| tag | d8124ce244d31d4b156d9a7d518a48a581f8c266 | |
|---|---|---|
| tagger | Owen O'Malley <omalley@apache.org> | Mon Jan 25 16:31:58 2016 -0800 |
| object | 704d97ec1ccef28e18cde5280ea8cfd3c0295621 |
ORC 1.0.0 release
| commit | 704d97ec1ccef28e18cde5280ea8cfd3c0295621 | [log] [tgz] |
|---|---|---|
| author | Owen O'Malley <omalley@apache.org> | Thu Jan 21 00:27:43 2016 -0800 |
| committer | Owen O'Malley <omalley@apache.org> | Fri Jan 22 16:13:50 2016 -0800 |
| tree | 5c3e11427f3ccfb008cd949a810569b8ba1ec965 | |
| parent | eaadb0c6ef7da37bbec7ec33a2690bb7b1c8b8c0 [diff] |
ORC-39. Create docker scripts for building and testing in various Linux distributions. (omalley reviewed by asandryh) Signed-off-by: Owen O'Malley <omalley@apache.org> Fixes apache/orc#17
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 library allows C++ programs to read and write the Optimized Row Columnar (ORC) file format.
-To compile: % export TZ=America/Los_Angeles % mkdir build % cd build % cmake .. % make % make test-out