rdblue commented on code in PR #6233:
URL: https://github.com/apache/iceberg/pull/6233#discussion_r1027370136
##########
python/pyiceberg/table/__init__.py:
##########
@@ -199,16 +223,114 @@ def use_ref(self, name: str):
raise ValueError(f"Cannot scan unknown ref={name}")
- def select(self, *field_names: str) -> TableScan:
+ def select(self, *field_names: str) -> S:
if "*" in self.selected_fields:
return self.update(selected_fields=field_names)
return
self.update(selected_fields=tuple(set(self.selected_fields).intersection(set(field_names))))
- def filter_rows(self, new_row_filter: BooleanExpression) -> TableScan:
+ def filter_rows(self, new_row_filter: BooleanExpression) -> S:
return self.update(row_filter=And(self.row_filter, new_row_filter))
- def filter_partitions(self, new_partition_filter: BooleanExpression) ->
TableScan:
+ def filter_partitions(self, new_partition_filter: BooleanExpression) -> S:
return self.update(partition_filter=And(self.partition_filter,
new_partition_filter))
- def with_case_sensitive(self, case_sensitive: bool = True) -> TableScan:
+ def with_case_sensitive(self, case_sensitive: bool = True) -> S:
return self.update(case_sensitive=case_sensitive)
+
+
+class ScanTask(ABC):
+ pass
+
+
+@dataclass(init=False)
+class FileScanTask(ScanTask):
+ data_file: DataFile
+ start: int
+ length: int
+
+ def __init__(self, data_file: DataFile, start: Optional[int] = None,
length: Optional[int] = None):
+ self.data_file = data_file
+ self.start = start or 0
+ self.length = length or data_file.file_size_in_bytes
+
+
+class _DictAsStruct(StructProtocol):
+ pos_to_name: dict[int, str]
+ wrapped: dict[str, Any]
+
+ def __init__(self, partition_type: StructType):
+ self.pos_to_name = {}
+ for pos, field in enumerate(partition_type.fields):
+ self.pos_to_name[pos] = field.name
+
+ def wrap(self, to_wrap: dict[str, Any]) -> _DictAsStruct:
+ self.wrapped = to_wrap
+ return self
+
+ def get(self, pos: int) -> Any:
+ return self.wrapped[self.pos_to_name[pos]]
+
+ def set(self, pos: int, value: Any) -> None:
+ raise NotImplementedError("Cannot set values in DictAsStruct")
+
+
+class DataScan(TableScan["DataScan"]):
+ def __init__(
+ self,
+ table: Table,
+ row_filter: Optional[BooleanExpression] = None,
+ partition_filter: Optional[BooleanExpression] = None,
+ selected_fields: Tuple[str] = ("*",),
+ case_sensitive: bool = True,
+ snapshot_id: Optional[int] = None,
+ options: Properties = EMPTY_DICT,
+ ):
+ super().__init__(table, row_filter, partition_filter, selected_fields,
case_sensitive, snapshot_id, options)
+
+ def plan_files(self) -> Iterator[ScanTask]:
+ snapshot = self.snapshot()
+ if not snapshot:
+ return ()
+
+ io = self.table.io
+
+ # step 1: filter manifests using partition summaries
+ # the filter depends on the partition spec used to write the manifest
file, so create a cache of filters for each spec id
+
+ @cache
+ def manifest_filter(spec_id: int) -> Callable[[ManifestFile], bool]:
+ spec = self.table.specs()[spec_id]
+ return visitors.manifest_evaluator(spec, self.table.schema(),
self.partition_filter, self.case_sensitive)
+
+ def partition_summary_filter(manifest_file: ManifestFile) -> bool:
+ return
manifest_filter(manifest_file.partition_spec_id)(manifest_file)
+
+ manifests = list(filter(partition_summary_filter,
snapshot.manifests(io)))
+
+ # step 2: filter the data files in each manifest
+ # this filter depends on the partition spec used to write the manifest
file
+
+ @cache
+ def partition_evaluator(spec_id: int) -> Callable[[DataFile], bool]:
+ spec = self.table.specs()[spec_id]
+ partition_type = spec.partition_type(self.table.schema())
+ partition_schema = Schema(*partition_type.fields)
+
+ # TODO: project the row filter # pylint: disable=W0511
+ partition_expr = And(self.partition_filter, AlwaysTrue())
+
+ # TODO: remove the dict to struct wrapper by using a
StructProtocol record # pylint: disable=W0511
+ wrapper = _DictAsStruct(partition_type)
+ evaluator = visitors.expression_evaluator(partition_schema,
partition_expr, self.case_sensitive)
+
+ return lambda data_file:
evaluator(wrapper.wrap(data_file.partition))
+
+ for manifest in manifests:
+ partition_filter = partition_evaluator(manifest.partition_spec_id)
+ all_files = files(io.new_input(manifest.manifest_path))
Review Comment:
This uses `files`, which doesn't do any column pruning. Pruning columns
would help performance in the short term, but stats are going to be used in the
long term so it's not a great way to speed up scan planning.
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