add datadog io normalization and yaml#38362
add datadog io normalization and yaml#38362derrickaw wants to merge 38 commits intoapache:masterfrom
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Code Review
This pull request adds a DatadogWriteSchemaTransformProvider to Apache Beam, allowing for Datadog integration within schema-aware pipelines and YAML. The implementation includes a row-based writer, configuration validation, and integration tests. Reviewer feedback identifies that the writer currently lacks batching, which is inefficient for API usage, and that the parallelism setting may be bypassed by transform fusion. Further recommendations include strengthening configuration validation for mandatory and numeric fields, ensuring output consistency with the provider's metadata, and improving test assertions for invalid configurations.
Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## master #38362 +/- ##
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- Coverage 60.50% 57.03% -3.48%
+ Complexity 20442 3634 -16808
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Files 3307 1185 -2122
Lines 315339 189633 -125706
Branches 16942 3751 -13191
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- Hits 190799 108148 -82651
+ Misses 116084 78034 -38050
+ Partials 8456 3451 -5005
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Code Review
This pull request implements a Datadog write SchemaTransform, enabling data ingestion into Datadog through Beam's SchemaTransform API and YAML. The changes include the Java provider and configuration classes, comprehensive unit tests, and Python-based integration test infrastructure utilizing Docker and mock servers. Key feedback includes addressing silent write failures when error handling is unconfigured, correcting the output port identifier in the PCollectionRowTuple, and refining the handling of nullable configuration parameters. Further improvements were suggested regarding the serialization of error payloads and the removal of unrelated coder registrations.
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/gemini review |
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Code Review
This pull request introduces the DatadogWriteSchemaTransformProvider, enabling Datadog write operations through Beam SchemaTransforms and YAML pipelines. The changes include the core Java implementation, comprehensive unit tests, and integration test utilities in Python using a mock Datadog server and container. Feedback focuses on ensuring consistency between the advertised output collection names and the actual tags used in the PCollectionRowTuple, as well as minor formatting improvements in the Python integration code.
…adding initil yaml test file
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