Fokko commented on code in PR #8622:
URL: https://github.com/apache/iceberg/pull/8622#discussion_r1335646423
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python/pyiceberg/manifest.py:
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@@ -265,6 +306,64 @@ def __init__(self, *data: Any, **named_data: Any) -> None:
super().__init__(*data, **{"struct": PARTITION_FIELD_SUMMARY_TYPE,
**named_data})
+class PartitionFieldStats:
+ _type: PrimitiveType
+ _contains_null: bool
+ _contains_nan: bool
+ _min: Optional[Any]
+ _max: Optional[Any]
+
+ def __init__(self, iceberg_type: IcebergType) -> None:
+ if not isinstance(iceberg_type, PrimitiveType):
+ raise ValueError(f"Expected a primitive type for the partition
field, got {iceberg_type}")
+ self._type = iceberg_type
+ self._contains_null = False
+ self._contains_nan = False
+ self._min = None
+ self._max = None
+
+ def to_summary(self) -> PartitionFieldSummary:
+ return PartitionFieldSummary(
+ contains_null=self._contains_null,
+ contains_nan=self._contains_nan,
+ lower_bound=to_bytes(self._type, self._min) if self._min is not
None else None,
+ upper_bound=to_bytes(self._type, self._max) if self._max is not
None else None,
+ )
+
+ def update(self, value: Any) -> None:
+ if value is None:
+ self._contains_null = True
+ elif math.isnan(value):
+ self._contains_nan = True
+ else:
+ if self._min is None:
+ self._min = value
+ self._max = value
+ else:
+ self._max = max(self._max, value)
+ self._min = min(self._min, value)
+
+
+class PartitionSummary:
+ _field_stats: List[PartitionFieldStats]
+ _types: List[IcebergType]
+
+ def __init__(self, spec: PartitionSpec, schema: Schema):
+ self._types = [field.field_type for field in
spec.partition_type(schema).fields]
+ self._field_stats = [PartitionFieldStats(field_type) for field_type in
self._types]
+
+ def summaries(self) -> List[PartitionFieldSummary]:
+ return [field.to_summary() for field in self._field_stats]
+
+ def update(self, partition_keys: Record) -> PartitionSummary:
Review Comment:
The function is nicer than the PartitionSummary class. The number of fields
should always be reasonable. This can explode if you do very fine-grained
partitioning. Since Arrow does not scale out (yet), the number of files will
probably be rather small.
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