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| From: | Saint Michael |
| Subject: | Re: GNU Parallel 20191022 ('Driving IT') released [stable] |
| Date: | Wed, 20 Nov 2019 22:18:39 -0500 |
GNU Parallel 20191022 ('Driving IT') [stable] has been released. It is
available for download at: http://ftpmirror.gnu.org/parallel/
No new functionality was introduced so this is a good candidate for a
stable release.
GNU Parallel is 10 years old next year on 2020-04-22. You are here by
invited to a reception on Friday 2020-04-17.
See https://www.gnu.org/software/parallel/10-years-anniversary.html
Quote of the month:
I've said it before: The command line program GNU Parallel is a godsend.
-- Jo Chr. Oterhals @oterhals@twitter
New in this release:
* --tee will use --output-error=warn-nopipe if supported by tee.
* GNU Parallel will be presented at Driving IT 2019:
https://ida.dk/arrangementer-og-kurser/konferencer/driving-it/tools
* UMN Duluth: Job parallelization with task arrays and GNU parallel
https://www.msi.umn.edu/tutorials/umn-duluth-job-parallelization-task-arrays-and-gnu-parallel
* Genome updater uses GNU Parallel https://github.com/pirovc/genome_updater
* Using GNU-Parallel for bioinformatics
https://www.danielecook.com/using-gnu-parallel-for-bioinformatics/
* Speeding up PostgreSQL ETL pipeline with the help of GODS
https://cfengine.com/company/blog-detail/speeding-up-postgresql-etl-pipeline-with-the-help-of-gods/
* Runing linux commands in parallel
https://dev.to/voyeg3r/runing-linux-commands-in-parallel-4ff8
* Research Computing University of Colorado Boulder contains an intro
to GNU Parallel
https://readthedocs.org/projects/curc/downloads/pdf/latest/
* 如何使用Parallel在Shell中并行执行命令https://www.myfreax.com/gnu-parallel/
* 如何测试 Amazon Elastic File System
https://aws.amazon.com/cn/blogs/china/how-to-test-drive-amazon-elastic-file-system/
* Bug fixes and man page updates.
Get the book: GNU Parallel 2018
http://www.lulu.com/shop/ole-tange/gnu-parallel-2018/paperback/product-23558902.html
GNU Parallel - For people who live life in the parallel lane.
= About GNU Parallel =
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 and pipe it into
commands 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 can even replace nested loops.
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 example you can run this to convert all jpeg files into png and
gif files and have a progress bar:
parallel --bar convert {1} {1.}.{2} ::: *.jpg ::: png gif
Or you can generate big, medium, and small thumbnails of all jpeg
files in sub dirs:
find . -name '*.jpg' |
parallel convert -geometry {2} {1} {1//}/thumb{2}_{1/} :::: - ::: 50 100 200
You can find more about GNU Parallel at: http://www.gnu.org/s/parallel/
You can install GNU Parallel in just 10 seconds with:
$ (wget -O - pi.dk/3 || lynx -source pi.dk/3 || curl pi.dk/3/ || \
fetch -o - http://pi.dk/3 ) > install.sh
$ sha1sum install.sh | grep 3374ec53bacb199b245af2dda86df6c9
12345678 3374ec53 bacb199b 245af2dd a86df6c9
$ md5sum install.sh | grep 029a9ac06e8b5bc6052eac57b2c3c9ca
029a9ac0 6e8b5bc6 052eac57 b2c3c9ca
$ sha512sum install.sh | grep f517006d9897747bed8a4694b1acba1b
40f53af6 9e20dae5 713ba06c f517006d 9897747b ed8a4694 b1acba1b 1464beb4
60055629 3f2356f3 3e9c4e3c 76e3f3af a9db4b32 bd33322b 975696fc e6b23cfb
$ bash install.sh
Watch the intro video on http://www.youtube.com/playlist?list=PL284C9FF2488BC6D1
Walk through the tutorial (man parallel_tutorial). Your command line
will love you for it.
When using programs that use GNU Parallel to process data for
publication please cite:
O. Tange (2018): GNU Parallel 2018, March 2018,
https://doi.org/10.5281/zenodo.1146014.
If you like GNU Parallel:
* Give a demo at your local user group/team/colleagues
* Post the intro videos on Reddit/Diaspora*/forums/blogs/
Identi.ca/Google+/Twitter/Facebook/Linkedin/mailing lists
* Get the merchandise https://gnuparallel.threadless.com/designs/gnu-parallel
* Request or write a review for your favourite blog or magazine
* Request or build a package for your favourite distribution (if it is
not already there)
* Invite me for your next conference
If you use programs that use GNU Parallel for research:
* Please cite GNU Parallel in you publications (use --citation)
If GNU Parallel saves you money:
* (Have your company) donate to FSF https://my.fsf.org/donate/
= About GNU SQL =
GNU sql aims to give a simple, unified interface for accessing
databases through all the different databases' command line clients.
So far the focus has been on giving a common way to specify login
information (protocol, username, password, hostname, and port number),
size (database and table size), and running queries.
The database is addressed using a DBURL. If commands are left out you
will get that database's interactive shell.
When using GNU SQL for a publication please cite:
O. Tange (2011): GNU SQL - A Command Line Tool for Accessing Different
Databases Using DBURLs, ;login: The USENIX Magazine, April 2011:29-32.
= About GNU Niceload =
GNU niceload slows down a program when the computer load average (or
other system activity) is above a certain limit. When the limit is
reached the program will be suspended for some time. If the limit is a
soft limit the program will be allowed to run for short amounts of
time before being suspended again. If the limit is a hard limit the
program will only be allowed to run when the system is below the
limit.
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