feat(yaml): add a simple schema unification for Flatten transform

[liferoad]

Fixes #35666

Use one simple rule to unify the schema: when the fields have different types, always use Optional[Any].

Tested:

cd sdks/python
pytest -v apache_beam/yaml/yaml_transform_test.py
pytest -v apache_beam/yaml/programming_guide_test.py

./gradlew :sdks:python:yamlIntegrationTests

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[gemini-code-assist]

Summary of Changes

Hello @liferoad, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request enhances the Flatten transform within Apache Beam's YAML DSL by introducing robust schema unification capabilities. The primary goal is to allow Flatten to seamlessly combine PCollections that may have differing schemas, automatically resolving type conflicts and handling missing fields to produce a consistent output schema. This makes the Flatten transform more flexible and powerful when dealing with heterogeneous data sources.

Highlights

• Schema Unification Logic: I've introduced a new private method, _merge_schemas, within the Flatten transform. This method is responsible for analyzing the schemas of multiple input PCollections. It identifies common fields and their types, making fields optional if they are missing in some inputs. Crucially, if a field exists across multiple inputs with different data types, its unified type is set to Optional[Any] to accommodate all possibilities.
• Element Transformation for Schema Compliance: A new private helper, _unify_element_with_schema, has been added. This function takes an individual element and a target schema, then transforms the element to conform to that schema. It ensures that all fields present in the target schema are represented in the output element, filling in None for missing fields and handling conversions for iterable types (e.g., ensuring they are lists).
• Enhanced Flatten Transform: The expand method of the Flatten transform has been updated to leverage the new schema unification capabilities. Before performing the actual flatten operation, it now attempts to derive a unified schema from its inputs. If a unified schema is successfully determined, each input PCollection is mapped through the _unify_element_with_schema function to ensure all elements adhere to the consistent schema before being flattened together.
• Comprehensive Test Coverage: I've added six new unit tests to yaml_transform_test.py to thoroughly validate the schema unification logic for the Flatten transform. These tests cover various scenarios, including basic unification, handling optional fields, unifying fields with different types, list fields, missing fields, and complex mixed schemas, ensuring the new functionality behaves as expected.

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[gemini-code-assist]

Code Review

This pull request introduces a valuable feature for schema unification in the YAML Flatten transform. The logic for merging schemas and unifying elements is well-implemented and handles various cases, including missing fields and differing types. The addition of comprehensive tests covering multiple scenarios is excellent and ensures the feature's robustness. My review includes a couple of suggestions focused on improving code readability and maintainability in both the implementation and the new tests. These are not critical but would enhance the long-term quality of the code.

[github-actions]

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[damccorm]

thanks, this LGTM - just had one question, feel free to merge though

[damccorm]

Thanks!

[github-actions]

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R: @damccorm for label python.

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