kevinjqliu commented on code in PR #921:
URL: https://github.com/apache/iceberg-python/pull/921#discussion_r1676880923
##########
pyiceberg/io/pyarrow.py:
##########
@@ -2079,36 +2082,63 @@ def _check_schema_compatible(table_schema: Schema,
other_schema: pa.Schema, down
Raises:
ValueError: If the schemas are not compatible.
"""
- name_mapping = table_schema.name_mapping
- try:
- task_schema = pyarrow_to_schema(
- other_schema, name_mapping=name_mapping,
downcast_ns_timestamp_to_us=downcast_ns_timestamp_to_us
- )
- except ValueError as e:
- other_schema = _pyarrow_to_schema_without_ids(other_schema,
downcast_ns_timestamp_to_us=downcast_ns_timestamp_to_us)
- additional_names = set(other_schema.column_names) -
set(table_schema.column_names)
- raise ValueError(
- f"PyArrow table contains more columns: {',
'.join(sorted(additional_names))}. Update the schema first (hint, use
union_by_name)."
- ) from e
-
- if table_schema.as_struct() != task_schema.as_struct():
- from rich.console import Console
- from rich.table import Table as RichTable
+ task_schema = assign_fresh_schema_ids(
+ _pyarrow_to_schema_without_ids(other_schema,
downcast_ns_timestamp_to_us=downcast_ns_timestamp_to_us)
+ )
- console = Console(record=True)
+ extra_fields = task_schema.field_names - table_schema.field_names
+ missing_fields = table_schema.field_names - task_schema.field_names
+ fields_in_both =
task_schema.field_names.intersection(table_schema.field_names)
+
+ from rich.console import Console
+ from rich.table import Table as RichTable
+
+ console = Console(record=True)
+
+ rich_table = RichTable(show_header=True, header_style="bold")
+ rich_table.add_column("Field Name")
+ rich_table.add_column("Category")
+ rich_table.add_column("Table field")
+ rich_table.add_column("Dataframe field")
+
+ def print_nullability(required: bool) -> str:
+ return "required" if required else "optional"
+
+ for field_name in fields_in_both:
Review Comment:
just want to check my understanding, this works for nested fields because
nested fields are "flattened" by `. field_names` and then fetched by
`.find_field`.
For example: a `df` schema like
```
task_schema = pa.field(
"person",
pa.struct([
pa.field("name", pa.string(), nullable=True),
]),
nullable=True,
)
```
`task_schema.field_names` will produce `{"person", "person.name"}`.
`task_schema.find_field("person")` and
`task_schema.find_field("person.name")` will fetch the corresponding fields
##########
pyiceberg/io/pyarrow.py:
##########
@@ -2079,36 +2082,63 @@ def _check_schema_compatible(table_schema: Schema,
other_schema: pa.Schema, down
Raises:
ValueError: If the schemas are not compatible.
"""
- name_mapping = table_schema.name_mapping
- try:
- task_schema = pyarrow_to_schema(
- other_schema, name_mapping=name_mapping,
downcast_ns_timestamp_to_us=downcast_ns_timestamp_to_us
- )
- except ValueError as e:
- other_schema = _pyarrow_to_schema_without_ids(other_schema,
downcast_ns_timestamp_to_us=downcast_ns_timestamp_to_us)
- additional_names = set(other_schema.column_names) -
set(table_schema.column_names)
- raise ValueError(
- f"PyArrow table contains more columns: {',
'.join(sorted(additional_names))}. Update the schema first (hint, use
union_by_name)."
- ) from e
-
- if table_schema.as_struct() != task_schema.as_struct():
- from rich.console import Console
- from rich.table import Table as RichTable
+ task_schema = assign_fresh_schema_ids(
+ _pyarrow_to_schema_without_ids(other_schema,
downcast_ns_timestamp_to_us=downcast_ns_timestamp_to_us)
+ )
- console = Console(record=True)
+ extra_fields = task_schema.field_names - table_schema.field_names
+ missing_fields = table_schema.field_names - task_schema.field_names
+ fields_in_both =
task_schema.field_names.intersection(table_schema.field_names)
+
+ from rich.console import Console
+ from rich.table import Table as RichTable
+
+ console = Console(record=True)
+
+ rich_table = RichTable(show_header=True, header_style="bold")
+ rich_table.add_column("Field Name")
+ rich_table.add_column("Category")
+ rich_table.add_column("Table field")
+ rich_table.add_column("Dataframe field")
+
+ def print_nullability(required: bool) -> str:
+ return "required" if required else "optional"
+
+ for field_name in fields_in_both:
+ lhs = table_schema.find_field(field_name)
+ rhs = task_schema.find_field(field_name)
+ # Check nullability
+ if lhs.required != rhs.required:
Review Comment:
to make this a bit more complicated...
