newsGNU Parallel - News: GNU Parallel 20150322 ('Hellwig') released

 
 
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GNU Parallel 20150322 ('Hellwig') released

Item posted by Ole Tange <tange> on Sun 22 Mar 2015 01:31:38 AM UTC.

GNU Parallel 20150322 ('Hellwig') has been released. It is available for download at: http://ftp.gnu.org/gnu/parallel/

Haiku of the month:

  Stand up for your rights.
  VMware does not comply.
  Hellwig goes to court.

  (https://sfconservancy.org/linux-compliance/vmware-lawsuit-faq.html)

New in this release:

  • --number-of-cores respects 'taskset' on GNU/Linux.


  • --joblog --pipe gives the data send and received in the log.


  • GNU Parallel was tested to support 100 GB sized records in --pipe. A few bugs was fixed to support >2 GB records. It works, but is rather slow.









  • GNU Parallel was cited in: Efficient Retrieval of Key Material for Inspecting Potentially Malicious Traffic in the Cloud http://sacko.uk/pdf/2015.1.pdf


















  • Bug fixes and man page updates.


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 is 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.

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 || curl pi.dk/3/) | bash

Watch the intro video on http://www.youtube.com/playlist?list=PL284C9FF2488BC6D1

Walk through the tutorial (man parallel_tutorial). Your commandline will love you for it.

When using programs that use GNU Parallel to process data for publication please cite:

O. Tange (2011): GNU Parallel - The Command-Line Power Tool, ;login: The USENIX Magazine, February 2011:42-47.

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://www.gnu.org/s/parallel/merchandise.html
  • 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 GNU Parallel for research:

  • Please cite GNU Parallel in you publications (use --bibtex)


If GNU Parallel saves you money:



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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