How to Install and Uninstall perl-Parallel-Iterator.noarch Package on Rocky Linux 9
Last updated: January 11,2025
1. Install "perl-Parallel-Iterator.noarch" package
Please follow the step by step instructions below to install perl-Parallel-Iterator.noarch on Rocky Linux 9
$
sudo dnf update
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$
sudo dnf install
perl-Parallel-Iterator.noarch
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2. Uninstall "perl-Parallel-Iterator.noarch" package
This guide covers the steps necessary to uninstall perl-Parallel-Iterator.noarch on Rocky Linux 9:
$
sudo dnf remove
perl-Parallel-Iterator.noarch
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$
sudo dnf autoremove
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3. Information about the perl-Parallel-Iterator.noarch package on Rocky Linux 9
Last metadata expiration check: 2:06:58 ago on Fri Feb 16 06:49:52 2024.
Available Packages
Name : perl-Parallel-Iterator
Version : 1.00
Release : 30.el9
Architecture : noarch
Size : 24 k
Source : perl-Parallel-Iterator-1.00-30.el9.src.rpm
Repository : epel
Summary : Simple parallel execution
URL : https://metacpan.org/release/Parallel-Iterator
License : GPL+ or Artistic
Description : The map function applies a user supplied transformation function to
: each element in a list, returning a new list containing the
: transformed elements.
:
: This module provides a 'parallel map'. Multiple worker processes are forked so
: that many instances of the transformation function may be executed
: simultaneously.
:
: For time consuming operations, particularly operations that spend most of their
: time waiting for I/O, this is a big performance win. It also provides a simple
: idiom to make effective use of multi CPU systems.
Available Packages
Name : perl-Parallel-Iterator
Version : 1.00
Release : 30.el9
Architecture : noarch
Size : 24 k
Source : perl-Parallel-Iterator-1.00-30.el9.src.rpm
Repository : epel
Summary : Simple parallel execution
URL : https://metacpan.org/release/Parallel-Iterator
License : GPL+ or Artistic
Description : The map function applies a user supplied transformation function to
: each element in a list, returning a new list containing the
: transformed elements.
:
: This module provides a 'parallel map'. Multiple worker processes are forked so
: that many instances of the transformation function may be executed
: simultaneously.
:
: For time consuming operations, particularly operations that spend most of their
: time waiting for I/O, this is a big performance win. It also provides a simple
: idiom to make effective use of multi CPU systems.