an optional field can be written to by a required field. the schema is
"widened"
a required field cannot be written to by an optional field. cannot deal with
null value
##########
pyiceberg/io/pyarrow.py:
##########
@@ -2079,36 +2082,63 @@ def _check_schema_compatible(table_schema: Schema,
other_schema: pa.Schema, down
Raises:
ValueError: If the schemas are not compatible.
"""
- name_mapping = table_schema.name_mapping
- try:
- task_schema = pyarrow_to_schema(
- other_schema, name_mapping=name_mapping,
downcast_ns_timestamp_to_us=downcast_ns_timestamp_to_us
- )
- except ValueError as e:
- other_schema = _pyarrow_to_schema_without_ids(other_schema,
downcast_ns_timestamp_to_us=downcast_ns_timestamp_to_us)
- additional_names = set(other_schema.column_names) -
set(table_schema.column_names)
- raise ValueError(
- f"PyArrow table contains more columns: {',
'.join(sorted(additional_names))}. Update the schema first (hint, use
union_by_name)."
- ) from e
-
- if table_schema.as_struct() != task_schema.as_struct():
- from rich.console import Console
- from rich.table import Table as RichTable
+ task_schema = assign_fresh_schema_ids(
+ _pyarrow_to_schema_without_ids(other_schema,
downcast_ns_timestamp_to_us=downcast_ns_timestamp_to_us)
+ )
- console = Console(record=True)
+ extra_fields = task_schema.field_names - table_schema.field_names
+ missing_fields = table_schema.field_names - task_schema.field_names
+ fields_in_both =
task_schema.field_names.intersection(table_schema.field_names)
+
+ from rich.console import Console
+ from rich.table import Table as RichTable
+
+ console = Console(record=True)
+
+ rich_table = RichTable(show_header=True, header_style="bold")
+ rich_table.add_column("Field Name")
+ rich_table.add_column("Category")
+ rich_table.add_column("Table field")
+ rich_table.add_column("Dataframe field")
+
+ def print_nullability(required: bool) -> str:
+ return "required" if required else "optional"
+
+ for field_name in fields_in_both:
+ lhs = table_schema.find_field(field_name)
+ rhs = task_schema.find_field(field_name)
+ # Check nullability
+ if lhs.required != rhs.required:
Review Comment:
similar to below with type promotion, we can deal with this later!
##########
pyiceberg/io/pyarrow.py:
##########
@@ -1450,14 +1451,17 @@ def field_partner(self, partner_struct:
Optional[pa.Array], field_id: int, _: st
except ValueError:
return None
- if isinstance(partner_struct, pa.StructArray):
- return partner_struct.field(name)
- elif isinstance(partner_struct, pa.Table):
- return partner_struct.column(name).combine_chunks()
- elif isinstance(partner_struct, pa.RecordBatch):
- return partner_struct.column(name)
- else:
- raise ValueError(f"Cannot find {name} in expected
partner_struct type {type(partner_struct)}")
+ try:
+ if isinstance(partner_struct, pa.StructArray):
+ return partner_struct.field(name)
+ elif isinstance(partner_struct, pa.Table):
+ return partner_struct.column(name).combine_chunks()
+ elif isinstance(partner_struct, pa.RecordBatch):
+ return partner_struct.column(name)
+ else:
+ raise ValueError(f"Cannot find {name} in expected
partner_struct type {type(partner_struct)}")
+ except KeyError:
Review Comment:
Is this change responsible for schema projection / writing a subset of the
schema? Do you mind expanding on the mechanism behind how this works? I'm
curious
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