Apache Arrow is a columnar in-memory analytics layer designed to accelerate big data. It houses a set of canonical in-memory representations of flat and hierarchical data along with multiple language-bindings for structure manipulation. It also provides IPC and common algorithm implementations.

Clone this repo:
  1. 1a1bfd3 ARROW-7351: [Developer] Only suggest cpp-* versions by default for PARQUET issues in merge tool by Wes McKinney · 66 minutes ago master
  2. eb752ef ARROW-7355: [CI] Environment variables are defined twice for the fuzzit builds by Krisztián Szűcs · 90 minutes ago
  3. e65c2fa ARROW-7353: [C++] Ignore -Wmissing-braces when building with clang by Wes McKinney · 2 hours ago
  4. be2dcb2 ARROW-7354: [C++] Fix crash in test-io-hdfs by Antoine Pitrou · 2 hours ago
  5. fcefd3d PARQUET-1712: [C++] Stop using deprecated APIs in examples by Kenta Murata · 3 hours ago

Apache Arrow

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Powering In-Memory Analytics

Apache Arrow is a development platform for in-memory analytics. It contains a set of technologies that enable big data systems to process and move data fast.

Major components of the project include:

Arrow is an Apache Software Foundation project. Learn more at arrow.apache.org.

What's in the Arrow libraries?

The reference Arrow libraries contain a number of distinct software components:

  • Columnar vector and table-like containers (similar to data frames) supporting flat or nested types
  • Fast, language agnostic metadata messaging layer (using Google's Flatbuffers library)
  • Reference-counted off-heap buffer memory management, for zero-copy memory sharing and handling memory-mapped files
  • IO interfaces to local and remote filesystems
  • Self-describing binary wire formats (streaming and batch/file-like) for remote procedure calls (RPC) and interprocess communication (IPC)
  • Integration tests for verifying binary compatibility between the implementations (e.g. sending data from Java to C++)
  • Conversions to and from other in-memory data structures

How to Contribute

Please read our latest project contribution guide.

Getting involved

Even if you do not plan to contribute to Apache Arrow itself or Arrow integrations in other projects, we'd be happy to have you involved: