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apache / arrow / 5bdb3afaccb60a3d41fff977c4dedf3f520ac533
commit5bdb3afaccb60a3d41fff977c4dedf3f520ac533[log] [tgz]
authorNeal Richardson <neal.p.richardson@gmail.com>Wed Apr 01 16:30:16 2020 -0700
committerNeal Richardson <neal.p.richardson@gmail.com>Wed Apr 01 16:30:16 2020 -0700
treec8e4597ac55afc2d4f6660c4a897c20b067f0887
parente381a72703c1565fa186cd21629bc77c2395035e [diff]
ARROW-7641: [R] Make dataset vignette have executable code:

This patch makes the dataset vignette executable, yet it also leaves in the expected output and conditionally shows it if the taxi data is not found locally. That way, the rendered vignette always looks useful.

In addition, the dataset print method is improved to report the number and format of the files it contains.

Closes #6247 from hadley/vignette-eval

Lead-authored-by: Neal Richardson <neal.p.richardson@gmail.com>
Co-authored-by: Hadley Wickham <h.wickham@gmail.com>
Signed-off-by: Neal Richardson <neal.p.richardson@gmail.com>
6 files changed
tree: c8e4597ac55afc2d4f6660c4a897c20b067f0887
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  31. CHANGELOG.md
  32. cmake-format.py
  33. CODE_OF_CONDUCT.md
  34. CONTRIBUTING.md
  35. docker-compose.yml
  36. header
  37. LICENSE.txt
  38. Makefile.docker
  39. NOTICE.txt
  40. README.md
  41. run-cmake-format.py
README.md

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: