Summary: Library for producing small, fast columnar storage for Hadoop workloads
Name: liborc
Version: 2.1.2
Release: 2
License: Apache-2.0
URL: http://orc.apache.org/
Source: https://downloads.apache.org/orc/orc-%{version}/orc-%{version}.tar.gz
Source1: https://downloads.apache.org/orc/orc-format-1.1.0/orc-format-1.1.0.tar.gz
Patch0001: 0001-cmake.patch
Patch0002: 0002-c++-src-CpuInfoUtil.cc.patch
Patch0003: fix-timestampColVector-notset-utc-flag.patch
# Apache ORC has numerous compile errors and apparently assumes a 64-bit
# build and runtime environment. The only consumer of this package is
# Ceph (by way of Apache Arrow) which is also 64-bit only
ExcludeArch: i686 armv7hl
BuildRequires: gnupg2
BuildRequires: cmake
BuildRequires: gcc-c++
BuildRequires: protobuf-devel
BuildRequires: protobuf-lite-devel
BuildRequires: zlib-devel
BuildRequires: libzstd-devel
BuildRequires: lz4-devel
BuildRequires: snappy-devel
%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.
%package -n %{name}2
Summary: Library for producing small, fast columnar storage for Hadoop workloads
Provides: %{name}%{?_isa} = %{version}-%{release}
Obsoletes: %{name}1 < %{version}-%{release}
%description -n %{name}2
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.
%package devel
Summary: Header files, libraries and development documentation for %{name}
Requires: %{name}2 = %{version}-%{release}
%description devel
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.
Contains header files for developing applications that use the %{name}
library.
%prep
%autosetup -p1 -n orc-%{version}
sed -i 's#homedir#%{getenv:HOME}#g' ./cmake_modules/ThirdpartyToolchain.cmake
%build
echo "RPM_OPT_FLAGS: $RPM_OPT_FLAGS"
# https://src.fedoraproject.org/rpms/protobuf/pull-request/26#comment-183002
export CXXFLAGS="$RPM_OPT_FLAGS -Wno-error=stringop-overflow"
%cmake \
-DOVERRIDE_INSTALL_PREFIX=/usr \
-DCMAKE_COLOR_MAKEFILE:BOOL=OFF \
-DCMAKE_INSTALL_LIBDIR:PATH=%{_libdir} \
-DINSTALL_LIBDIR:PATH=%{_libdir} \
-DBUILD_SHARED_LIBS:BOOL=on \
-DBUILD_LIBHDFSPP:BOOL=off \
-DSNAPPY_HOME="$(pkg-config --variable=prefix snappy)" \
-DLZ4_HOME="$(pkg-config --variable=prefix liblz4)" \
-DZLIB_HOME="$(pkg-config --variable=prefix zlib)" \
-DZSTD_HOME="$(pkg-config --variable=prefix libzstd)" \
-DGTEST_HOME="$(pkg-config --variable=prefix gtest)" \
-DPROTOBUF_HOME="$(pkg-config --variable=prefix protobuf)" \
-Dorc_VERSION="%{version}" \
-DBUILD_CPP_TESTS=off \
-DBUILD_TOOLS=off \
-DBUILD_JAVA=off \
-DANALYZE_JAVA=off \
"-GUnix Makefiles"
%cmake_build
%check
%install
%cmake_install
mkdir %{buildroot}%{_docdir}/%{name}2
mv %{buildroot}%{_docdir}/orc/NOTICE %{buildroot}%{_docdir}/%{name}2/
mkdir -p %{buildroot}/%{_defaultlicensedir}/%{name}2
mv %{buildroot}%{_docdir}/orc/LICENSE %{buildroot}/%{_defaultlicensedir}/%{name}2/
rm -f %{buildroot}/%{_includedir}/orc/._*.hh
rm -f %{buildroot}/%{_includedir}/orc/sargs/._*.hh
%ldconfig_scriptlets
%files -n %{name}2
%license LICENSE
%doc README.md NOTICE
%{_libdir}/liborc.so.*
%{_libdir}/cmake/orc/orcConfig*
%exclude %{_libdir}/cmake/orc/*
%exclude %{_libdir}/orcTargets*
%files devel
%dir %{_includedir}/orc
%{_includedir}/orc/*.hh
%dir %{_includedir}/orc/sargs
%{_includedir}/orc/sargs/*.hh
%{_libdir}/liborc.so
%changelog
* Mon Nov 10 2025 shaojiansong <shaojiansong@kylonos.cn> - 2.1.2-2
- Init package
* Wed May 28 2025 Dongxing Wang <dongxing.wang_a@thundersoft.com> - 2.1.2-1
- Init package