How to Install and Uninstall liborc1.x86_64 Package on AlmaLinux 9
Last updated: November 25,2024
1. Install "liborc1.x86_64" package
In this section, we are going to explain the necessary steps to install liborc1.x86_64 on AlmaLinux 9
$
sudo dnf update
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$
sudo dnf install
liborc1.x86_64
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2. Uninstall "liborc1.x86_64" package
Please follow the guidance below to uninstall liborc1.x86_64 on AlmaLinux 9:
$
sudo dnf remove
liborc1.x86_64
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$
sudo dnf autoremove
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3. Information about the liborc1.x86_64 package on AlmaLinux 9
Last metadata expiration check: 0:31:39 ago on Wed Mar 13 07:41:12 2024.
Available Packages
Name : liborc1
Version : 1.8.6
Release : 1.el9
Architecture : x86_64
Size : 413 k
Source : liborc-1.8.6-1.el9.src.rpm
Repository : epel
Summary : Library for producing small, fast columnar storage for Hadoop workloads
URL : http://orc.apache.org/
License : Apache-2.0
Description : ORC is a self-describing type-aware columnar file format designed
: for Hadoop workloads. It is optimized for large streaming reads,
: but with integrated support for finding required rows quickly.
: Storing data in a columnar format lets the reader read, decompress,
: and process only the values that are required for the current query.
: Because ORC files are type-aware, the writer chooses the most
: appropriate encoding for the type and builds an internal index as
: the file is written. Predicate pushdown uses those indexes to
: determine which stripes in a file need to be read for a particular
: query and the row indexes can narrow the search to a particular set
: of 10,000 rows. ORC supports the complete set of types in Hive,
: including the complex types: structs, lists, maps, and unions.
Available Packages
Name : liborc1
Version : 1.8.6
Release : 1.el9
Architecture : x86_64
Size : 413 k
Source : liborc-1.8.6-1.el9.src.rpm
Repository : epel
Summary : Library for producing small, fast columnar storage for Hadoop workloads
URL : http://orc.apache.org/
License : Apache-2.0
Description : ORC is a self-describing type-aware columnar file format designed
: for Hadoop workloads. It is optimized for large streaming reads,
: but with integrated support for finding required rows quickly.
: Storing data in a columnar format lets the reader read, decompress,
: and process only the values that are required for the current query.
: Because ORC files are type-aware, the writer chooses the most
: appropriate encoding for the type and builds an internal index as
: the file is written. Predicate pushdown uses those indexes to
: determine which stripes in a file need to be read for a particular
: query and the row indexes can narrow the search to a particular set
: of 10,000 rows. ORC supports the complete set of types in Hive,
: including the complex types: structs, lists, maps, and unions.