dtenedor commented on code in PR #42663:
URL: https://github.com/apache/spark/pull/42663#discussion_r1310566256
##########
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):
+ 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)
+
+ with self.assertRaisesRegex(
+ AnalysisException,
+
"DUPLICATE_ROUTINE_PARAMETER_ASSIGNMENT.DOUBLE_NAMED_ARGUMENT_REFERENCE",
+ ):
+ self.spark.sql(
+ "SELECT id, weighted_mean(v => v, v => w) as wm FROM v
GROUP BY id"
Review Comment:
thanks for this test! In addition could we add a negative test case where we
provide a positional argument matching the first parameter of the function,
then a named argument with the same name as that first parameter? It should
return an error in that case. Same for the window functions testing.
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