
The files will be stored in a directory tree rooted at name. Within this directory tree, each command will result in two files: name/<ARGS>/stdout and name/<ARGS>/stderr, where <ARGS> is a sequence of directories representing the header of the input source (if using --header :) or the number of the input source and corresponding values.
name can contain replacement strings.
E.g:
parallel --header : --results foo echo {a} {b} \
::: a I II ::: b III IIII
will generate the files:
foo/a/I/b/III/stderr
foo/a/I/b/III/stdout
foo/a/I/b/IIII/stderr
foo/a/I/b/IIII/stdout
foo/a/II/b/III/stderr
foo/a/II/b/III/stdout
foo/a/II/b/IIII/stderr
foo/a/II/b/IIII/stdout
and
parallel --results foo echo {1} {2} ::: I II ::: III IIII
will generate the files:
foo/1/I/2/III/stderr
foo/1/I/2/III/stdout
foo/1/I/2/IIII/stderr
foo/1/I/2/IIII/stdout
foo/1/II/2/III/stderr
foo/1/II/2/III/stdout
foo/1/II/2/IIII/stderr
foo/1/II/2/IIII/stdout
and
parallel --results foo-{1} echo {1} {2} ::: I II ::: III IIII
will generate the files:
foo-I/1/I/2/IIII/seq
foo-I/1/I/2/IIII/stderr
foo-I/1/I/2/IIII/stdout
foo-I/1/I/2/III/seq
foo-I/1/I/2/III/stderr
foo-I/1/I/2/III/stdout
foo-II/1/II/2/IIII/seq
foo-II/1/II/2/IIII/stderr
foo-II/1/II/2/IIII/stdout
foo-II/1/II/2/III/seq
foo-II/1/II/2/III/stderr
foo-II/1/II/2/III/stdout
If you do not want the dir structure, try --files --tag instead.
See also --files, --tag, --header, --joblog.
See also --joblog, --results, --resume-failed, --retries.
See also --joblog, --resume, --retry-failed, --retries.
--retry-failed ignores the command and arguments on the command line: It only looks at the joblog.
B<Differences between --resume, --resume-failed, --retry-failed>
In this example exit {= $_%=2 =} will cause every other job to fail.
timeout -k 1 4 parallel --joblog log -j10 'sleep {}; exit {= $_%=2 =}' ::: {10..1}
4 jobs completed. 2 failed:
Seq [...] Exitval Signal Command
10 [...] 1 0 sleep 1; exit 1
9 [...] 0 0 sleep 2; exit 0
8 [...] 1 0 sleep 3; exit 1
7 [...] 0 0 sleep 4; exit 0
--resume does not care about the Exitval, but only looks at Seq. If the Seq is run, it will not be run again. So if needed, you can change the command for the seqs not run yet:
parallel --resume --joblog log -j10 'sleep .{}; exit {= $_%=2 =}' ::: {10..1}
Seq [...] Exitval Signal Command
[... as above ...]
1 [...] 0 0 sleep .10; exit 0
6 [...] 1 0 sleep .5; exit 1
5 [...] 0 0 sleep .6; exit 0
4 [...] 1 0 sleep .7; exit 1
3 [...] 0 0 sleep .8; exit 0
2 [...] 1 0 sleep .9; exit 1
--resume-failed cares about the Exitval, but also only looks at Seq to figure out which commands to run. Again this means you can change the command, but not the arguments. It will run the failed seqs and the seqs not yet run:
parallel --resume-failed --joblog log -j10 'echo {};sleep .{}; exit {= $_%=3 =}' ::: {10..1}
Seq [...] Exitval Signal Command
[... as above ...]
10 [...] 1 0 echo 1;sleep .1; exit 1
8 [...] 0 0 echo 3;sleep .3; exit 0
6 [...] 2 0 echo 5;sleep .5; exit 2
4 [...] 1 0 echo 7;sleep .7; exit 1
2 [...] 0 0 echo 9;sleep .9; exit 0
--retry-failed cares about the Exitval, but takes the command from the joblog. It ignores any arguments or commands given on the command line:
parallel --retry-failed --joblog log -j10 this part is ignored
Seq [...] Exitval Signal Command
[... as above ...]
10 [...] 1 0 echo 1;sleep .1; exit 1
6 [...] 2 0 echo 5;sleep .5; exit 2
4 [...] 1 0 echo 7;sleep .7; exit 1
See also --joblog, --resume, --resume-failed, --retries.
echo foo/bar.txt | parallel --return {.}.out \
--sshlogin server.example.com touch {.}.out
This will transfer the file $HOME/foo/bar.out from the computer server.example.com to the file foo/bar.out after running touch foo/bar.out on server.example.com.
parallel -S server --trc out/./{}.out touch {}.out ::: in/file
This will transfer the file in/file.out from the computer server.example.com to the files out/in/file.out after running touch in/file.out on server.
echo /tmp/foo/bar.txt | parallel --return {.}.out \
--sshlogin server.example.com touch {.}.out
This will transfer the file /tmp/foo/bar.out from the computer server.example.com to the file /tmp/foo/bar.out after running touch /tmp/foo/bar.out on server.example.com.
Multiple files can be transferred by repeating the option multiple times:
echo /tmp/foo/bar.txt | parallel \
--sshlogin server.example.com \
--return {.}.out --return {.}.out2 touch {.}.out {.}.out2
--return is often used with --transferfile and --cleanup.
--return is ignored when used with --sshlogin : or when not used with --sshlogin.
--keep-order will not work with --round-robin as it is impossible to track which input block corresponds to which output.
--round-robin implies --pipe, except if --pipepart is given.
--rpl '{} '
--rpl '{#} 1 $_=$job->seq()'
--rpl '{%} 1 $_=$job->slot()'
--rpl '{/} s:.*/::'
--rpl '{//} $Global::use{"File::Basename"} ||= eval "use File::Basename; 1;"; $_ = dirname($_);'
--rpl '{/.} s:.*/::; s:\.[^/.]+$::;'
--rpl '{.} s:\.[^/.]+$::'
The --plus replacement strings are implemented as:
--rpl '{+/} s:/[^/]*$::'
--rpl '{+.} s:.*\.::'
--rpl '{+..} s:.*\.([^.]*\.):$1:'
--rpl '{+...} s:.*\.([^.]*\.[^.]*\.):$1:'
--rpl '{..} s:\.[^/.]+$::; s:\.[^/.]+$::'
--rpl '{...} s:\.[^/.]+$::; s:\.[^/.]+$::; s:\.[^/.]+$::'
--rpl '{/..} s:.*/::; s:\.[^/.]+$::; s:\.[^/.]+$::'
--rpl '{/...} s:.*/::; s:\.[^/.]+$::; s:\.[^/.]+$::; s:\.[^/.]+$::'
--rpl '{##} $_=total_jobs()'
If the user defined replacement string starts with '{' it can also be used as a positional replacement string (like {2.}).
It is recommended to only change $_ but you have full access to all of GNU parallel's internal functions and data structures.
Here are a few examples:
Is the job sequence even or odd?
--rpl '{odd} $_ = $job->seq() % 2 ? "odd" : "even"'
Pad job sequence with leading zeros to get equal width
--rpl '{0#} $f = "%0".int(1+log(total_jobs())/log(10))."d"; $_=sprintf($f,$job->seq())'
Job sequence counting from 0
--rpl '{#0} $_ = $job->seq() - 1'
Job slot counting from 2
--rpl '{%1} $_ = $job->slot() + 1'
See also: {= perl expression =} --parens
Implies -X unless -m is set.
--semaphore implies --bg unless --fg is specified.
--semaphore implies --semaphorename `tty` unless --semaphorename is specified.
Used with --fg, --wait, and --semaphorename.
The command sem is an alias for parallel --semaphore.
See also man sem.
The default normally works as expected when used interactively, but when used in a script name should be set. $$ or my_task_name are often a good value.
The semaphore is stored in ~/.parallel/semaphores/
Implies --semaphore.
See also man sem.
If secs < 0: If the semaphore is not released within secs seconds, exit.
Implies --semaphore.
See also man sem.
Like this:
#!/usr/bin/parallel --shebang -r traceroute
qubes-os.org
debian.org
freenetproject.org
--shebang must be set as the first option.
On FreeBSD env is needed:
#!/usr/bin/env -S parallel --shebang -r traceroute
qubes-os.org
debian.org
freenetproject.org
There are many limitations of shebang (#!) depending on your operating system. See details on http://www.in-ulm.de/~mascheck/various/shebang/
cat arguments | parallel the_program
then the script can be changed to:
#!/usr/bin/parallel --shebang-wrap /the/original/parser --with-options
E.g.
#!/usr/bin/parallel --shebang-wrap /usr/bin/python
If the program can be run like this:
cat data | parallel --pipe the_program
then the script can be changed to:
#!/usr/bin/parallel --shebang-wrap --pipe /the/original/parser --with-options
E.g.
#!/usr/bin/parallel --shebang-wrap --pipe /usr/bin/perl -w
--shebang-wrap must be set as the first option.
If DBURL is prepended with '+' GNU parallel assumes the table is already made with the correct columns and appends the jobs to it.
If DBURL is not prepended with '+' the table will be dropped and created with the correct amount of V-columns unless
--sqlmaster does not run any jobs, but it creates the values for the jobs to be run. One or more --sqlworker must be run to actually execute the jobs.
If --wait is set, GNU parallel will wait for the jobs to complete.
