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apache / arrow / bafb2d86c4c6f67d894a043648c00914ba42e904
commitbafb2d86c4c6f67d894a043648c00914ba42e904[log] [tgz]
authorRaúl Cumplido <raulcumplido@gmail.com>Fri Jul 12 21:30:53 2024 +0200
committerGitHub <noreply@github.com>Sat Jul 13 04:30:53 2024 +0900
treeb3f6f1fb75103f151c0de296c29e1b985a43dae0
parent63cef36fa9125cd0305e4004bf375c8e6c302245 [diff]
GH-43232: [Release][Packaging][Python] Add tzdata as conda env requirement to avoid ORC failure (#43233)

### Rationale for this change

Binary verifications for wheels on conda are failing on ORC test due to missing tzdata

### What changes are included in this PR?

Adding tzdata as conda requirement when setting up the environment on the verification script

### Are these changes tested?

Those changes have been tested locally

### Are there any user-facing changes?
No
* GitHub Issue: #43232

Authored-by: Raúl Cumplido <raulcumplido@gmail.com>
Signed-off-by: Sutou Kouhei <kou@clear-code.com>
1 file changed
tree: b3f6f1fb75103f151c0de296c29e1b985a43dae0
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  5. csharp/
  6. dev/
  7. docs/
  8. format/
  9. go/
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  32. appveyor.yml
  33. CHANGELOG.md
  34. cmake-format.py
  35. CODE_OF_CONDUCT.md
  36. CONTRIBUTING.md
  37. docker-compose.yml
  38. header
  39. LICENSE.txt
  40. NOTICE.txt
  41. README.md
README.md

Apache Arrow

Fuzzing Status License Twitter Follow

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 many 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
  • Readers and writers for various widely-used file formats (such as Parquet, CSV)

Implementation status

The official Arrow libraries in this repository are in different stages of implementing the Arrow format and related features. See our current feature matrix on git main.

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: