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[SPARK-56377][PYTHON] Add type hint for shuffle.py #55241

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gaogaotiantian wants to merge 5 commits into from
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[SPARK-56377][PYTHON] Add type hint for shuffle.py #55241

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50a45b6
Add type hint for shuffle
gaogaotiantian Apr 3, 2026
e679fdf
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gaogaotiantian Apr 3, 2026
39e85b5
Done!
gaogaotiantian Apr 7, 2026
6303f99
Remove unnecessary change
gaogaotiantian Apr 7, 2026
418dc39
Merge branch 'master' into shuffle-type-hint
gaogaotiantian Apr 7, 2026
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3 changes: 0 additions & 3 deletions python/mypy.ini
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Original file line number Diff line number Diff line change
Expand Up @@ -38,9 +38,6 @@ disallow_untyped_defs = False
[mypy-pyspark.serializers]
disallow_untyped_defs = False

[mypy-pyspark.shuffle]
disallow_untyped_defs = False

[mypy-pyspark.streaming.util]
disallow_untyped_defs = False

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16 changes: 8 additions & 8 deletions python/pyspark/core/rdd.py
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Expand Up @@ -97,7 +97,7 @@
if TYPE_CHECKING:
from py4j.java_gateway import JavaObject

from pyspark._typing import S, NumberOrArray
from pyspark._typing import S, SizedIterable, NumberOrArray
from pyspark.core.context import SparkContext
from pyspark.sql.dataframe import DataFrame
from pyspark.sql.types import AtomicType, StructType
Expand Down Expand Up @@ -1274,7 +1274,7 @@ def repartitionAndSortWithinPartitions(
serializer = self._jrdd_deserializer

def sortPartition(iterator: Iterable[Tuple[K, V]]) -> Iterable[Tuple[K, V]]:
sort = ExternalSorter(memory * 0.9, serializer).sorted
sort = ExternalSorter[tuple[K, V]](memory * 0.9, serializer).sorted
return iter(sort(iterator, key=lambda k_v: keyfunc(k_v[0]), reverse=(not ascending)))

return self.partitionBy(numPartitions, partitionFunc).mapPartitions(sortPartition, True)
Expand Down Expand Up @@ -1354,7 +1354,7 @@ def sortByKey(
serializer = self._jrdd_deserializer

def sortPartition(iterator: Iterable[Tuple[K, V]]) -> Iterable[Tuple[K, V]]:
sort = ExternalSorter(memory * 0.9, serializer).sorted
sort = ExternalSorter[tuple[K, V]](memory * 0.9, serializer).sorted
return iter(sort(iterator, key=lambda kv: keyfunc(kv[0]), reverse=(not ascending)))

if numPartitions == 1:
Expand Down Expand Up @@ -3841,15 +3841,15 @@ def combineByKey(
agg = Aggregator(createCombiner, mergeValue, mergeCombiners)

def combineLocally(iterator: Iterable[Tuple[K, V]]) -> Iterable[Tuple[K, U]]:
merger = ExternalMerger(agg, memory * 0.9, serializer)
merger = ExternalMerger[K, V, U](agg, memory * 0.9, serializer)
merger.mergeValues(iterator)
return merger.items()

locally_combined = self.mapPartitions(combineLocally, preservesPartitioning=True)
shuffled = locally_combined.partitionBy(numPartitions, partitionFunc)

def _mergeCombiners(iterator: Iterable[Tuple[K, U]]) -> Iterable[Tuple[K, U]]:
merger = ExternalMerger(agg, memory, serializer)
merger = ExternalMerger[K, V, U](agg, memory, serializer)
merger.mergeCombiners(iterator)
return merger.items()

Expand Down Expand Up @@ -4033,15 +4033,15 @@ def mergeCombiners(a: List[V], b: List[V]) -> List[V]:
agg = Aggregator(createCombiner, mergeValue, mergeCombiners)

def combine(iterator: Iterable[Tuple[K, V]]) -> Iterable[Tuple[K, List[V]]]:
merger = ExternalMerger(agg, memory * 0.9, serializer)
merger = ExternalMerger[K, V, list[V]](agg, memory * 0.9, serializer)
merger.mergeValues(iterator)
return merger.items()

locally_combined = self.mapPartitions(combine, preservesPartitioning=True)
shuffled = locally_combined.partitionBy(numPartitions, partitionFunc)

def groupByKey(it: Iterable[Tuple[K, List[V]]]) -> Iterable[Tuple[K, List[V]]]:
merger = ExternalGroupBy(agg, memory, serializer)
def groupByKey(it: Iterable[Tuple[K, List[V]]]) -> Iterable[Tuple[K, "SizedIterable[V]"]]:
merger = ExternalGroupBy[K, V](agg, memory, serializer) # type: ignore[arg-type]
merger.mergeCombiners(it)
return merger.items()

Expand Down
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