The format of a DBURL is:
[sql:]vendor://[[user][:password]@][host][:port]/[database]/table
E.g.
sql:mysql://hr:hr@localhost:3306/hrdb/jobs
mysql://scott:tiger@my.example.com/pardb/paralleljobs
sql:oracle://scott:tiger@ora.example.com/xe/parjob
postgresql://scott:tiger@pg.example.com/pgdb/parjob
pg:///parjob
sqlite3:///pardb/parjob
It can also be an alias from ~/.sql/aliases:
:myalias mysql:///mydb/paralleljobs
If you have more than one --sqlworker jobs may be run more than once.
If hostgroups is given, the sshlogin will be added to that hostgroup. Multiple hostgroups are separated by '+'. The sshlogin will always be added to a hostgroup named the same as sshlogin.
If only the @hostgroup is given, only the sshlogins in that hostgroup will be used. Multiple @hostgroup can be given.
GNU parallel will determine the number of CPU cores on the remote computers and run the number of jobs as specified by -j. If the number ncpu is given GNU parallel will use this number for number of CPU cores on the host. Normally ncpu will not be needed.
An sshlogin is of the form:
[sshcommand [options]] [username@]hostname
The sshlogin must not require a password (ssh-agent, ssh-copy-id, and sshpass may help with that).
The sshlogin ':' is special, it means 'no ssh' and will therefore run on the local computer.
The sshlogin '..' is special, it read sshlogins from ~/.parallel/sshloginfile
The sshlogin '-' is special, too, it read sshlogins from stdin (standard input).
To specify more sshlogins separate the sshlogins by comma, newline (in the same string), or repeat the options multiple times.
For examples: see --sshloginfile.
The remote host must have GNU parallel installed.
--sshlogin is known to cause problems with -m and -X.
--sshlogin is often used with --transferfile, --return, --cleanup, and --trc.
server.example.com
username@server2.example.com
8/my-8-core-server.example.com
2/my_other_username@my-dualcore.example.net
# This server has SSH running on port 2222
ssh -p 2222 server.example.net
4/ssh -p 2222 quadserver.example.net
# Use a different ssh program
myssh -p 2222 -l myusername hexacpu.example.net
# Use a different ssh program with default number of cores
//usr/local/bin/myssh -p 2222 -l myusername hexacpu
# Use a different ssh program with 6 cores
6//usr/local/bin/myssh -p 2222 -l myusername hexacpu
# Assume 16 cores on the local computer
16/:
# Put server1 in hostgroup1
@hostgroup1/server1
# Put myusername@server2 in hostgroup1+hostgroup2
@hostgroup1+hostgroup2/myusername@server2
# Force 4 cores and put 'ssh -p 2222 server3' in hostgroup1
@hostgroup1/4/ssh -p 2222 server3
When using a different ssh program the last argument must be the hostname.
Multiple --sshloginfile are allowed.
GNU parallel will first look for the file in current dir; if that fails it look for the file in ~/.parallel.
The sshloginfile '..' is special, it read sshlogins from ~/.parallel/sshloginfile
The sshloginfile '.' is special, it read sshlogins from /etc/parallel/sshloginfile
The sshloginfile '-' is special, too, it read sshlogins from stdin (standard input).
If the sshloginfile is changed it will be re-read when a job finishes though at most once per second. This makes it possible to add and remove hosts while running.
This can be used to have a daemon that updates the sshloginfile to only contain servers that are up:
cp original.slf tmp2.slf
while [ 1 ] ; do
nice parallel --nonall -j0 -k --slf original.slf \
--tag echo | perl 's/\t$//' > tmp.slf
if diff tmp.slf tmp2.slf; then
mv tmp.slf tmp2.slf
fi
sleep 10
done &
parallel --slf tmp2.slf ...
You can of course override -j1 and -u.
--tag is ignored when using -u.
--tagstring is ignored when using -u, --onall, and --nonall.
TERM,200,TERM,100,TERM,50,KILL,25
which sends a TERM signal, waits 200 ms, sends another TERM signal, waits 100 ms, sends another TERM signal, waits 50 ms, sends a KILL signal, waits 25 ms, and exits. GNU parallel discovers if a process dies before the waiting time is up.
If secs is followed by a % then the timeout will dynamically be computed as a percentage of the median average runtime. Only values > 100% will make sense.
See also -v, -p.
echo foo/bar.txt | parallel \
--sshlogin server.example.com --transferfile {} wc
This will transfer the file foo/bar.txt to the computer server.example.com to the file $HOME/foo/bar.txt before running wc foo/bar.txt on server.example.com.
echo /tmp/foo/bar.txt | parallel \
--sshlogin server.example.com --transferfile {} wc
This will transfer the file /tmp/foo/bar.txt to the computer server.example.com to the file /tmp/foo/bar.txt before running wc /tmp/foo/bar.txt on server.example.com.
echo /tmp/./foo/bar.txt | parallel \
--sshlogin server.example.com --transferfile {} wc {= s:.*/./:./: =}
This will transfer the file /tmp/foo/bar.txt to the computer server.example.com to the file foo/bar.txt before running wc ./foo/bar.txt on server.example.com.
--transferfile is often used with --return and --cleanup. A shorthand for --transferfile {} is --transfer.
--transferfile is ignored when used with --sshlogin : or when not used with --sshlogin.
--transferfile {} --return filename --cleanup
seq 4 | parallel -j0 \
'sleep {};echo -n start{};sleep {};echo {}end'
seq 4 | parallel -u -j0 \
'sleep {};echo -n start{};sleep {};echo {}end'
It also disables --tag. GNU parallel outputs faster with -u. Compare the speed of these:
parallel seq ::: 300000000 >/dev/null
parallel -u seq ::: 300000000 >/dev/null
parallel --line-buffer seq ::: 300000000 >/dev/null
Can be reversed with --group.
See also: --line-buffer --group
Use -v -v to print the wrapping ssh command when running remotely.
The special mydir value ... will create working dirs under ~/.parallel/tmp/ on the remote computers. If --cleanup is given these dirs will be removed.
The special mydir value . uses the current working dir. If the current working dir is beneath your home dir, the value . is treated as the relative path to your home dir. This means that if your home dir is different on remote computers (e.g. if your login is different) the relative path will still be relative to your home dir.
To see the difference try:
parallel -S server pwd ::: ""
parallel --wd . -S server pwd ::: ""
parallel --wd ... -S server pwd ::: ""
mydir can contain GNU parallel's replacement strings.
Used with --semaphore or --sqlmaster.
See also man sem.
If {} is not used the arguments will be appended to the line. If {} is used as part of a word (like pic{}.jpg) then the whole word will be repeated. If {} is used multiple times each {} will be replaced with the arguments.
Normally -X will do the right thing, whereas -m can give unexpected results if {} is used as part of a word.
Support for -X with --sshlogin is limited and may fail.
See also -m.
GNU parallel can work similar to xargs -n1.
To compress all html files using gzip run:
find . -name '*.html' | parallel gzip --best
If the file names may contain a newline use -0. Substitute FOO BAR with FUBAR in all files in this dir and subdirs:
find . -type f -print0 | parallel -q0 perl -i -pe 's/FOO BAR/FUBAR/g'
Note -q is needed because of the space in 'FOO BAR'.
GNU parallel can take the arguments from command line instead of stdin (standard input). To compress all html files in the current dir using gzip run:
parallel gzip --best ::: *.html
To convert *.wav to *.mp3 using LAME running one process per CPU core run:
parallel lame {} -o {.}.mp3 ::: *.wav
When moving a lot of files like this: mv *.log destdir you will sometimes get the error:
bash: /bin/mv: Argument list too long
because there are too many files. You can instead do:
ls | grep -E '\.log$' | parallel mv {} destdir
This will run mv for each file. It can be done faster if mv gets as many arguments that will fit on the line:
ls | grep -E '\.log$' | parallel -m mv {} destdir
To remove the files pict0000.jpg .. pict9999.jpg you could do:
seq -w 0 9999 | parallel rm pict{}.jpg
You could also do:
seq -w 0 9999 | perl -pe 's/(.*)/pict$1.jpg/' | parallel -m rm
The first will run rm 10000 times, while the last will only run rm as many times needed to keep the command line length short enough to avoid Argument list too long (it typically runs 1-2 times).
You could also run:
seq -w 0 9999 | parallel -X rm pict{}.jpg
This will also only run rm as many times needed to keep the command line length short enough.
If ImageMagick is installed this will generate a thumbnail of a jpg file:
convert -geometry 120 foo.jpg thumb_foo.jpg
This will run with number-of-cpu-cores jobs in parallel for all jpg files in a directory:
ls *.jpg | parallel convert -geometry 120 {} thumb_{}
To do it recursively use find:
find . -name '*.jpg' | parallel convert -geometry 120 {} {}_thumb.jpg
Notice how the argument has to start with {} as {} will include path (e.g. running convert -geometry 120 ./foo/bar.jpg thumb_./foo/bar.jpg would clearly be wrong). The command will generate files like ./foo/bar.jpg_thumb.jpg.
Use {.} to avoid the extra .jpg in the file name. This command will make files like ./foo/bar_thumb.jpg:
find . -name '*.jpg' | parallel convert -geometry 120 {} {.}_thumb.jpg
This will generate an uncompressed version of .gz-files next to the .gz-file:
parallel zcat {} ">"{.} ::: *.gz
Quoting of > is necessary to postpone the redirection. Another solution is to quote the whole command:
parallel "zcat {} >{.}" ::: *.gz
Other special shell characters (such as * ; $ > < | >> <<) also need to be put in quotes, as they may otherwise be interpreted by the shell and not given to GNU parallel.
