Copilot commented on code in PR #4083:
URL: https://github.com/apache/iceberg-python/pull/4083#discussion_r4200704841
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pyiceberg/io/pyarrow.py:
##########
@@ -1641,9 +1641,7 @@ def _get_column_projection_values(
for field_id in project_schema_diff:
for partition_field in partition_spec.fields_by_source_id(field_id):
if isinstance(partition_field.transform, IdentityTransform):
- 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)
Review Comment:
This still misses filter-only partition columns.
`_get_column_projection_values` derives candidates solely from
`projected_schema.field_ids`, so a scan selecting only `other_field` and
filtering with `IsNull("partition_col")` never records this explicit null;
`_ColumnNameTranslator` then falls back to the non-null `initial_default` and
incorrectly removes every row. Include the union of output and filter field IDs
(the caller's `projected_field_ids`) when computing missing projected values,
and cover the partial-projection case described in #4082.
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