rdblue commented on code in PR #6437:
URL: https://github.com/apache/iceberg/pull/6437#discussion_r1056562592
##########
python/pyiceberg/io/pyarrow.py:
##########
@@ -437,3 +465,198 @@ 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())
+
+
+def project_table(
+ files: Iterable[FileScanTask], table: Table, row_filter:
BooleanExpression, projected_schema: Schema, case_sensitive: bool
+) -> pa.Table:
+ """Resolves the right columns based on the identifier
+
+ Args:
+ files(Iterable[FileScanTask]): A URI or a path to a local file
+ table(Table): The table that's being queried
+ row_filter(BooleanExpression): The expression for filtering rows
+ projected_schema(Schema): The output schema
+ case_sensitive(bool): Case sensitivity when looking up column names
+
+ Raises:
+ ResolveException: When an incompatible query is done
+ """
+
+ if isinstance(table.io, PyArrowFileIO):
+ scheme, path = PyArrowFileIO.parse_location(table.location())
+ fs = table.io.get_fs(scheme)
+ else:
+ raise ValueError(f"Expected PyArrowFileIO, got: {table.io}")
+
+ bound_row_filter = bind(table.schema(), row_filter,
case_sensitive=case_sensitive)
+
+ projected_field_ids = {
+ id for id in projected_schema.field_ids if not
isinstance(projected_schema.find_type(id), (MapType, ListType))
+ }.union(extract_field_ids(bound_row_filter))
+
+ tables = []
+ for task in files:
+ _, path = PyArrowFileIO.parse_location(task.file.file_path)
+
+ # Get the schema
+ with fs.open_input_file(path) as fout:
+ parquet_schema = pq.read_schema(fout)
+ schema_raw = parquet_schema.metadata.get(ICEBERG_SCHEMA)
+ file_schema = Schema.parse_raw(schema_raw)
+
+ pyarrow_filter = None
+ if row_filter is not AlwaysTrue():
+ translated_row_filter = translate_column_names(bound_row_filter,
file_schema, case_sensitive=case_sensitive)
+ bound_row_filter = bind(file_schema, translated_row_filter,
case_sensitive=case_sensitive)
+ pyarrow_filter = expression_to_pyarrow(bound_row_filter)
+
+ file_project_schema = prune_columns(file_schema, projected_field_ids,
select_full_types=False)
+
+ if file_schema is None:
+ raise ValueError(f"Missing Iceberg schema in Metadata for file:
{path}")
+
+ # Prune the stuff that we don't need anyway
+ file_project_schema_arrow = schema_to_pyarrow(file_project_schema)
+
+ arrow_table = ds.dataset(
+ source=[path], schema=file_project_schema_arrow,
format=ds.ParquetFileFormat(), filesystem=fs
+ ).to_table(filter=pyarrow_filter)
+
+ tables.append(to_requested_schema(projected_schema,
file_project_schema, arrow_table))
+
+ if len(tables) > 1:
+ return pa.concat_tables(tables)
+ else:
+ return tables[0]
+
+
+def to_requested_schema(requested_schema: Schema, file_schema: Schema, table:
pa.Table) -> pa.Table:
+ return VisitWithArrow(requested_schema, file_schema, table).visit()
+
+
+class VisitWithArrow:
+ requested_schema: Schema
+ file_schema: Schema
+ table: pa.Table
+
+ def __init__(self, requested_schema: Schema, file_schema: Schema, table:
pa.Table) -> None:
+ self.requested_schema = requested_schema
+ self.file_schema = file_schema
+ self.table = table
+
+ def visit(self) -> pa.Table:
+ return self.visit_with_arrow(self.requested_schema, self.file_schema)
+
+ @singledispatchmethod
+ def visit_with_arrow(self, requested_schema: Union[Schema, IcebergType],
file_schema: Union[Schema, IcebergType]) -> pa.Table:
+ """A generic function for applying a schema visitor to any point
within a schema
+
+ The function traverses the schema in post-order fashion
+
+ Args:
+ obj(Schema | IcebergType): An instance of a Schema or an
IcebergType
+ visitor (VisitWithArrow[T]): An instance of an implementation of
the generic VisitWithArrow base class
+
+ Raises:
+ NotImplementedError: If attempting to visit an unrecognized object
type
+ """
+ raise NotImplementedError(f"Cannot visit non-type: {requested_schema}")
Review Comment:
Unsupported type? We can't necessarily conclude that it is a non-type.
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