A job can consist of several commands. This will print the number of files in each directory:
ls | parallel 'echo -n {}" "; ls {}|wc -l'
To put the output in a file called <name>.dir:
ls | parallel '(echo -n {}" "; ls {}|wc -l) >{}.dir'
Even small shell scripts can be run by GNU parallel:
find . | parallel 'a={}; name=${a##*/};' \
'upper=$(echo "$name" | tr "[:lower:]" "[:upper:]");'\
'echo "$name - $upper"'
ls | parallel 'mv {} "$(echo {} | tr "[:upper:]" "[:lower:]")"'
Given a list of URLs, list all URLs that fail to download. Print the line number and the URL.
cat urlfile | parallel "wget {} 2>/dev/null || grep -n {} urlfile"
Create a mirror directory with the same filenames except all files and symlinks are empty files.
cp -rs /the/source/dir mirror_dir
find mirror_dir -type l | parallel -m rm {} '&&' touch {}
Find the files in a list that do not exist
cat file_list | parallel 'if [ ! -e {} ] ; then echo {}; fi'
You have a dir with files named as 24 hours in 5 minute intervals: 00:00, 00:05, 00:10 .. 23:55. You want to find the files missing:
parallel [ -f {1}:{2} ] "||" echo {1}:{2} does not exist ::: {00..23} ::: {00..55..5}
If the composed command is longer than a line, it becomes hard to read. In Bash you can use functions. Just remember to export -f the function.
doit() {
echo Doing it for $1
sleep 2
echo Done with $1
}
export -f doit
parallel doit ::: 1 2 3
doubleit() {
echo Doing it for $1 $2
sleep 2
echo Done with $1 $2
}
export -f doubleit
parallel doubleit ::: 1 2 3 ::: a b
To do this on remote servers you need to transfer the function using --env:
parallel --env doit -S server doit ::: 1 2 3 parallel --env doubleit -S server doubleit ::: 1 2 3 ::: a b
If your environment (aliases, variables, and functions) is small you can copy the full environment without having to export -f anything. See env_parallel.
To test a program with different parameters:
tester() {
if (eval "$@") >&/dev/null; then
perl -e 'printf "\033[30;102m[ OK ]\033[0m @ARGV\n"' "$@"
else
perl -e 'printf "\033[30;101m[FAIL]\033[0m @ARGV\n"' "$@"
fi
}
export -f tester
parallel tester my_program ::: arg1 arg2
parallel tester exit ::: 1 0 2 0
If my_program fails a red FAIL will be printed followed by the failing command; otherwise a green OK will be printed followed by the command.
Log rotation renames a logfile to an extension with a higher number: log.1 becomes log.2, log.2 becomes log.3, and so on. The oldest log is removed. To avoid overwriting files the process starts backwards from the high number to the low number. This will keep 10 old versions of the log:
seq 9 -1 1 | parallel -j1 mv log.{} log.'{= $_++ =}'
mv log log.1
When processing files removing the file extension using {.} is often useful.
Create a directory for each zip-file and unzip it in that dir:
parallel 'mkdir {.}; cd {.}; unzip ../{}' ::: *.zip
Recompress all .gz files in current directory using bzip2 running 1 job per CPU core in parallel:
parallel "zcat {} | bzip2 >{.}.bz2 && rm {}" ::: *.gz
Convert all WAV files to MP3 using LAME:
find sounddir -type f -name '*.wav' | parallel lame {} -o {.}.mp3
Put all converted in the same directory:
find sounddir -type f -name '*.wav' | \
parallel lame {} -o mydir/{/.}.mp3
If you have directory with tar.gz files and want these extracted in the corresponding dir (e.g foo.tar.gz will be extracted in the dir foo) you can do:
parallel --plus 'mkdir {..}; tar -C {..} -xf {}' ::: *.tar.gz
Let us assume a website stores images like:
http://www.example.com/path/to/YYYYMMDD_##.jpg
where YYYYMMDD is the date and ## is the number 01-24. This will download images for the past 30 days:
parallel wget http://www.example.com/path/to/'$(date -d "today -{1} days" +%Y%m%d)_{2}.jpg' ::: $(seq 30) ::: $(seq -w 24)
$(date -d "today -{1} days" +%Y%m%d) will give the dates in YYYYMMDD with {1} days subtracted.
find . | parallel cp {} \
'../destdir/{= $a=int(10000*rand); $_=`date -r "$_" +%FT%T"$a"`; chomp; =}'
{= and =} mark a perl expression. date +%FT%T is the date in ISO8601 with time.
The : in a digital clock blinks. To make every other line have a ':' and the rest a ' ' a perl expression is used to look at the 3rd input source. If the value modudo 2 is 1: Use ":" otherwise use " ":
parallel -k echo {1}'{=3 $_=$_%2?":":" "=}'{2}{3} \
::: {0..12} ::: {0..5} ::: {0..9}
This:
parallel --header : echo x{X}y{Y}z{Z} \> x{X}y{Y}z{Z} \
::: X {1..5} ::: Y {01..10} ::: Z {1..5}
will generate the files x1y01z1 .. x5y10z5. If you want to aggregate the output grouping on x and z you can do this:
parallel eval 'cat {=s/y01/y*/=} > {=s/y01//=}' ::: *y01*
For all values of x and z it runs commands like:
cat x1y*z1 > x1z1
So you end up with x1z1 .. x5z5 each containing the content of all values of y.
This script below will crawl and mirror a URL in parallel. It downloads first pages that are 1 click down, then 2 clicks down, then 3; instead of the normal depth first, where the first link link on each page is fetched first.
Run like this:
PARALLEL=-j100 ./parallel-crawl http://gatt.org.yeslab.org/
Remove the wget part if you only want a web crawler.
It works by fetching a page from a list of URLs and looking for links in that page that are within the same starting URL and that have not already been seen. These links are added to a new queue. When all the pages from the list is done, the new queue is moved to the list of URLs and the process is started over until no unseen links are found.
#!/bin/bash
# E.g. http://gatt.org.yeslab.org/
URL=$1
# Stay inside the start dir
BASEURL=$(echo $URL | perl -pe 's:#.*::; s:(//.*/)[^/]*:$1:')
URLLIST=$(mktemp urllist.XXXX)
URLLIST2=$(mktemp urllist.XXXX)
SEEN=$(mktemp seen.XXXX)
# Spider to get the URLs
echo $URL >$URLLIST
cp $URLLIST $SEEN
while [ -s $URLLIST ] ; do
cat $URLLIST |
parallel lynx -listonly -image_links -dump {} \; \
wget -qm -l1 -Q1 {} \; echo Spidered: {} \>\&2 |
perl -ne 's/#.*//; s/\s+\d+.\s(\S+)$/$1/ and do { $seen{$1}++ or print }' |
grep -F $BASEURL |
grep -v -x -F -f $SEEN | tee -a $SEEN > $URLLIST2
mv $URLLIST2 $URLLIST
done
rm -f $URLLIST $URLLIST2 $SEEN
If the files to be processed are in a tar file then unpacking one file and processing it immediately may be faster than first unpacking all files.
tar xvf foo.tgz | perl -ne 'print $l;$l=$_;END{print $l}' | \
parallel echo
The Perl one-liner is needed to make sure the file is complete before handing it to GNU parallel.
for-loops like this:
(for x in `cat list` ; do
do_something $x
done) | process_output
and while-read-loops like this:
cat list | (while read x ; do
do_something $x
done) | process_output
can be written like this:
cat list | parallel do_something | process_output
For example: Find which host name in a list has IP address 1.2.3 4:
cat hosts.txt | parallel -P 100 host | grep 1.2.3.4
If the processing requires more steps the for-loop like this:
(for x in `cat list` ; do
no_extension=${x%.*};
do_something $x scale $no_extension.jpg
do_step2 <$x $no_extension
done) | process_output
and while-loops like this:
cat list | (while read x ; do
no_extension=${x%.*};
do_something $x scale $no_extension.jpg
do_step2 <$x $no_extension
done) | process_output
can be written like this:
cat list | parallel "do_something {} scale {.}.jpg ; do_step2 <{} {.}" |\
process_output
If the body of the loop is bigger, it improves readability to use a function:
(for x in `cat list` ; do
do_something $x
[... 100 lines that do something with $x ...]
done) | process_output
cat list | (while read x ; do
do_something $x
[... 100 lines that do something with $x ...]
done) | process_output
can both be rewritten as:
doit() {
x=$1
do_something $x
[... 100 lines that do something with $x ...]
}
export -f doit
cat list | parallel doit
Nested for-loops like this:
(for x in `cat xlist` ; do
for y in `cat ylist` ; do
do_something $x $y
done
done) | process_output
can be written like this:
parallel do_something {1} {2} :::: xlist ylist | process_output
Nested for-loops like this:
(for colour in red green blue ; do
for size in S M L XL XXL ; do
echo $colour $size
done
done) | sort
can be written like this:
parallel echo {1} {2} ::: red green blue ::: S M L XL XXL | sort
diff is good for finding differences in text files. diff | wc -l gives an indication of the size of the difference. To find the differences between all files in the current dir do:
parallel --tag 'diff {1} {2} | wc -l' ::: * ::: * | sort -nk3
This way it is possible to see if some files are closer to other files.
When doing multiple nested for-loops it can be easier to keep track of the loop variable if is is named instead of just having a number. Use --header : to let the first argument be an named alias for the positional replacement string:
parallel --header : echo {colour} {size} ::: colour red green blue ::: size S M L XL XXL
This also works if the input file is a file with columns:
cat addressbook.tsv | \
parallel --colsep '\t' --header : echo {Name} {E-mail address}
Using --results the results are saved in /tmp/diffcount*.
parallel --results /tmp/diffcount "diff -U 0 {1} {2} | \
tail -n +3 |grep -v '^@'|wc -l" ::: * ::: *
To see the difference between file A and file B look at the file '/tmp/diffcount/1/A/2/B'.
