feat(datafusion): Add schema validation for partition projection #2008
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viirya
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| /// | ||
| /// # Returns | ||
| /// A new Arrow data type with all metadata removed from nested structures | ||
| fn strip_metadata_from_datatype(data_type: &DataType) -> DataType { |
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Two suggestions:
- Move this part to arrow module, we have plans to make move arrow out of core library, so it would be better to put all arrow related code to same module.
- Use ArrowSchemaVisitor to do it.
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Okay. I will update this today.
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Implement schema validation in project_with_partition to ensure the input schema matches the Iceberg table schema before calculating partition values. This prevents subtle bugs from schema mismatches and provides clear error messages when schemas don't match. Changes: - Add helper functions to recursively strip metadata from Arrow schemas - Implement schema validation that compares input schema with expected Iceberg table schema, ignoring metadata differences - Add comprehensive tests for metadata stripping and schema validation - Closes apache#1752 The implementation follows the approach suggested in issue apache#1752: - Recursively visits schema and removes metadata from all fields - Compares cleaned schemas using Arrow's built-in equality operator - Returns helpful error messages showing both schemas on mismatch Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
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Implement schema validation in project_with_partition to ensure the input schema matches the Iceberg table schema before calculating partition values. This prevents subtle bugs from schema mismatches and provides clear error messages when schemas don't match.
Changes:
The implementation follows the approach suggested in issue #1752:
Which issue does this PR close?
What changes are included in this PR?
Are these changes tested?