Apache Beam is a unified programming model for Batch and Streaming data processing.
C-Rank Grade: A (Welcoming) - 68/100
External PR Merge Rate: 67%
Response Time: -
First Timer Success: 65%
apache/beam has a recorded first-timer success rate of 65.0%. Repositories ranked A typically provide actionable feedback during code reviews and actively nurture new community contributors.
Maintainers in apache/beam respond to incoming external pull requests in approximately 0.0 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.
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 67.9 places apache/beam in the A tier.
The external contributor pull request merge rate for apache/beam is 67.1%, based on public PR activity from non-core contributors.
apache/beam currently has 2 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".
Highly welcoming maintainers in apache/beam. Prompt code reviews with positive guidance for new contributors.
Average Response Latency
Tracks hours until a maintainer leaves a review, comment, or PR response.
External Acceptance Rate
Percentage of community pull requests successfully merged into main.
First PR Conversion
Rate at which developers submitting their first repository PR succeed.
Show contributors that your repository actively reviews and merges external pull requests.
[](https://getmerged.abhishekco.de/apache/beam?utm_source=github&utm_medium=badge)
Historical health & responsiveness evolution
External PR acceptance
First PR success rate
50% receive response in
90% receive response in
Maintainer review activity heatmap & prime window prediction
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Detected: UTC
Maintainers are most responsive around 13:00 UTC (13:00 UTC in your timezone). Recommended submission window is Monday - Wednesday from 13:00 to 17:00 UTC (13:00 - 17:00 UTC local).
Maintainer Strategy: Maintainer Sweet Spot: PRs under 150 lines merge in ~16 hours (84% approval). Large PRs (>500 lines) take ~115 hours (30% approval). Keep your diff compact for rapid review.
What needs to happen? Logical types defined in https://github.com/apache/beam/blob/master/model/pipeline/src/main/proto/org/apache/beam/model/pipeline/v1/schema.proto are not supported in Go SDK. This prevents Go SDK to use schema transforms in a meaningful way. Currently, only PYTHON_CALLABLE appear to be supported, beam/sdks/go/pkg/beam/transforms/xlang/python/external.go Line 42 in 1318bfe beam.RegisterSchemaProviderWithURN(pcsType, &callableSourceProvider{}, pythonCallableUrn) however, through a different mechanism. Likely we need to first implement a framework for portable logical types in Golang, then implement each of them Issue Priority Priority: 2 (default / most normal work should be filed as P2) Issue Components Component: Python SDK Component: Java SDK Component: Go SDK Component: Typescript SDK Component: IO connector Component: Beam YAML Component: Bea
What would you like to happen? both Flink and Dataflow supports that. PipelineResult allow stopping pipeline, drain may be helpful addition. Issue Priority Priority: 3 (nice-to-have improvement) Issue Components Component: Python SDK Component: Java SDK Component: Go SDK Component: Typescript SDK Component: IO connector Component: Beam YAML Component: Beam examples Component: Beam playground Component: Beam katas Component: Website Component: Infrastructure Component: Spark Runner Component: Flink Runner Component: Prism Runner Component: Twister2 Runner Component: Hazelcast Jet Runner Component: Google Cloud Dataflow Runner
What would you like to happen? In the case of high throughput jobs, we may want to disable metrics requests that adding pressures to backends. In Java SDK we honor pipeline option experiments "disableCounterMetrics", "disableStringSetMetrics", "disableBoundedTrieMetrics", but not yet in Python. Issue Priority Priority: 2 (default / most feature requests should be filed as P2) Issue Components Component: Python SDK Component: Java SDK Component: Go SDK Component: Typescript SDK Component: IO connector Component: Beam YAML Component: Beam examples Component: Beam playground Component: Beam katas Component: Website Component: Infrastructure Component: Spark Runner Component: Flink Runner Component: Prism Runner Component: Twister2 Runner Component: Hazelcast Jet Runner Component: Google Cloud Dataflow Runner
What would you like to happen? BigQuery IO does not have direct support for dedicated clone operations. https://beam.apache.org/documentation/io/built-in/google-bigquery/ Issue Priority Priority: 2 (default / most feature requests should be filed as P2) Issue Components Component: Python SDK Component: Java SDK Component: Go SDK Component: Typescript SDK Component: IO connector Component: Beam YAML Component: Beam examples Component: Beam playground Component: Beam katas Component: Website Component: Infrastructure Component: Spark Runner Component: Flink Runner Component: Samza Runner Component: Twister2 Runner Component: Hazelcast Jet Runner Component: Google Cloud Dataflow Runner
There's an inconsistency in how FileSystems.get_filesystem() handles missing optional dependencies between GCS and S3. Current Behavior S3 (without aws extra): >>> from apache_beam.io import filesystems >>> filesystems.FileSystems.get_filesystem("s3://blah") <apache_beam.io.aws.s3filesystem.S3FileSystem at 0x11a0af750> Returns the filesystem object; validation happens later when the filesystem is actually used. GCS (without gcp extra): >>> from apache_beam.io import filesystems >>> filesystems.FileSystems.get_filesystem("gcs://blah") ValueError: Unable to get filesystem from specified path, please use the correct path or ensure the required dependency is installed, e.g., pip install apache-beam[gcp]. Path specified: gcs://blah Raises immediately because GCSFileSystem isn't registered as a subclass. Proposed Behavior Both should behave consistently. GCSFileSystem should be returned from get_filesystem() like S3FileSystem, allowing callers to validate dependencies when the filesystem is
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When evaluating whether to contribute to apache/beam, 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/beam acknowledge new external contributions in approximately -. Out of all submitted pull requests from non-core authors in the last 180-day window, 67.1% were successfully merged into the primary branch.
apache/beam has a recorded first-timer success rate of 65.0%. Repositories ranked Welcoming typically provide actionable feedback during code reviews and actively nurture new community contributors.
The initial maintainer response time averages ~-. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.
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 67.9 places apache/beam in the Welcoming tier.
The external pull request merge rate is 67.1%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.
Yes, apache/beam currently has 2 active issue(s) tagged with beginner-friendly labels. You can inspect these directly from the repository issues tab.
All metrics displayed for apache/beam 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.