Starting a job on the local machine takes around 10 ms. This can be a big overhead if the job takes very few ms to run. Often you can group small jobs together using -X which will make the overhead less significant. Compare the speed of these:
seq -w 0 9999 | parallel touch pict{}.jpg
seq -w 0 9999 | parallel -X touch pict{}.jpg
If your program cannot take multiple arguments, then you can use GNU parallel to spawn multiple GNU parallels:
seq -w 0 999999 | parallel -j10 --pipe parallel -j0 touch pict{}.jpg
If -j0 normally spawns 252 jobs, then the above will try to spawn 2520 jobs. On a normal GNU/Linux system you can spawn 32000 jobs using this technique with no problems. To raise the 32000 jobs limit raise /proc/sys/kernel/pid_max to 4194303.
When using shell variables you need to quote them correctly as they may otherwise be split on spaces.
Notice the difference between:
V=("My brother's 12\" records are worth <\$\$\$>"'!' Foo Bar)
parallel echo ::: ${V[@]} # This is probably not what you want
and:
V=("My brother's 12\" records are worth <\$\$\$>"'!' Foo Bar)
parallel echo ::: "${V[@]}"
When using variables in the actual command that contains special characters (e.g. space) you can quote them using '"$VAR"' or using "'s and -q:
V="Here are two " parallel echo "'$V'" ::: spaces parallel -q echo "$V" ::: spaces
When running jobs that output data, you often do not want the output of multiple jobs to run together. GNU parallel defaults to grouping the output of each job, so the output is printed when the job finishes. If you want full lines to be printed while the job is running you can use --line-buffer. If you want output to be printed as soon as possible you can use -u.
Compare the output of:
parallel traceroute ::: qubes-os.org debian.org freenetproject.org parallel --line-buffer traceroute ::: qubes-os.org debian.org freenetproject.org parallel -u traceroute ::: qubes-os.org debian.org freenetproject.org
GNU parallel groups the output lines, but it can be hard to see where the different jobs begin. --tag prepends the argument to make that more visible:
parallel --tag traceroute ::: qubes-os.org debian.org freenetproject.org
--tag works with --line-buffer but not with -u:
parallel --tag --line-buffer traceroute \
::: qubes-os.org debian.org freenetproject.org
Check the uptime of the servers in ~/.parallel/sshloginfile:
parallel --tag -S .. --nonall uptime
Normally the output of a job will be printed as soon as it completes. Sometimes you want the order of the output to remain the same as the order of the input. This is often important, if the output is used as input for another system. -k will make sure the order of output will be in the same order as input even if later jobs end before earlier jobs.
Append a string to every line in a text file:
cat textfile | parallel -k echo {} append_string
If you remove -k some of the lines may come out in the wrong order.
Another example is traceroute:
parallel traceroute ::: qubes-os.org debian.org freenetproject.org
will give traceroute of qubes-os.org, debian.org and freenetproject.org, but it will be sorted according to which job completed first.
To keep the order the same as input run:
parallel -k traceroute ::: qubes-os.org debian.org freenetproject.org
This will make sure the traceroute to qubes-os.org will be printed first.
A bit more complex example is downloading a huge file in chunks in parallel: Some internet connections will deliver more data if you download files in parallel. For downloading files in parallel see: "EXAMPLE: Download 10 images for each of the past 30 days". But if you are downloading a big file you can download the file in chunks in parallel.
To download byte 10000000-19999999 you can use curl:
curl -r 10000000-19999999 http://example.com/the/big/file >file.part
To download a 1 GB file we need 100 10MB chunks downloaded and combined in the correct order.
seq 0 99 | parallel -k curl -r \
{}0000000-{}9999999 http://example.com/the/big/file > file
grep -r greps recursively through directories. On multicore CPUs GNU parallel can often speed this up.
find . -type f | parallel -k -j150% -n 1000 -m grep -H -n STRING {}
This will run 1.5 job per core, and give 1000 arguments to grep.
The simplest solution to grep a big file for a lot of regexps is:
grep -f regexps.txt bigfile
Or if the regexps are fixed strings:
grep -F -f regexps.txt bigfile
There are 3 limiting factors: CPU, RAM, and disk I/O.
RAM is easy to measure: If the grep process takes up most of your free memory (e.g. when running top), then RAM is a limiting factor.
CPU is also easy to measure: If the grep takes >90% CPU in top, then the CPU is a limiting factor, and parallelization will speed this up.
It is harder to see if disk I/O is the limiting factor, and depending on the disk system it may be faster or slower to parallelize. The only way to know for certain is to test and measure.
The normal grep -f regexs.txt bigfile works no matter the size of bigfile, but if regexps.txt is so big it cannot fit into memory, then you need to split this.
grep -F takes around 100 bytes of RAM and grep takes about 500 bytes of RAM per 1 byte of regexp. So if regexps.txt is 1% of your RAM, then it may be too big.
If you can convert your regexps into fixed strings do that. E.g. if the lines you are looking for in bigfile all looks like:
ID1 foo bar baz Identifier1 quux fubar ID2 foo bar baz Identifier2
then your regexps.txt can be converted from:
ID1.*Identifier1 ID2.*Identifier2
into:
ID1 foo bar baz Identifier1 ID2 foo bar baz Identifier2
This way you can use grep -F which takes around 80% less memory and is much faster.
If it still does not fit in memory you can do this:
parallel --pipepart -a regexps.txt --block 1M grep -F -f - -n bigfile |
sort -un | perl -pe 's/^\d+://'
The 1M should be your free memory divided by the number of cores and divided by 200 for grep -F and by 1000 for normal grep. On GNU/Linux you can do:
free=$(awk '/^((Swap)?Cached|MemFree|Buffers):/ { sum += $2 }
END { print sum }' /proc/meminfo)
percpu=$((free / 200 / $(parallel --number-of-cores)))k
parallel --pipepart -a regexps.txt --block $percpu --compress grep -F -f - -n bigfile |
sort -un | perl -pe 's/^\d+://'
If you can live with duplicated lines and wrong order, it is faster to do:
parallel --pipepart -a regexps.txt --block $percpu --compress grep -F -f - bigfile
If the CPU is the limiting factor parallelization should be done on the regexps:
cat regexp.txt | parallel --pipe -L1000 --round-robin --compress grep -f - -n bigfile |
sort -un | perl -pe 's/^\d+://'
The command will start one grep per CPU and read bigfile one time per CPU, but as that is done in parallel, all reads except the first will be cached in RAM. Depending on the size of regexp.txt it may be faster to use --block 10m instead of -L1000.
Some storage systems perform better when reading multiple chunks in parallel. This is true for some RAID systems and for some network file systems. To parallelize the reading of bigfile:
parallel --pipepart --block 100M -a bigfile -k --compress grep -f regexp.txt
This will split bigfile into 100MB chunks and run grep on each of these chunks. To parallelize both reading of bigfile and regexp.txt combine the two using --fifo:
parallel --pipepart --block 100M -a bigfile --fifo cat regexp.txt \
\| parallel --pipe -L1000 --round-robin grep -f - {}
If a line matches multiple regexps, the line may be duplicated.
If the problem is too big to be solved by this, you are probably ready for Lucene.
To run commands on a remote computer SSH needs to be set up and you must be able to login without entering a password (The commands ssh-copy-id, ssh-agent, and sshpass may help you do that).
If you need to login to a whole cluster, you typically do not want to accept the host key for every host. You want to accept them the first time and be warned if they are ever changed. To do that:
# Add the servers to the sshloginfile (echo servera; echo serverb) > .parallel/my_cluster # Make sure .ssh/config exist touch .ssh/config cp .ssh/config .ssh/config.backup # Disable StrictHostKeyChecking temporarily (echo 'Host *'; echo StrictHostKeyChecking no) >> .ssh/config parallel --slf my_cluster --nonall true # Remove the disabling of StrictHostKeyChecking mv .ssh/config.backup .ssh/config
The servers in .parallel/my_cluster are now added in .ssh/known_hosts.
To run echo on server.example.com:
seq 10 | parallel --sshlogin server.example.com echo
To run commands on more than one remote computer run:
seq 10 | parallel --sshlogin server.example.com,server2.example.net echo
Or:
seq 10 | parallel --sshlogin server.example.com \
--sshlogin server2.example.net echo
If the login username is foo on server2.example.net use:
seq 10 | parallel --sshlogin server.example.com \
--sshlogin foo@server2.example.net echo
If your list of hosts is server1-88.example.net with login foo:
seq 10 | parallel -Sfoo@server{1..88}.example.net echo
To distribute the commands to a list of computers, make a file mycomputers with all the computers:
server.example.com foo@server2.example.com server3.example.com
Then run:
seq 10 | parallel --sshloginfile mycomputers echo
To include the local computer add the special sshlogin ':' to the list:
server.example.com foo@server2.example.com server3.example.com :
GNU parallel will try to determine the number of CPU cores on each of the remote computers, and run one job per CPU core - even if the remote computers do not have the same number of CPU cores.
If the number of CPU cores on the remote computers is not identified correctly the number of CPU cores can be added in front. Here the computer has 8 CPU cores.
seq 10 | parallel --sshlogin 8/server.example.com echo
To recompress gzipped files with bzip2 using a remote computer run:
find logs/ -name '*.gz' | \
parallel --sshlogin server.example.com \
--transfer "zcat {} | bzip2 -9 >{.}.bz2"
This will list the .gz-files in the logs directory and all directories below. Then it will transfer the files to server.example.com to the corresponding directory in $HOME/logs. On server.example.com the file will be recompressed using zcat and bzip2 resulting in the corresponding file with .gz replaced with .bz2.
