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🟡 Changes recommended
Filter-only partition columns still fall back to the initial default when excluded from the output projection.
Review effort: Balanced
Findings: 1
What changed in this PR
Fixes null identity partition projection so it takes precedence over a field’s initial default.
Changes:
- Preserves explicit null partition values during projection and filtering.
- Adds regression coverage for null projection and predicates.
| File | Description |
|---|---|
pyiceberg/io/pyarrow.py |
Distinguishes explicit null projections from absent values. |
tests/io/test_pyarrow.py |
Tests null identity partitions with initial defaults. |
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| partition_value = accessors[partition_field.field_id].get(file.partition) | ||
| if partition_value is not None: | ||
| projected_missing_fields[field_id] = partition_value | ||
| projected_missing_fields[field_id] = accessors[partition_field.field_id].get(file.partition) |
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Rationale for this change
The spec's Column Projection rules say that when a field isn't present in a data file, we resolve its value in order:
Today _get_column_projection_values only records the identity partition value when it's non-null. So when a file's partition value is null, we skip rule 1 and fall through to rule 3, as if the partition metadata had nothing to say. This was harmless before v3 because initial-default was always null anyway, but with a non-null initial-default we now read the default instead of null.
This came up while reviewing #4082
Are these changes tested?
Yes
Are there any user-facing changes?
Only for v3 tables with a non-null initial-default on an identity-partitioned column on null partition. This is a bug fix that conforms to the spec: https://iceberg.apache.org/spec/#column-projection