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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.

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:

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Apache License 2.0
Created May 2, 2017
Updated February 28, 2020
stephanie-wang/arrow | GitHunt