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.
This project includes both a Java library for reading and writing and a C++ library for reading the Optimized Row Columnar (ORC) file format. The C++ and Java libraries are completely independent of each other and will each read all versions of ORC files.
The current build status:
To build a release version with debug information:
% mkdir build % cd build % cmake .. % make package % make test-out
To build a debug version:
% mkdir build % cd build % cmake .. -DCMAKE_BUILD_TYPE=DEBUG % make package % make test-out
To build a release version without debug information:
% mkdir build % cd build % cmake .. -DCMAKE_BUILD_TYPE=RELEASE % make package % make test-out
To build only the Java library:
% cd java % mvn package
To build only the C++ library:
% mkdir build % cd build % cmake .. -DBUILD_JAVA=OFF % make package % make test-out