zhengruifeng commented on code in PR #53317:
URL: https://github.com/apache/spark/pull/53317#discussion_r2600639778
##########
python/pyspark/sql/tests/pandas/test_pandas_udf_grouped_agg.py:
##########
@@ -897,6 +897,146 @@ def sum_udf(v):
)
assert_frame_equal(expected, result)
+ def test_iterator_grouped_agg_basic(self):
+ """
+ Test basic functionality of iterator grouped agg pandas UDF with
Iterator[pd.Series].
+ """
+ df = self.spark.createDataFrame(
+ [(1, 1.0), (1, 2.0), (2, 3.0), (2, 5.0), (2, 10.0)], ("id", "v")
+ )
+
+ @pandas_udf("double")
+ def pandas_mean_iter(it: Iterator[pd.Series]) -> float:
+ sum_val = 0.0
+ cnt = 0
+ for series in it:
+ assert isinstance(series, pd.Series)
+ sum_val += series.sum()
+ cnt += len(series)
+ return sum_val / cnt if cnt > 0 else 0.0
+
+ result =
df.groupby("id").agg(pandas_mean_iter(df["v"]).alias("mean")).sort("id").collect()
+
+ # Expected means:
+ # Group 1: (1.0 + 2.0) / 2 = 1.5
+ # Group 2: (3.0 + 5.0 + 10.0) / 3 = 6.0
+ expected = [Row(id=1, mean=1.5), Row(id=2, mean=6.0)]
+ self.assertEqual(result, expected)
+
+ def test_iterator_grouped_agg_multiple_columns(self):
+ """
+ Test iterator grouped agg pandas UDF with multiple columns
+ using Iterator[Tuple[pd.Series, ...]].
+ """
+ df = self.spark.createDataFrame(
+ [(1, 1.0, 1.0), (1, 2.0, 2.0), (2, 3.0, 1.0), (2, 5.0, 2.0), (2,
10.0, 3.0)],
+ ("id", "v", "w"),
+ )
+
+ @pandas_udf("double")
+ def pandas_weighted_mean_iter(it: Iterator[Tuple[pd.Series,
pd.Series]]) -> float:
+ import numpy as np
+
+ weighted_sum = 0.0
+ weight = 0.0
+ for v_series, w_series in it:
+ assert isinstance(v_series, pd.Series)
+ assert isinstance(w_series, pd.Series)
+ weighted_sum += np.dot(v_series, w_series)
+ weight += w_series.sum()
+ return weighted_sum / weight if weight > 0 else 0.0
+
+ result = (
+ df.groupby("id")
+ .agg(pandas_weighted_mean_iter(df["v"], df["w"]).alias("wm"))
+ .sort("id")
+ .collect()
+ )
+
+ # Expected weighted means:
+ # Group 1: (1.0*1.0 + 2.0*2.0) / (1.0 + 2.0) = 5.0 / 3.0
+ # Group 2: (3.0*1.0 + 5.0*2.0 + 10.0*3.0) / (1.0 + 2.0 + 3.0) = 43.0 /
6.0
Review Comment:
are you still assuming the ordering with a group?
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