(spark) branch master updated: [SPARK-46385][PYTHON][TESTS] Test aggregate functions for groups (pyspark.sql.group)

[gurwls223]

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The following commit(s) were added to refs/heads/master by this push:
     new 79f61985c8de [SPARK-46385][PYTHON][TESTS] Test aggregate functions for 
groups (pyspark.sql.group)
79f61985c8de is described below

commit 79f61985c8de6c1be5f82c79c50f2b7aa7b46f67
Author: Xinrong Meng <xinr...@apache.org>
AuthorDate: Wed Dec 13 12:23:31 2023 -0800

    [SPARK-46385][PYTHON][TESTS] Test aggregate functions for groups 
(pyspark.sql.group)
    
    ### What changes were proposed in this pull request?
    Test aggregate functions for groups (pyspark.sql.group)
    
    ### Why are the changes needed?
    Subtasks of 
[SPARK-46041](https://issues.apache.org/jira/browse/SPARK-46041) to improve 
test coverage
    
    ### Does this PR introduce _any_ user-facing change?
    No.
    
    ### How was this patch tested?
    Test change only.
    
    ### Was this patch authored or co-authored using generative AI tooling?
    No.
    
    Closes #44322 from xinrong-meng/test_group.
    
    Authored-by: Xinrong Meng <xinr...@apache.org>
    Signed-off-by: Hyukjin Kwon <gurwls...@apache.org>
---
 python/pyspark/sql/tests/test_group.py | 23 +++++++++++++++++++++++
 1 file changed, 23 insertions(+)

diff --git a/python/pyspark/sql/tests/test_group.py 
b/python/pyspark/sql/tests/test_group.py
index 6981601cb129..6c84bd740171 100644
--- a/python/pyspark/sql/tests/test_group.py
+++ b/python/pyspark/sql/tests/test_group.py
@@ -22,6 +22,29 @@ from pyspark.testing import assertDataFrameEqual, 
assertSchemaEqual
 
 
 class GroupTestsMixin:
+    def test_agg_func(self):
+        data = [Row(key=1, value=10), Row(key=1, value=20), Row(key=1, 
value=30)]
+        df = self.spark.createDataFrame(data)
+        g = df.groupBy("key")
+        self.assertEqual(g.max("value").collect(), [Row(**{"key": 1, 
"max(value)": 30})])
+        self.assertEqual(g.min("value").collect(), [Row(**{"key": 1, 
"min(value)": 10})])
+        self.assertEqual(g.sum("value").collect(), [Row(**{"key": 1, 
"sum(value)": 60})])
+        self.assertEqual(g.count().collect(), [Row(key=1, count=3)])
+        self.assertEqual(g.mean("value").collect(), [Row(**{"key": 1, 
"avg(value)": 20.0})])
+
+        data = [
+            Row(electronic="Smartphone", year=2018, sales=150000),
+            Row(electronic="Tablet", year=2018, sales=120000),
+            Row(electronic="Smartphone", year=2019, sales=180000),
+            Row(electronic="Tablet", year=2019, sales=50000),
+        ]
+
+        df_pivot = self.spark.createDataFrame(data)
+        assertDataFrameEqual(
+            df_pivot.groupBy("year").pivot("electronic", ["Smartphone", 
"Tablet"]).sum("sales"),
+            df_pivot.groupBy("year").pivot("electronic").sum("sales"),
+        )
+
     def test_aggregator(self):
         df = self.df
         g = df.groupBy()


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