rdblue commented on code in PR #6437:
URL: https://github.com/apache/iceberg/pull/6437#discussion_r1051676210
##########
python/pyiceberg/io/pyarrow.py:
##########
@@ -437,3 +459,120 @@ def visit_or(self, left_result: pc.Expression,
right_result: pc.Expression) -> p
def expression_to_pyarrow(expr: BooleanExpression) -> pc.Expression:
return boolean_expression_visit(expr, _ConvertToArrowExpression())
+
+
+class _ConstructFinalSchema(SchemaVisitor[pa.ChunkedArray]):
+ file_schema: Schema
+ table: pa.Table
+
+ def __init__(self, file_schema: Schema, table: pa.Table):
+ self.file_schema = file_schema
+ self.table = table
+
+ def schema(self, schema: Schema, struct_result: List[pa.ChunkedArray]) ->
pa.Table:
+ return pa.table(struct_result, schema=schema_to_pyarrow(schema))
+
+ def struct(self, _: StructType, field_results: List[pa.ChunkedArray]) ->
List[pa.ChunkedArray]:
+ return field_results
+
+ def field(self, field: NestedField, _: pa.ChunkedArray) -> pa.ChunkedArray:
Review Comment:
This approach assumes that the column data is available at a specific column
index in the table. I'm not sure that is true. It _might_ be if the column
index space is flat (e.g. id, location.lat, location.lon, data) but it may not
be (e.g. id, location, data).
If that's the case, you will probably want a
[`SchemaWithPartnerVisitor`](https://github.com/apache/iceberg/blob/master/core/src/main/java/org/apache/iceberg/schema/SchemaWithPartnerVisitor.java)
to traverse two structures (the table and the schema) at the same time.
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