dtenedor commented on code in PR #42663:
URL: https://github.com/apache/spark/pull/42663#discussion_r1310564760
##########
python/pyspark/sql/tests/pandas/test_pandas_udf_grouped_agg.py:
##########
@@ -575,6 +575,128 @@ def mean(x):
assert filtered.collect()[0]["mean"] == 42.0
+ def test_named_arguments(self):
+ df = self.data
+ weighted_mean = self.pandas_agg_weighted_mean_udf
+
+ with self.tempView("v"):
+ df.createOrReplaceTempView("v")
+ self.spark.udf.register("weighted_mean", weighted_mean)
+
+ for i, aggregated in enumerate(
+ [
+ df.groupby("id").agg(weighted_mean(df.v,
w=df.w).alias("wm")),
+ df.groupby("id").agg(weighted_mean(v=df.v,
w=df.w).alias("wm")),
+ df.groupby("id").agg(weighted_mean(w=df.w,
v=df.v).alias("wm")),
+ self.spark.sql("SELECT id, weighted_mean(v, w => w) as wm
FROM v GROUP BY id"),
+ self.spark.sql(
+ "SELECT id, weighted_mean(v => v, w => w) as wm FROM v
GROUP BY id"
+ ),
+ self.spark.sql(
+ "SELECT id, weighted_mean(w => w, v => v) as wm FROM v
GROUP BY id"
+ ),
+ ]
+ ):
+ with self.subTest(query_no=i):
+ assertDataFrameEqual(aggregated,
df.groupby("id").agg(mean(df.v).alias("wm")))
+
+ def test_named_arguments_negative(self):
Review Comment:
can you please also port these negative tests to the 'kwargs' Pandas UDF
case as well? It would be good to make sure we do the same checks there. Same
for the window functions testing.
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