If you want the resulting bz2-file to be transferred back to the local computer add --return {.}.bz2:
find logs/ -name '*.gz' | \
parallel --sshlogin server.example.com \
--transfer --return {.}.bz2 "zcat {} | bzip2 -9 >{.}.bz2"
After the recompressing is done the .bz2-file is transferred back to the local computer and put next to the original .gz-file.
If you want to delete the transferred files on the remote computer add --cleanup. This will remove both the file transferred to the remote computer and the files transferred from the remote computer:
find logs/ -name '*.gz' | \
parallel --sshlogin server.example.com \
--transfer --return {.}.bz2 --cleanup "zcat {} | bzip2 -9 >{.}.bz2"
If you want run on several computers add the computers to --sshlogin either using ',' or multiple --sshlogin:
find logs/ -name '*.gz' | \
parallel --sshlogin server.example.com,server2.example.com \
--sshlogin server3.example.com \
--transfer --return {.}.bz2 --cleanup "zcat {} | bzip2 -9 >{.}.bz2"
You can add the local computer using --sshlogin :. This will disable the removing and transferring for the local computer only:
find logs/ -name '*.gz' | \
parallel --sshlogin server.example.com,server2.example.com \
--sshlogin server3.example.com \
--sshlogin : \
--transfer --return {.}.bz2 --cleanup "zcat {} | bzip2 -9 >{.}.bz2"
Often --transfer, --return and --cleanup are used together. They can be shortened to --trc:
find logs/ -name '*.gz' | \
parallel --sshlogin server.example.com,server2.example.com \
--sshlogin server3.example.com \
--sshlogin : \
--trc {.}.bz2 "zcat {} | bzip2 -9 >{.}.bz2"
With the file mycomputers containing the list of computers it becomes:
find logs/ -name '*.gz' | parallel --sshloginfile mycomputers \
--trc {.}.bz2 "zcat {} | bzip2 -9 >{.}.bz2"
If the file ~/.parallel/sshloginfile contains the list of computers the special short hand -S .. can be used:
find logs/ -name '*.gz' | parallel -S .. \
--trc {.}.bz2 "zcat {} | bzip2 -9 >{.}.bz2"
Convert *.mp3 to *.ogg running one process per CPU core on local computer and server2:
parallel --trc {.}.ogg -S server2,: \
'mpg321 -w - {} | oggenc -q0 - -o {.}.ogg' ::: *.mp3
To run the command uptime on remote computers you can do:
parallel --tag --nonall -S server1,server2 uptime
--nonall reads no arguments. If you have a list of jobs you want run on each computer you can do:
parallel --tag --onall -S server1,server2 echo ::: 1 2 3
Remove --tag if you do not want the sshlogin added before the output.
If you have a lot of hosts use '-j0' to access more hosts in parallel.
If the workers are behind a NAT wall, you need some trickery to get to them.
If you can ssh to a jump host, and reach the workers from there, then the obvious solution would be this, but it does not work:
parallel --ssh 'ssh jumphost ssh' -S host1 echo ::: DOES NOT WORK
It does not work because the command is dequoted by ssh twice where as GNU parallel only expects it to be dequoted once.
So instead put this in ~/.ssh/config:
Host host1 host2 host3
ProxyCommand ssh jumphost.domain nc -w 1 %h 22
It requires nc(netcat) to be installed on jumphost. With this you can simply:
parallel -S host1,host2,host3 echo ::: This does work
If there is no jumphost but each server has port 22 forwarded from the firewall (e.g. the firewall's port 22001 = port 22 on host1, 22002 = host2, 22003 = host3) then you can use ~/.ssh/config:
Host host1.v
Port 22001
Host host2.v
Port 22002
Host host3.v
Port 22003
Host *.v
Hostname firewall
And then use host{1..3}.v as normal hosts:
parallel -S host1.v,host2.v,host3.v echo ::: a b c
If ports cannot be forwarded, you need some sort of VPN to traverse the NAT-wall. TOR is one options for that, as it is very easy to get working.
You need to install TOR and setup a hidden service. In torrc put:
HiddenServiceDir /var/lib/tor/hidden_service/ HiddenServicePort 22 127.0.0.1:22
Then start TOR: /etc/init.d/tor restart
The TOR hostname is now in /var/lib/tor/hidden_service/hostname and is something similar to izjafdceobowklhz.onion. Now you simply prepend torsocks to ssh:
parallel --ssh 'torsocks ssh' -S izjafdceobowklhz.onion \
-S zfcdaeiojoklbwhz.onion,auclucjzobowklhi.onion echo ::: a b c
If not all hosts are accessible through TOR:
parallel -S 'torsocks ssh izjafdceobowklhz.onion,host2,host3' echo ::: a b c
See more ssh tricks on https://en.wikibooks.org/wiki/OpenSSH/Cookbook/Proxies_and_Jump_Hosts
rsync is a great tool, but sometimes it will not fill up the available bandwidth. This is often a problem when copying several big files over high speed connections.
The following will start one rsync per big file in src-dir to dest-dir on the server fooserver:
cd src-dir; find . -type f -size +100000 | \
parallel -v ssh fooserver mkdir -p /dest-dir/{//}\; \
rsync -s -Havessh {} fooserver:/dest-dir/{}
The dirs created may end up with wrong permissions and smaller files are not being transferred. To fix those run rsync a final time:
rsync -Havessh src-dir/ fooserver:/dest-dir/
If you are unable to push data, but need to pull them and the files are called digits.png (e.g. 000000.png) you might be able to do:
seq -w 0 99 | parallel rsync -Havessh fooserver:src-path/*{}.png destdir/
Copy files like foo.es.ext to foo.ext:
ls *.es.* | perl -pe 'print; s/\.es//' | parallel -N2 cp {1} {2}
The perl command spits out 2 lines for each input. GNU parallel takes 2 inputs (using -N2) and replaces {1} and {2} with the inputs.
Count in binary:
parallel -k echo ::: 0 1 ::: 0 1 ::: 0 1 ::: 0 1 ::: 0 1 ::: 0 1
Print the number on the opposing sides of a six sided die:
parallel --link -a <(seq 6) -a <(seq 6 -1 1) echo parallel --link echo :::: <(seq 6) <(seq 6 -1 1)
Convert files from all subdirs to PNG-files with consecutive numbers (useful for making input PNG's for ffmpeg):
parallel --link -a <(find . -type f | sort) \
-a <(seq $(find . -type f|wc -l)) convert {1} {2}.png
Alternative version:
find . -type f | sort | parallel convert {} {#}.png
Content of table_file.tsv:
foo<TAB>bar baz <TAB> quux
To run:
cmd -o bar -i foo cmd -o quux -i baz
you can run:
parallel -a table_file.tsv --colsep '\t' cmd -o {2} -i {1}
Note: The default for GNU parallel is to remove the spaces around the columns. To keep the spaces:
parallel -a table_file.tsv --trim n --colsep '\t' cmd -o {2} -i {1}
GNU parallel can output to a database table and a CSV-file:
DBURL=csv:///%2Ftmp%2Fmy.csv
DBTABLEURL=$DBURL/mytable
parallel --sqlandworker $DBTABLEURL seq ::: {1..10}
It is rather slow and takes up a lot of CPU time because GNU parallel parses the whole CSV file for each update.
A better approach is to use an SQLite-base and then convert that to CSV:
DBURL=sqlite3:///%2Ftmp%2Fmy.sqlite
DBTABLEURL=$DBURL/mytable
parallel --sqlandworker $DBTABLEURL seq ::: {1..10}
sql $DBURL '.headers on' '.mode csv' 'SELECT * FROM mytable;'
This takes around a second per job.
If you have access to a real database system, such as PostgreSQL, it is even faster:
DBURL=pg://user:pass@host/mydb
DBTABLEURL=$DBURL/mytable
parallel --sqlandworker $DBTABLEURL seq ::: {1..10}
sql $DBURL "COPY (SELECT * FROM mytable) TO stdout DELIMITER ',' CSV HEADER;"
Or MySQL:
DBURL=mysql://user:pass@host/mydb
DBTABLEURL=$DBURL/mytable
parallel --sqlandworker $DBTABLEURL seq ::: {1..10}
sql -p -B $DBURL "SELECT * FROM mytable;" > mytable.tsv
perl -pe 's/"/""/g;s/\t/","/g;s/^/"/;s/$/"/;s/\\\\/\\/g;s/\\t/\t/g;s/\\n/\n/g;' mytable.tsv
If you have no need for the advanced job distribution control that a database provides, but you simply want output into a CSV file that you can read into R or LibreCalc, then you can use --results:
parallel --results my.csv seq ::: 10 20 30
R
> mydf <- read.csv("my.csv");
> print(mydf[2,])
> write(as.character(mydf[2,c("Stdout")]),'')
If you want to run the same command with the same arguments 10 times in parallel you can do:
seq 10 | parallel -n0 my_command my_args
GNU parallel can work similar to cat | sh.
A resource inexpensive job is a job that takes very little CPU, disk I/O and network I/O. Ping is an example of a resource inexpensive job. wget is too - if the webpages are small.
The content of the file jobs_to_run:
ping -c 1 10.0.0.1 wget http://example.com/status.cgi?ip=10.0.0.1 ping -c 1 10.0.0.2 wget http://example.com/status.cgi?ip=10.0.0.2 ... ping -c 1 10.0.0.255 wget http://example.com/status.cgi?ip=10.0.0.255
To run 100 processes simultaneously do:
parallel -j 100 < jobs_to_run
As there is not a command the jobs will be evaluated by the shell.
To process a big file or some output you can use --pipe to split up the data into blocks and pipe the blocks into the processing program.
