HonahX commented on code in PR #219:
URL: https://github.com/apache/iceberg-python/pull/219#discussion_r1451632412
##########
pyiceberg/io/pyarrow.py:
##########
@@ -698,77 +708,143 @@ def before_field(self, field: pa.Field) -> None:
def after_field(self, field: pa.Field) -> None:
"""Override this method to perform an action immediately after
visiting a field."""
+ def before_list_element(self, element: pa.Field) -> None:
+ """Override this method to perform an action immediately before
visiting an element within a ListType."""
+
+ def after_list_element(self, element: pa.Field) -> None:
+ """Override this method to perform an action immediately after
visiting an element within a ListType."""
+
+ def before_map_key(self, key: pa.Field) -> None:
+ """Override this method to perform an action immediately before
visiting a key within a MapType."""
+
+ def after_map_key(self, key: pa.Field) -> None:
+ """Override this method to perform an action immediately after
visiting a key within a MapType."""
+
+ def before_map_value(self, value: pa.Field) -> None:
+ """Override this method to perform an action immediately before
visiting a value within a MapType."""
+
+ def after_map_value(self, value: pa.Field) -> None:
+ """Override this method to perform an action immediately after
visiting a value within a MapType."""
+
@abstractmethod
- def schema(self, schema: pa.Schema, field_results: List[Optional[T]]) ->
Optional[T]:
+ def schema(self, schema: pa.Schema, struct_result: T) -> T:
"""Visit a schema."""
@abstractmethod
- def struct(self, struct: pa.StructType, field_results: List[Optional[T]])
-> Optional[T]:
+ def struct(self, struct: pa.StructType, field_results: List[T]) -> T:
"""Visit a struct."""
@abstractmethod
- def list(self, list_type: pa.ListType, element_result: Optional[T]) ->
Optional[T]:
+ def field(self, field: pa.Field, field_result: T) -> T:
+ """Visit a field."""
+
+ @abstractmethod
+ def list(self, list_type: pa.ListType, element_result: T) -> T:
"""Visit a list."""
@abstractmethod
- def map(self, map_type: pa.MapType, key_result: Optional[T], value_result:
Optional[T]) -> Optional[T]:
+ def map(self, map_type: pa.MapType, key_result: T, value_result: T) -> T:
"""Visit a map."""
@abstractmethod
- def primitive(self, primitive: pa.DataType) -> Optional[T]:
+ def primitive(self, primitive: pa.DataType) -> T:
"""Visit a primitive type."""
def _get_field_id(field: pa.Field) -> Optional[int]:
- for pyarrow_field_id_key in PYARROW_FIELD_ID_KEYS:
- if field_id_str := field.metadata.get(pyarrow_field_id_key):
- return int(field_id_str.decode())
+ if field.metadata:
+ for pyarrow_field_id_key in PYARROW_FIELD_ID_KEYS:
+ if field_id_str := field.metadata.get(pyarrow_field_id_key):
+ return int(field_id_str.decode())
return None
def _get_field_doc(field: pa.Field) -> Optional[str]:
- for pyarrow_doc_key in PYARROW_FIELD_DOC_KEYS:
- if doc_str := field.metadata.get(pyarrow_doc_key):
- return doc_str.decode()
+ if field.metadata:
+ for pyarrow_doc_key in PYARROW_FIELD_DOC_KEYS:
+ if doc_str := field.metadata.get(pyarrow_doc_key):
+ return doc_str.decode()
return None
-class _ConvertToIceberg(PyArrowSchemaVisitor[Union[IcebergType, Schema]]):
- def _convert_fields(self, arrow_fields: Iterable[pa.Field], field_results:
List[Optional[IcebergType]]) -> List[NestedField]:
- fields = []
- for i, field in enumerate(arrow_fields):
- field_id = _get_field_id(field)
- field_doc = _get_field_doc(field)
- field_type = field_results[i]
- if field_type is not None and field_id is not None:
- fields.append(NestedField(field_id, field.name, field_type,
required=not field.nullable, doc=field_doc))
- return fields
-
- def schema(self, schema: pa.Schema, field_results:
List[Optional[IcebergType]]) -> Schema:
- return Schema(*self._convert_fields(schema, field_results))
-
- def struct(self, struct: pa.StructType, field_results:
List[Optional[IcebergType]]) -> IcebergType:
- return StructType(*self._convert_fields(struct, field_results))
-
- def list(self, list_type: pa.ListType, element_result:
Optional[IcebergType]) -> Optional[IcebergType]:
+class _HasIds(PyArrowSchemaVisitor[bool]):
+ def schema(self, schema: pa.Schema, struct_result: bool) -> bool:
+ return struct_result
+
+ def struct(self, struct: pa.StructType, field_results: List[bool]) -> bool:
+ return all(field_results)
+
+ def field(self, field: pa.Field, field_result: bool) -> bool:
+ return all([_get_field_id(field) is not None, field_result])
+
+ def list(self, list_type: pa.ListType, element_result: bool) -> bool:
element_field = list_type.value_field
element_id = _get_field_id(element_field)
- if element_result is not None and element_id is not None:
- return ListType(element_id, element_result, element_required=not
element_field.nullable)
- return None
+ return element_result and element_id is not None
- def map(
- self, map_type: pa.MapType, key_result: Optional[IcebergType],
value_result: Optional[IcebergType]
- ) -> Optional[IcebergType]:
+ def map(self, map_type: pa.MapType, key_result: bool, value_result: bool)
-> bool:
key_field = map_type.key_field
key_id = _get_field_id(key_field)
value_field = map_type.item_field
value_id = _get_field_id(value_field)
- if key_result is not None and value_result is not None and key_id is
not None and value_id is not None:
- return MapType(key_id, key_result, value_id, value_result,
value_required=not value_field.nullable)
- return None
+ return all([key_id is not None, value_id is not None, key_result,
value_result])
+
+ def primitive(self, primitive: pa.DataType) -> bool:
+ return True
- def primitive(self, primitive: pa.DataType) -> IcebergType:
+
+class _ConvertToIceberg(PyArrowSchemaVisitor[Union[IcebergType, Schema]]):
+ """Converts PyArrowSchema to Iceberg Schema. Applies the IDs from
name_mapping if provided."""
+
+ field_names: List[str]
+ name_mapping: Optional[NameMapping]
+
+ def __init__(self, name_mapping: Optional[NameMapping] = None) -> None:
+ self.field_names = []
+ self.name_mapping = name_mapping
+
+ def _current_path(self) -> str:
+ return ".".join(self.field_names)
+
+ def _get_field_id(self, field: pa.Field) -> int:
Review Comment:
I think @syun64 is right that currently we do not have a convenient way to
convert an in memory arrow table to a new iceberg table. I'm +1 on adding a
utility method to extract the iceberg schema from a pyarrow table, similar to
the existing
[SparkSchemaUtil.schemaForTable](https://github.com/apache/iceberg/blob/31e31fd819c846f49d2bd459b8bfadfdc3c2bc3a/spark/v3.5/spark/src/main/java/org/apache/iceberg/spark/SparkSchemaUtil.java#L51-L65).
A similar use case is in table migration: we convert Spark or Delta Lake
schemas to new iceberg schemas with fresh ids for use in
`createTableTransaction`
I think it's crucial for the method's docstring to specify that this utility
should be employed exclusively when creating a new iceberg table. It might be
better to make this a distinct method (may be named as `new_schema_for_table`)
separate from `pyarrow_to_schema` to avoid confusion. As for the implementation
details, I think we can introduce a new visitor
(`_ConvertToIcebergWithFreshIds`) for this. Do you think this sounds reasonable?
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