apache/arrow - Open Source PR Review Scorecard

Apache Arrow is the universal columnar format and multi-language toolbox for fast data interchange and in-memory analytics

C-Rank Grade: A (Welcoming) - 59/100

External PR Merge Rate: 57%

Response Time: 20h

First Timer Success: 42%

Frequently Asked Questions

Is apache/arrow welcoming to first-time open-source contributors?

apache/arrow has a recorded first-timer success rate of 42.4%. Repositories ranked A typically provide actionable feedback during code reviews and actively nurture new community contributors.

How fast can I expect code review feedback on my pull request?

Maintainers in apache/arrow respond to incoming external pull requests in approximately 19.8 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 59.0 C-Rank™ score (A Tier) represent?

The C-Rank™ system evaluates GitHub projects on a 0–100 scale using real data: PR merge rates, review turnaround time, active maintainer presence, and first-time contributor success. A score of 59.0 places apache/arrow in the A tier.

What is the external contributor pull request merge rate for apache/arrow?

The external contributor pull request merge rate for apache/arrow is 57.3%, based on public PR activity from non-core contributors.

Are there Good First Issues available in apache/arrow?

apache/arrow currently has 4 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".

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Apache Arrow is the universal columnar format and multi-language toolbox for fast data interchange and in-memory analytics

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AI Maintainer Review Guidelines

Review Persona

Strict Quality Architect

Warmth Score
7.2/10
Patience Score
7.7/10
Nitpick Rate
35%

Balanced & professional review environment in apache/arrow. Maintains strict focus on technical quality and test standards.

Top PR Submission Do's

  • •Add unit tests with >80% coverage for modified code paths
  • •Run repository linter and code formatters locally before pushing
  • •Link relevant GitHub issue ID in PR description pre-flight checklist

Top PR Friction Pitfalls (Don'ts)

  • •Do not submit unlinked PRs without referencing an existing issue
  • •Do not mix refactoring and feature logic into a single commit
  • •Do not ping maintainers repeatedly within 24 hours of opening
Response Velocity
19 hours
Standard maintainer review cycle

Average Response Latency

Tracks hours until a maintainer leaves a review, comment, or PR response.

Merge Efficiency
57.3%
Moderate PR acceptance rate

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
42.4%
Accepts new contributor PRs

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
145 core
Highly collaborative maintainer core
Diagnostic Health HUD
57.3%
Merge Gauge
42.4%
1st-Timer
Community Vibe51/100

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Active Good First Issues (5)

View on GitHub

Describe the bug The R bindings do not expose page_checksum_verification, so an R user has no way to turn on page-CRC verification when reading Parquet. Arrow's own deliberately-corrupt test files are read without error. C++ has the option and Python exposes it; only R does not. C++ cpp/src/parquet/properties.h:148-150 — page_checksum_verification() / set_page_checksum_verification(bool check_crc), defaulting to false at line 166 Python python/pyarrow/parquet/core.py:269,325,346 — a documented page_checksum_verification=False parameter R r/R/parquet.R:656-682 — ParquetReaderProperties declares and implements only thrift_string_size_limit and thrift_container_size_limit Reproduction Using the files parquet-testing ships expressly so readers can be shown to reject a bad CRC — datapage_v1-corrupt-checksum.parquet ("uncompressed INT32 columns in v1 data pages with a mismatching CRC") and rle-dict-uncompressed-corrupt-checksum.parquet: library(arrow) packageVersion("

📅 Opened Oct 10, 2026💬 2 comments
Quality: 80/100Contribute

Describe the enhancement requested Arrow C++ 26.0.0 adds two new arrow::csv::ParseOptions fields: ignore_extra_columns (#51118): rows with more columns than expected have the extra columns dropped instead of erroring. pad_short_rows (#50926): rows with fewer columns than expected are padded with nulls instead of erroring. Neither can be set from R. csv_parse_options() and CsvParseOptions$create() should accept both, and csv.cpp should pass them through: arrow/r/R/csv.R Lines 735 to 753 in 9479e68 quote_char = '"', double_quote = TRUE, escaping = FALSE, escape_char = "\\", newlines_in_values = FALSE, ignore_empty_lines = TRUE ) {

📅 Opened Sep 30, 2026💬 1 comment
Quality: 80/100Contribute

Describe the enhancement requested In the Python Parquet reader docstrings, many snippets are duplicated for describing various common options, such as thrift_string_size_limit. We should deduplicate these snippets and find a way to reuse them across all Parquet reader docstrings. This will ease maintenance and reduce the risk of errors when updating those docstrings. Component(s) Parquet, Python

📅 Opened Sep 9, 2026💬 3 comments
Quality: 80/100Contribute

Describe the enhancement requested In visit_type_inline.h we have a VisitType that dispatches all existing data types to a generic callable (presumably a lambda or template function). It would be useful to have a similar VisitIntegerType helper that assumes its input is an integer type. This would help implementing helpers for dictionary indices, take indices, etc. For example this snippet could be reimplemented more tersely using said helper: arrow/cpp/src/arrow/util/dict_util.cc Lines 61 to 79 in 154962c const auto& dict_array_type = internal::checked_cast<const DictionaryType&>(*span.type); switch (dict_array_type.index_type()->id()) { case Type::UINT8: return LogicalNullCount<UInt8Type>(span); case Type::INT8:

📅 Opened Jul 22, 2026💬 6 comments
Quality: 70/100Contribute

Describe the bug, including details regarding any error messages, version, and platform. The r-devdocs crossbow job consistently fails during the period between when the main Apache Arrow release completes (and C++ packages are published to apt) and when the R package is released to CRAN. Example failure from 23.0.1: https://github.com/ursacomputing/crossbow/actions/runs/22147872099/job/64030288380 The error is an ABI mismatch: Error: package or namespace load failed for 'arrow' in dyn.load(file, DLLpath = DLLpath, ...): unable to load shared object '/home/runner/work/_temp/Library/arrow/libs/arrow.so': /home/runner/work/crossbow/crossbow/dist/lib/libarrow_compute.so.2300: undefined symbol: _ZN5arrow6Status14AddContextLineEPKciS2_ Root cause The r/vignettes/developers/setup.Rmd file contains a hidden test section (lines 342-351) that: Builds Arrow C++ from source (from the git checkout) Installs the R package linked against this custom-built libarrow Installs system libarrow-dev f

📅 Opened Feb 24, 2026💬 3 comments
Quality: 60/100Contribute
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Contributor Compatibility & Review Speed Analysis for apache/arrow

When evaluating whether to contribute to apache/arrow, response velocity and maintainer engagement are crucial. GetMerged continuously tracks pull request trajectories, first-comment latency, and code review rounds to help developers avoid submitting pull requests to backlogged repositories.

Currently, maintainers of apache/arrow acknowledge new external contributions in approximately 19 hours. Out of all submitted pull requests from non-core authors in the last 180-day window, 57.3% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to apache/arrow

01

Is apache/arrow welcoming to first-time open-source contributors?

apache/arrow has a recorded first-timer success rate of 42.4%. Repositories ranked Welcoming typically provide actionable feedback during code reviews and actively nurture new community contributors.

02

How fast can I expect code review feedback on my pull request?

The initial maintainer response time averages ~19 hours. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 59.0 C-Rank™ score represent?

The C-Rank™ index scores repositories on a 0 to 100 scale using an objective formula: external PR merge rates, initial response speed, active maintainer count, and first-time contributor retention. A score of 59.0 places apache/arrow in the Welcoming tier.

04

What is the external contributor pull request merge rate for apache/arrow?

The external pull request merge rate is 57.3%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.

05

Are there beginner Good First Issues open in apache/arrow?

Yes, apache/arrow currently has 4 active issue(s) tagged with beginner-friendly labels. You can inspect these directly from the repository issues tab.

GetMerged C-Rank™ Indexing Standard

All metrics displayed for apache/arrow are automatically retrieved via the public GitHub API and recalculated daily. Insider pull requests submitted by repository owners or organization members are excluded from merge rate calculations to preserve objective external contributor statistics.