If the program is gzip -9 you can do:
cat bigfile | parallel --pipe --recend '' -k gzip -9 > bigfile.gz
This will split bigfile into blocks of 1 MB and pass that to gzip -9 in parallel. One gzip will be run per CPU core. The output of gzip -9 will be kept in order and saved to bigfile.gz
gzip works fine if the output is appended, but some processing does not work like that - for example sorting. For this GNU parallel can put the output of each command into a file. This will sort a big file in parallel:
cat bigfile | parallel --pipe --files sort |\
parallel -Xj1 sort -m {} ';' rm {} >bigfile.sort
Here bigfile is split into blocks of around 1MB, each block ending in '\n' (which is the default for --recend). Each block is passed to sort and the output from sort is saved into files. These files are passed to the second parallel that runs sort -m on the files before it removes the files. The output is saved to bigfile.sort.
GNU parallel's --pipe maxes out at around 100 MB/s because every byte has to be copied through GNU parallel. But if bigfile is a real (seekable) file GNU parallel can by-pass the copying and send the parts directly to the program:
parallel --pipepart --block 100m -a bigfile --files sort |\
parallel -Xj1 sort -m {} ';' rm {} >bigfile.sort
If you need to run a massive amount of jobs in parallel, then you will likely hit the filehandle limit which is often around 250 jobs. If you are super user you can raise the limit in /etc/security/limits.conf but you can also use this workaround. The filehandle limit is per process. That means that if you just spawn more GNU parallels then each of them can run 250 jobs. This will spawn up to 2500 jobs:
cat myinput |\
parallel --pipe -N 50 --round-robin -j50 parallel -j50 your_prg
This will spawn up to 62500 jobs (use with caution - you need 64 GB RAM to do this, and you may need to increase /proc/sys/kernel/pid_max):
cat myinput |\
parallel --pipe -N 250 --round-robin -j250 parallel -j250 your_prg
The command sem is an alias for parallel --semaphore.
A counting semaphore will allow a given number of jobs to be started in the background. When the number of jobs are running in the background, GNU sem will wait for one of these to complete before starting another command. sem --wait will wait for all jobs to complete.
Run 10 jobs concurrently in the background:
for i in *.log ; do
echo $i
sem -j10 gzip $i ";" echo done
done
sem --wait
A mutex is a counting semaphore allowing only one job to run. This will edit the file myfile and prepends the file with lines with the numbers 1 to 3.
seq 3 | parallel sem sed -i -e 'i{}' myfile
As myfile can be very big it is important only one process edits the file at the same time.
Name the semaphore to have multiple different semaphores active at the same time:
seq 3 | parallel sem --id mymutex sed -i -e 'i{}' myfile
Assume a script is called from cron or from a web service, but only one instance can be run at a time. With sem and --shebang-wrap the script can be made to wait for other instances to finish. Here in bash:
#!/usr/bin/sem --shebang-wrap -u --id $0 --fg /bin/bash echo This will run sleep 5 echo exclusively
Here perl:
#!/usr/bin/sem --shebang-wrap -u --id $0 --fg /usr/bin/perl print "This will run "; sleep 5; print "exclusively\n";
Here python:
#!/usr/local/bin/sem --shebang-wrap -u --id $0 --fg /usr/bin/python import time print "This will run "; time.sleep(5) print "exclusively";
You can use GNU parallel to start interactive programs like emacs or vi:
cat filelist | parallel --tty -X emacs cat filelist | parallel --tty -X vi
If there are more files than will fit on a single command line, the editor will be started again with the remaining files.
sudo requires a password to run a command as root. It caches the access, so you only need to enter the password again if you have not used sudo for a while.
The command:
parallel sudo echo ::: This is a bad idea
is no good, as you would be prompted for the sudo password for each of the jobs. You can either do:
sudo echo This parallel sudo echo ::: is a good idea
or:
sudo parallel echo ::: This is a good idea
This way you only have to enter the sudo password once.
GNU parallel can work as a simple job queue system or batch manager. The idea is to put the jobs into a file and have GNU parallel read from that continuously. As GNU parallel will stop at end of file we use tail to continue reading:
true >jobqueue; tail -n+0 -f jobqueue | parallel
To submit your jobs to the queue:
echo my_command my_arg >> jobqueue
You can of course use -S to distribute the jobs to remote computers:
true >jobqueue; tail -n+0 -f jobqueue | parallel -S ..
If you keep this running for a long time, jobqueue will grow. A way of removing the jobs already run is by making GNU parallel stop when it hits a special value and then restart. To use --eof to make GNU parallel exit, tail also needs to be forced to exit:
true >jobqueue;
while true; do
tail -n+0 -f jobqueue |
(parallel -E StOpHeRe -S ..; echo GNU Parallel is now done;
perl -e 'while(<>){/StOpHeRe/ and last};print <>' jobqueue > j2;
(seq 1000 >> jobqueue &);
echo Done appending dummy data forcing tail to exit)
echo tail exited;
mv j2 jobqueue
done
In some cases you can run on more CPUs and computers during the night:
# Day time echo 50% > jobfile cp day_server_list ~/.parallel/sshloginfile # Night time echo 100% > jobfile cp night_server_list ~/.parallel/sshloginfile tail -n+0 -f jobqueue | parallel --jobs jobfile -S ..
GNU Parallel discovers if jobfile or ~/.parallel/sshloginfile changes.
There is a a small issue when using GNU parallel as queue system/batch manager: You have to submit JobSlot number of jobs before they will start, and after that you can submit one at a time, and job will start immediately if free slots are available. Output from the running or completed jobs are held back and will only be printed when JobSlots more jobs has been started (unless you use --ungroup or --line-buffer, in which case the output from the jobs are printed immediately). E.g. if you have 10 jobslots then the output from the first completed job will only be printed when job 11 has started, and the output of second completed job will only be printed when job 12 has started.
If you have a dir in which users drop files that needs to be processed you can do this on GNU/Linux (If you know what inotifywait is called on other platforms file a bug report):
inotifywait -q -m -r -e MOVED_TO -e CLOSE_WRITE --format %w%f my_dir |\
parallel -u echo
This will run the command echo on each file put into my_dir or subdirs of my_dir.
You can of course use -S to distribute the jobs to remote computers:
inotifywait -q -m -r -e MOVED_TO -e CLOSE_WRITE --format %w%f my_dir |\
parallel -S .. -u echo
If the files to be processed are in a tar file then unpacking one file and processing it immediately may be faster than first unpacking all files. Set up the dir processor as above and unpack into the dir.
Using GNU Parallel as dir processor has the same limitations as using GNU Parallel as queue system/batch manager.
GNU parallel is very liberal in quoting. You only need to quote characters that have special meaning in shell:
( ) $ ` ' " < > ; | \
and depending on context these needs to be quoted, too:
~ & # ! ? space * {
Therefore most people will never need more quoting than putting '\' in front of the special characters.
Often you can simply put \' around every ':
perl -ne '/^\S+\s+\S+$/ and print $ARGV,"\n"' file
can be quoted:
parallel perl -ne \''/^\S+\s+\S+$/ and print $ARGV,"\n"'\' ::: file
However, when you want to use a shell variable you need to quote the $-sign. Here is an example using $PARALLEL_SEQ. This variable is set by GNU parallel itself, so the evaluation of the $ must be done by the sub shell started by GNU parallel:
seq 10 | parallel -N2 echo seq:\$PARALLEL_SEQ arg1:{1} arg2:{2}
If the variable is set before GNU parallel starts you can do this:
VAR=this_is_set_before_starting
echo test | parallel echo {} $VAR
Prints: test this_is_set_before_starting
It is a little more tricky if the variable contains more than one space in a row:
VAR="two spaces between each word"
echo test | parallel echo {} \'"$VAR"\'
Prints: test two spaces between each word
If the variable should not be evaluated by the shell starting GNU parallel but be evaluated by the sub shell started by GNU parallel, then you need to quote it:
echo test | parallel VAR=this_is_set_after_starting \; echo {} \$VAR
Prints: test this_is_set_after_starting
It is a little more tricky if the variable contains space:
echo test |\
parallel VAR='"two spaces between each word"' echo {} \'"$VAR"\'
Prints: test two spaces between each word
$$ is the shell variable containing the process id of the shell. This will print the process id of the shell running GNU parallel:
seq 10 | parallel echo $$
And this will print the process ids of the sub shells started by GNU parallel.
seq 10 | parallel echo \$\$
If the special characters should not be evaluated by the sub shell then you need to protect it against evaluation from both the shell starting GNU parallel and the sub shell:
echo test | parallel echo {} \\\$VAR
Prints: test $VAR
GNU parallel can protect against evaluation by the sub shell by using -q:
echo test | parallel -q echo {} \$VAR
Prints: test $VAR
This is particularly useful if you have lots of quoting. If you want to run a perl script like this:
perl -ne '/^\S+\s+\S+$/ and print $ARGV,"\n"' file
It needs to be quoted like one of these:
ls | parallel perl -ne '/^\\S+\\s+\\S+\$/\ and\ print\ \$ARGV,\"\\n\"' ls | parallel perl -ne \''/^\S+\s+\S+$/ and print $ARGV,"\n"'\'
Notice how spaces, \'s, "'s, and $'s need to be quoted. GNU parallel can do the quoting by using option -q:
ls | parallel -q perl -ne '/^\S+\s+\S+$/ and print $ARGV,"\n"'
However, this means you cannot make the sub shell interpret special characters. For example because of -q this WILL NOT WORK:
ls *.gz | parallel -q "zcat {} >{.}"
ls *.gz | parallel -q "zcat {} | bzip2 >{.}.bz2"
because > and | need to be interpreted by the sub shell.
If you get errors like:
sh: -c: line 0: syntax error near unexpected token sh: Syntax error: Unterminated quoted string sh: -c: line 0: unexpected EOF while looking for matching `'' sh: -c: line 1: syntax error: unexpected end of file
then you might try using -q.
If you are using bash process substitution like <(cat foo) then you may try -q and prepending command with bash -c:
ls | parallel -q bash -c 'wc -c <(echo {})'
Or for substituting output:
ls | parallel -q bash -c \
'tar c {} | tee >(gzip >{}.tar.gz) | bzip2 >{}.tar.bz2'
Conclusion: To avoid dealing with the quoting problems it may be easier just to write a small script or a function (remember to export -f the function) and have GNU parallel call that.
If you want a list of the jobs currently running you can run:
killall -USR1 parallel
GNU parallel will then print the currently running jobs on stderr (standard error).
If you regret starting a lot of jobs you can simply break GNU parallel, but if you want to make sure you do not have half-completed jobs you should send the signal SIGTERM to GNU parallel:
killall -TERM parallel
This will tell GNU parallel to not start any new jobs, but wait until the currently running jobs are finished before exiting.
Example: If each of the jobs tests a solution and one of jobs finds the solution the job can tell GNU parallel not to start more jobs by: kill -TERM $PARALLEL_PID. This only works on the local computer.
Example:
seq 10 | parallel -N2 \
echo seq:'$'PARALLEL_SEQ arg1:{1} arg2:{2}
Example:
cat list | parallel -j1 -k -v ls
cat list | parallel -j1 -k -v -S"myssh user@server" ls
can be written as:
cat list | PARALLEL="-kvj1" parallel ls
cat list | PARALLEL='-kvj1 -S myssh\ user@server' \
parallel echo
Notice the \ in the middle is needed because 'myssh' and 'user@server' must be one argument.
The global configuration file /etc/parallel/config, followed by user configuration file ~/.parallel/config (formerly known as .parallelrc) will be read in turn if they exist. Lines starting with '#' will be ignored. The format can follow that of the environment variable $PARALLEL, but it is often easier to simply put each option on its own line.
Options on the command line take precedence, followed by the environment variable $PARALLEL, user configuration file ~/.parallel/config, and finally the global configuration file /etc/parallel/config.
Note that no file that is read for options, nor the environment variable $PARALLEL, may contain retired options such as --tollef.
If --profile set, GNU parallel will read the profile from that file rather than the global or user configuration files. You can have multiple --profiles.
Example: Profile for running a command on every sshlogin in ~/.ssh/sshlogins and prepend the output with the sshlogin:
echo --tag -S .. --nonall > ~/.parallel/n parallel -Jn uptime
Example: Profile for running every command with -j-1 and nice
echo -j-1 nice > ~/.parallel/nice_profile parallel -J nice_profile bzip2 -9 ::: *
Example: Profile for running a perl script before every command:
echo "perl -e '\$a=\$\$; print \$a,\" \",'\$PARALLEL_SEQ',\" \";';" \
> ~/.parallel/pre_perl
parallel -J pre_perl echo ::: *
Note how the $ and " need to be quoted using \.
Example: Profile for running distributed jobs with nice on the remote computers:
echo -S .. nice > ~/.parallel/dist
parallel -J dist --trc {.}.bz2 bzip2 -9 ::: *
Exit status depends on --halt-on-error if one of these are used: success=X, success=Y%, fail=Y%.
If fail=1 is used, the exit status will be the exit status of the failing job.
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.
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
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
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 E1 E2 E3 E4 E5 E6 R1 R2 R3 R4 R5 R6 R7 R8 R9 S1 S2
xargs: I1 I2 - - - - - - M2 M3 - - - - O2 O3 - O5 O6 E1 - - - - - - - - - - x - - - - -
find -exec: - - - x - x - - M2 M3 - - - - - O2 O3 O4 O5 O6 - - - - - - - - - - - - - - - - x x
make -j: - - - - - - - - - - - - - O1 O2 O3 - x O6 E1 - - - E5 - - - - - - - - - - - -
ppss: I1 I2 - - - - I7 M1 - M3 - - M6 O1 - - x - - E1 E2 ?E3 E4 - - R1 R2 R3 R4 - - ?R7 ? ? - -
pexec: I1 I2 - I4 I5 - - M1 - M3 - - M6 O1 O2 O3 - O5 O6 E1 - - E4 - E6 R1 - - - - R6 - - - S1 -
xjobs, prll, dxargs, mdm/middelman, xapply, paexec, ladon, jobflow, ClusterSSH: TODO - Please file a bug-report if you know what features they support (See REPORTING BUGS).
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 head, tail, awk, ls, echo, sed, tar -v, perl (-0 and \0 instead of \n), locate (requires using -0), find (requires using -print0), grep (requires user to use -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
ls -l a b c d e f
parallel -kP4 -n1 grep 1 > out.par ::: a b c d e f
echo a b c d e f | xargs -P4 -n1 grep 1 > out.xargs-unbuf
echo a b c d e f | \
xargs -P4 -n1 grep --line-buffered 1 > out.xargs-linebuf
echo a b c d e f | xargs -n1 grep 1 > out.xargs-serial
ls -l out*
md5sum out*
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)
ls | xargs -d "\n" -P8 -I {} bash -c "wc {} >{}.wc"
ls | xargs -d "\n" -P8 -I {} bash -c "echo {}; ls {}|wc"
find -exec offer some of the same possibilities as GNU parallel.
find -exec only works on files. So 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.
make -j can run jobs in parallel, but requires a crafted Makefile to do this. That results in extra quoting to get filename containing newline to work correctly.
make -j computes a dependency graph before running jobs. Jobs run by GNU parallel does not depend on eachother.
(Very early versions of GNU parallel were coincidently implemented using make -j).
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 ($ITEM) cannot be changed. Arguments must be quoted - thus arguments containing special characters (space '"&!*) may cause problems. More than one argument is not supported. File names containing newlines are not processed correctly. When reading input from a file null cannot be used as a terminator. ppss needs to read the whole input file before starting any jobs.
Output and status information is stored in ppss_dir and thus requires cleanup when completed. If the dir is not removed before running ppss again it may cause nothing to happen as ppss thinks the task is already done. GNU parallel will normally not need cleaning up if running locally and will only need cleaning up if stopped abnormally and running remote (--cleanup may not complete if stopped abnormally). The example Parallel grep would require extra postprocessing if written using ppss.
For remote systems PPSS requires 3 steps: config, deploy, and start. GNU parallel only requires one step.
EXAMPLES FROM ppss MANUAL
Here are the examples from ppss's manual page with the equivalent using GNU parallel:
1 ./ppss.sh standalone -d /path/to/files -c 'gzip '
1 find /path/to/files -type f | parallel gzip
2 ./ppss.sh standalone -d /path/to/files -c 'cp "$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 "$ITEM"'
4 parallel -a list-of-urls.txt wget -q {}
5 ./ppss config -C config.cfg -c 'encode.sh ' -d /source/dir -m 192.168.1.100 -u ppss -k ppss-key.key -S ./encode.sh -n nodes.txt -o /some/output/dir --upload --download ; ./ppss deploy -C config.cfg ; ./ppss start -C config
5 # parallel does not use configs. If you want a different username put it in nodes.txt: user@hostname
5 find source/dir -type f | parallel --sshloginfile nodes.txt --trc {.}.mp3 lame -a {} -o {.}.mp3 --preset standard --quiet
6 ./ppss stop -C config.cfg
6 killall -TERM parallel
7 ./ppss pause -C config.cfg
7 Press: CTRL-Z or killall -SIGTSTP parallel
8 ./ppss continue -C config.cfg
8 Enter: fg or killall -SIGCONT parallel
9 ./ppss.sh status -C config.cfg
9 killall -SIGUSR2 parallel
pexec is also a tool for running jobs in parallel.
EXAMPLES FROM pexec MANUAL
Here are the examples from pexec's info page with the equivalent using GNU parallel:
1 pexec -o sqrt-%s.dat -p "$(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 parallel and GNU sem.
8 ls *jpg | parallel -j8 'sem --id blockread cat {} |
jpegtopnm |' \
'pnmscale 0.5 | pnmtojpeg | sem --id blockwrite cat > th_{}'
8 If reading and writing is done to the same disk, this may be faster as only one process will be either reading or writing:
8 ls *jpg | parallel -j8 'sem --id diskio cat {} |
jpegtopnm |' \
'pnmscale 0.5 | pnmtojpeg | sem --id diskio cat > th_{}'
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.
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
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.
Here is the example from prll's man page with the equivalent using GNU parallel:
prll -s 'mogrify -flip $1' *.jpg parallel mogrify -flip ::: *.jpg
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.
middleman(mdm) is also a tool for running jobs in parallel.
Here are the shellscripts of http://mdm.berlios.de/usage.html ported to GNU parallel:
seq 19 | parallel buffon -o - | sort -n > result
cat files | parallel cmd
find dir -execdir sem cmd {} \;
xapply can run jobs in parallel on the local computer.
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 | ...
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.
Here are the examples from https://www-01.ibm.com/support/knowledgecenter/ssw_aix_71/com.ibm.aix.cmds1/apply.htm
1. To obtain results similar to those of the ls command, enter:
apply echo * parallel echo ::: *
2. To compare the file named a1 to the file named b1, and the file named a2 to the file named b2, enter:
apply -2 cmp a1 b1 a2 b2 parallel -N2 cmp ::: a1 b1 a2 b2
3. To run the who command five times, enter:
apply -0 who 1 2 3 4 5 parallel -N0 who ::: 1 2 3 4 5
4. To link all files in the current directory to the directory /usr/joe, enter:
apply 'ln %1 /usr/joe' *
parallel ln {} /usr/joe ::: *
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.
Here are the examples from paexec's example catalog with the equivalent using GNU parallel:
../../paexec -s -l -c "`pwd`/1_div_X_cmd" -n +1 <<EOF [...]
parallel echo {} '|' `pwd`/1_div_X_cmd <<EOF [...]
../../paexec -lp -c "`pwd`/all_substr_cmd" -n +3 <<EOF [...]
parallel echo {} '|' `pwd`/all_substr_cmd <<EOF [...]
../../paexec -c "env CC=gcc CFLAGS=-O2 `pwd`/cc_wrapper_cmd" \
-n 'host1 host2' \
-t '/usr/bin/ssh -x' <<EOF [...]
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 [...]
../../paexec -lp -c "`pwd`/toupper_cmd" -n +10 <<EOF [...]
parallel echo {} '|' ./toupper_cmd <<EOF [...]
# Without the wrapper:
parallel echo {} '| awk {print\ toupper\(\$0\)}' <<EOF [...]
map sees it as a feature to have less features and in doing so it also handles corner cases incorrectly. A lot of GNU parallel's code is to handle corner cases correctly on every platform, so you will not get a nasty surprise if a user for example saves a file called: My brother's 12" records.txt
map's example showing how to deal with special characters fails on special characters:
echo "The Cure" > My\ brother\'s\ 12\"\ records
ls | \
map 'echo -n `gzip < "%" | wc -c`; echo -n '*100/'; wc -c < "%"' | bc
It works with GNU parallel:
ls | \
parallel 'echo -n `gzip < {} | wc -c`; echo -n '*100/'; wc -c < {}' | bc
And you can even get the file name prepended:
ls | \
parallel --tag '(echo -n `gzip < {} | wc -c`'*100/'; wc -c < {}) | bc'
map has no support for grouping. So this gives the wrong results without any warnings:
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 > out.par ::: a b c d e f
map -p 4 'grep 1' a b c d e f > out.map-unbuf
map -p 4 'grep --line-buffered 1' a b c d e f > out.map-linebuf
map -p 1 'grep --line-buffered 1' a b c d e f > out.map-serial
ls -l out*
md5sum out*
The documentation shows a workaround, but not only does that mix stdout (standard output) with stderr (standard error) it also fails completely for certain jobs (and may even be considered less readable):
parallel echo -n {} ::: 1 2 3
map -p 4 'echo -n % 2>&1 | sed -e "s/^/$$:/"' 1 2 3 | sort | cut -f2- -d:
maps replacement strings (% %D %B %E) can be simulated in GNU parallel by putting this in ~/.parallel/config:
--rpl '%' --rpl '%D $_=::shell_quote(::dirname($_));' --rpl '%B s:.*/::;s:\.[^/.]+$::;' --rpl '%E s:.*\.::'
map cannot handle bundled options: map -vp 0 echo this fails
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 does not set exit value according to whether one of the jobs failed:
parallel false ::: 1 || echo Job failed map false 1 || echo Never run
map requires Perl v5.10.0 making it harder to use on old systems.
map has no way of using % in the command (GNU Parallel has -I to specify another replacement string than {}).
By design map is option incompatible with xargs, it does not have remote job execution, a structured way of saving results, multiple input sources, progress indicator, configurable record delimiter (only field delimiter), logging of jobs run with possibility to resume, keeping the output in the same order as input, --pipe processing, and dynamically timeouts.
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 $_=::shell_quote($_);chomp($_=qx{readlink -f $_});'
--rpl 'DIRNAME $_=::shell_quote(::dirname($_));chomp($_=qx{readlink -f $_});'
--rpl 'BASENAME s:.*/::;s:\.[^/.]+$::;'
--rpl 'EXT s:.*\.::'
--rpl 'RELDIR $_=::shell_quote($_);chomp(($_,$c)=qx{readlink -f $_;pwd});s:\Q$c/\E::;$_=::dirname($_);'
--rpl 'RELPATH $_=::shell_quote($_);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
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 - not even if jobflow dies unexpectently. If the total output is big (in the order of RAM+swap) it can cause the system to run out of memory.
jobflow gives no error if the command is unknown, and like xargs redirection requires wrapping with bash -c.
jobflow makes it possible to set ressource 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
gargs can run multiple jobs in parallel.
It caches 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.
Output to stderr (standard error) is changed if the command fails.
Here are the two 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: \'{}\'"
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 --linebuffer"
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.
Rust parallel implements a few features from GNU parallel, but lacks many functions. All of these fail:
# -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
# Show what would be executed
parallel --dry-run echo ::: a
# Run different shell dialects
zsh -c 'parallel echo \={} ::: zsh && true'
csh -c 'parallel echo \$\{\} ::: shell && true'
bash -c 'parallel echo \$\({}\) ::: pwd && true'
Rust parallel lacks ::::, --pipe, and has no remote facilities.
Rust parallel buffers in RAM like gargs. This can cause death-by-swapping. See man parallel_design.
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
Because of the way newline is quoted this will not work:
echo 1,2,3 | parallel -vkd, "echo 'a{}b'"
However, these will all work:
echo 1,2,3 | parallel -vkd, echo a{}b
echo 1,2,3 | parallel -vkd, "echo 'a'{}'b'"
echo 1,2,3 | parallel -vkd, "echo 'a'"{}"'b'"
Startup
GNU parallel is slow at starting up - around 250 ms the first time and 150 ms after that.
Job startup
Starting a job on the local machine takes around 10 ms. This can be a big overhead if the job takes very few ms to run. Often you can group small jobs together using -X which will make the overhead less significant. Or you can run multiple GNU parallels as described in EXAMPLE: Speeding up fast jobs.
SSH
When using multiple computers GNU parallel opens ssh connections to them to figure out how many connections can be used reliably simultaneously (Namely SSHD's MaxStartups). This test is done for each host in serial, so if your --sshloginfile contains many hosts it may be slow.
If your jobs are short you may see that there are fewer jobs running on the remove systems than expected. This is due to time spent logging in and out. -M may help here.
Disk access
A single disk can normally read data faster if it reads one file at a time instead of reading a lot of files in parallel, as this will avoid disk seeks. However, newer disk systems with multiple drives can read faster if reading from multiple files in parallel.
If the jobs are of the form read-all-compute-all-write-all, so everything is read before anything is written, it may be faster to force only one disk access at the time:
sem --id diskio cat file | compute | sem --id diskio cat > file
If the jobs are of the form read-compute-write, so writing starts before all reading is done, it may be faster to force only one reader and writer at the time:
sem --id read cat file | compute | sem --id write cat > file
If the jobs are of the form read-compute-read-compute, it may be faster to run more jobs in parallel than the system has CPUs, as some of the jobs will be stuck waiting for disk access.
The current implementation of --nice is too pessimistic in the max allowed command length. It only uses a little more than half of what it could. This affects -X and -m. If this becomes a real problem for you file a bug-report.
If you get:
Can't exec "command": No such file or directory
or:
open3: exec of by command failed
it may be because command is not known, but it could also be because command is an alias or a function. If it is a function you need to export -f the function first. An alias will only work if you use env_parallel.
Report bugs to <bug-parallel@gnu.org> or https://savannah.gnu.org/bugs/?func=additem&group=parallel
See a perfect bug report on https://lists.gnu.org/archive/html/bug-parallel/2015-01/msg00000.html
Your bug report should always include:
It should be a complete example that others can run that shows the problem including all files needed to run the example. This should preferably be small and simple, so try to remove as many options as possible. A combination of yes, seq, cat, echo, and sleep can reproduce most errors. If your example requires large files, see if you can make them by something like seq 1000000 > file or yes | head -n 10000000 > file.
If your example requires remote execution, see if you can use localhost - maybe using another login.
If you suspect the error is dependent on your environment or distribution, please see if you can reproduce the error on one of these VirtualBox images: http://sourceforge.net/projects/virtualboximage/files/ http://www.osboxes.org/virtualbox-images/
Specifying the name of your distribution is not enough as you may have installed software that is not in the VirtualBox images.
If you cannot reproduce the error on any of the VirtualBox images above, see if you can build a VirtualBox image on which you can reproduce the error. If not you should assume the debugging will be done through you. That will put more burden on you and it is extra important you give any information that help. In general the problem will be fixed faster and with less work for you if you can reproduce the error on a VirtualBox.
When using GNU parallel for a publication please cite:
O. Tange (2011): GNU Parallel - The Command-Line Power Tool, ;login: The USENIX Magazine, February 2011:42-47.
This helps funding further development; and it won't cost you a cent. If you pay 10000 EUR you should feel free to use GNU Parallel without citing.
Copyright (C) 2007-10-18 Ole Tange, http://ole.tange.dk
Copyright (C) 2008,2009,2010 Ole Tange, http://ole.tange.dk
Copyright (C) 2010,2011,2012,2013,2014,2015,2016 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.
Copyright (C) 2007,2008,2009,2010,2011,2012,2013,2014,2015,2016 Free Software Foundation, Inc.
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 <http://www.gnu.org/licenses/>.
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 fdl.txt.
You are free:
Under the following conditions:
With the understanding that:
A copy of the full license is included in the file as cc-by-sa.txt.
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.
ssh(1), ssh-agent(1), sshpass(1), ssh-copy-id(1), rsync(1), find(1), xargs(1), dirname(1), make(1), pexec(1), ppss(1), xjobs(1), prll(1), dxargs(1), mdm(1)
| 2018-12-01 | 20161222 |