Group: Apache ORC

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1. ORC Core129 usages

org.apache.orc » orc-coreApache

The core reader and writer for ORC files. Uses the vectorized column batch for the in memory representation.
Last Release on Nov 10, 2023

2. ORC MapReduce29 usages

org.apache.orc » orc-mapreduceApache

An implementation of Hadoop's mapred and mapreduce input and output formats for ORC files. They use the core reader and writer, but present the data to the user in Writable objects.
Last Release on Nov 10, 2023

3. ORC Shims8 usages

org.apache.orc » orc-shimsApache

A shim layer for supporting various versions of Hadoop dynamically. This module uses a higher version of Hadoop so that we can create shims that let us use new features of Hadoop without having a hard dependency on the latest version.
Last Release on Nov 10, 2023

4. ORC Tools5 usages

org.apache.orc » orc-toolsApache

ORC Tools
Last Release on Nov 10, 2023

5. Apache ORC1 usages

org.apache.orc » orcApache

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.
Last Release on Nov 10, 2023

6. ORC Examples

org.apache.orc » orc-examplesApache

ORC Examples
Last Release on Nov 10, 2023

7. ORC Benchmarks

org.apache.orc » orc-benchmarksApache

Benchmarks for comparing ORC, Parquet, and Avro performance.
Last Release on Jan 23, 2018

8. Apache ORC Format

org.apache.orc » orc-formatApache

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.
Last Release on Jan 6, 2024