rdblue commented on code in PR #6437:
URL: https://github.com/apache/iceberg/pull/6437#discussion_r1051674613


##########
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:
+        column_name = self.file_schema.find_column_name(field.field_id)
+
+        if column_name:
+            column_idx = self.table.schema.get_field_index(column_name)
+        else:
+            column_idx = -1
+
+        expected_arrow_type = schema_to_pyarrow(field.field_type)
+
+        # The idx will be -1 when the column can't be found
+        if column_idx >= 0:
+            column_field: pa.Field = self.table.schema[column_idx]
+            column_arrow_type: pa.DataType = column_field.type
+            column_data: pa.ChunkedArray = self.table[column_idx]
+            file_type = self.file_schema.find_type(field.field_id)
+
+            # In case of schema evolution
+            if column_arrow_type != expected_arrow_type:
+                # To check if the promotion is allowed
+                _ = promote(file_type, field.field_type)
+                column_data = column_data.cast(expected_arrow_type)
+        else:
+            import numpy as np
+
+            column_data = pa.array(np.full(shape=len(self.table), 
fill_value=None), type=expected_arrow_type)
+        return column_data
+
+    def list(self, _: ListType, element_result: pa.ChunkedArray) -> 
pa.ChunkedArray:
+        pass

Review Comment:
   I think we will need to implement at least `map` and `list`.



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