kosiew opened a new pull request, #17281:
URL: https://github.com/apache/datafusion/pull/17281
## Which issue does this PR close?
* Closes #16579
## Rationale for this change
Evolving data sources often have structural mismatches with the expected
table schema, especially when nested `Struct` types are involved. This PR
introduces robust handling for schema adaptation and column casting within
Apache DataFusion to ensure compatibility and correctness when processing such
evolving schemas.
## What changes are included in this PR?
* Introduces `cast_column` for recursively casting nested `StructArray`
fields to match target schema.
* Adds compatibility checks to prevent casting nullable fields to
non-nullable targets.
* Updates the `SchemaAdapter` and `SchemaMapping` logic to leverage
`cast_column`.
* Adds thorough unit tests covering:
* Casting structs with reordering, extra, and missing fields
* Preserving parent nullability
* Structs containing arrays and maps
* Schema mapping and record batch transformation
* Fixes column casting behavior in `pruning_predicate` by using
`cast_column` instead of generic Arrow cast.
* Updates documentation:
* Adds new guide: `docs/source/library-user-guide/schema_adapter.md`
* References this guide in main user and API docs
## Are these changes tested?
Yes, extensive tests are included that:
* Validate the `cast_column` logic across multiple complex nested schemas.
* Verify compatibility validation logic.
* Test end-to-end behavior of `SchemaAdapter::map_batch()` with various
structural transformations.
* Ensure correct pruning predicate behavior when stats use structs with
different field types.
## Are there any user-facing changes?
Yes:
* Users benefit from improved compatibility when reading nested structured
data with evolving schemas.
* Documentation has been expanded to include a new section explaining how
schema adaptation works and how to use `cast_column`.
There are no breaking changes to public APIs.
---
This change enhances DataFusion's resilience to schema drift and paves the
way for more robust handling of semi-structured data. ✨
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