newsGNU Parallel - News: GNU Parallel 20140722 ('MH17') released

 
 
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GNU Parallel 20140722 ('MH17') released

Item posted by Ole Tange <tange> on Tue 22 Jul 2014 04:53:00 AM UTC.

GNU Parallel 20140722 ('MH17') has been released. It is available for download at: http://ftp.gnu.org/gnu/parallel/

This release contains a major change in central parts of the code and should be considered beta quality. As always it passes the testsuite, so most functionality clearly works.

Thanks to Malcolm Cook for the brilliant idea to use a general perl expression as a replacement string.

Haiku of the month:

  Are you tired of
  inflexible replacements?
  Use Perl expressions.
         -- Ole Tange

New in this release:

  • {= perl expression =} can be used as replacement string. The expression should modify $_. E.g. {= s/\.gz$// =} to remove .gz from the string. This makes replacement strings extremely flexible.


  • Positional perl expressions (similar to {2}) are given as {=2 perl expression=} where 2 is the position.


  • One small backwards incompatability: {1}_{2} will replace {2} with the empty string if there is only one argument. Previously {2} would have been left untouched.


  • Replacement strings can be defined using --rpl. E.g. parallel --rpl '{.gz} s/\.gz$//' echo {.gz} ::: *.gz


  • The parenthesis around {= perl expression =} can be changed with --parens.


  • --tmux will direct the output to a tmux session instead of files. Each running jobs will be in its own window.


  • --halt 10% will stop spawning new jobs if 10% failed so far.














  • 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.


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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