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pr_review

Review Apache DataFusion pull requests using the project's review guide. Gather the proposed changes, discussion, and automated check results, or apply the same review criteria to your own changes before submitting a pull request.

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Review Apache DataFusion pull requests following the project's PR review guide. Use whenever asked to review a DataFusion PR or PR URL, and whenever creating a PR, to check the changes against the same criteria before submitting.

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适用场景

  • Reviewing an Apache DataFusion pull request
  • Checking your changes before submitting a pull request
  • Reviewing changes alongside discussion and automated check results

包含的文件(1)

  • SKILL.md1.2 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

DataFusion PR Review

This skill describes the mechanics for doing PR reviews from the command line.

When creating a PR, skip the "Collect PR context" step and instead check the changes against each area of the PR review guide before submitting.

Collect PR context

  • Check out the PR locally: gh pr checkout <PR number> (ask first if the working tree has other work in progress).
  • Fetch the PR description, comments, and reviews: gh pr view <PR number> --json title,body,comments,reviews
  • Fetch CI status: gh pr checks <PR number>.

Compute the diff

# find the remote that points at apache/datafusion (e.g. `apache`, `upstream`, or `origin`)
UPSTREAM=$(git remote -v | grep -m1 'apache/datafusion' | cut -f1)
git fetch $UPSTREAM main
git diff $(git merge-base HEAD $UPSTREAM/main)

Review checklist

Work through each area from the PR review guide.

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同一仓库的技能

Design or extend DataFusion benchmarks using SQL where practical. Select representative workload variations, keep unrelated processing lightweight, and integrate runs with bench.sh so measurements reflect useful execution paths and remain practical to run.

中文简介正在准备中。当前显示英语简介。

  • Add SQL benchmarks for DataFusion operators
  • Select representative input sizes and filter conditions
  • Reduce unrelated processing overhead in measurements
apache/datafusion95012026年10月20日 更新

Audit one datafusion-spark function against Apache Spark 4.2.0. Compare source code, accepted types, and edge cases, verify expected results with PySpark, then fix differences and record remaining gaps as issues and disabled tests.

中文简介正在准备中。当前显示英语简介。

  • Auditing a function for Spark compatibility
  • Checking NULL, overflow, and ANSI mode behavior
  • Finding missing SQL test coverage
apache/datafusion95012026年10月20日 更新

Guide changes and reviews in datafusion-ffi, which connects separately compiled libraries. Check binary compatibility, memory ownership, and method coverage, and choose unit and cross-library tests for new wrappers, trait extensions, or codec changes.

中文简介正在准备中。当前显示英语简介。

  • Add FFI wrappers for DataFusion traits
  • Check that default method overrides cross the FFI boundary
  • Review binary compatibility and memory ownership in pull requests
apache/datafusion95012026年10月20日 更新

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