apache
@apache Organization
Public Skills
gradle-build
by apache
Guides understanding and using the Gradle build system in Apache Beam. Use when building projects, understanding dependencies, or troubleshooting build issues.
contributing
by apache
Guides the contribution workflow for Apache Beam, including creating PRs, issue management, code review process, and release cycles. Use when contributing code, creating PRs, or understanding the contribution process.
runners
by apache
Guides understanding and working with Apache Beam runners (Direct, Dataflow, Flink, Spark, etc.). Use when configuring pipelines for different execution environments or debugging runner-specific issues.
io-connectors
by apache
Guides development and usage of I/O connectors in Apache Beam. Use when working with I/O connectors, creating new connectors, or debugging data source/sink issues.
java-development
by apache
Guides Java SDK development in Apache Beam, including building, testing, running examples, and understanding the project structure. Use when working with Java code in sdks/java/, runners/, or examples/java/.
license-compliance
by apache
Ensures all new files include proper Apache 2.0 license headers. Use when creating any new file in the Apache Beam repository.
beam-concepts
by apache
Explains core Apache Beam programming model concepts including PCollections, PTransforms, Pipelines, and Runners. Use when learning Beam fundamentals or explaining pipeline concepts.
python-development
by apache
Guides Python SDK development in Apache Beam, including environment setup, testing, building, and running pipelines. Use when working with Python code in sdks/python/.
ci-cd
by apache
Guides understanding and working with Apache Beam's CI/CD system using GitHub Actions. Use when debugging CI failures, understanding test workflows, or modifying CI configuration.
datafusion-python
by apache
Use when the user is writing datafusion-python (Apache DataFusion Python bindings) DataFrame or SQL code. Covers imports, data loading, DataFrame operations, expression building, SQL-to-DataFrame mappings, idiomatic patterns, and common pitfalls.