[GitHub] [spark] HyukjinKwon commented on a diff in pull request #39262: [SPARK-41069][CONNECT][PYTHON] Implement `DataFrame.approxQuantile` and `DataFrame.stat.approxQuantile`

[GitBox <gi...@apache.org>]

HyukjinKwon commented on code in PR #39262:
URL: https://github.com/apache/spark/pull/39262#discussion_r1058894403


##########
python/pyspark/sql/tests/connect/test_connect_basic.py:
##########
@@ -1013,6 +1013,42 @@ def test_stat_cov(self):
             self.spark.read.table(self.tbl_name2).stat.cov("col1", "col3"),
         )
 
+    def test_stat_approx_quantile(self):
+        # SPARK-41069: Test the stat.approxQuantile method
+        result = self.connect.read.table(self.tbl_name2).stat.approxQuantile(
+            ["col1", "col3"], [0.1, 0.5, 0.9], 0.1
+        )
+        self.assertEqual(len(result), 2)
+        self.assertEqual(len(result[0]), 3)
+        self.assertEqual(len(result[1]), 3)
+
+        with self.assertRaisesRegex(
+            TypeError, "col should be a string, list or tuple, but got <class 'int'>"
+        ):
+            self.connect.read.table(self.tbl_name2).stat.approxQuantile(1, [0.1, 0.5, 0.9], 0.1)
+        with self.assertRaisesRegex(TypeError, "columns should be strings, but got <class 'int'>"):
+            self.connect.read.table(self.tbl_name2).stat.approxQuantile([1], [0.1, 0.5, 0.9], 0.1)
+        with self.assertRaisesRegex(TypeError, "probabilities should be a list or tuple"):
+            self.connect.read.table(self.tbl_name2).stat.approxQuantile(["col1", "col3"], 0.1, 0.1)
+        with self.assertRaises(ValueError) as context:

Review Comment:
   hm, I think `assertRaisesRegex` is better since you;re doing `"probabilities should be numerical (float, int) in [0,1]" in str(context.exception)`? Using regex would be shorter at least.



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