zero323 commented on a change in pull request #27278:
[SPARK-30569][SQL][PYSPARK][SPARKR] Add percentile_approx DSL functions.
URL: https://github.com/apache/spark/pull/27278#discussion_r368307650
##########
File path: python/pyspark/sql/tests/test_functions.py
##########
@@ -310,6 +310,31 @@ def test_input_file_name_udf(self):
file_name = df.collect()[0].file
self.assertTrue("python/test_support/hello/hello.txt" in file_name)
+ def test_percentile_approx(self):
+ from pyspark.sql.functions import col, percentile_approx
+ from itertools import chain
+ import re
+
+ actual =
list(chain.from_iterable([re.findall("(percentile_approx\(.*\))", str(x)) for x
in [
+ percentile_approx(col("foo"), 0.5),
+ percentile_approx(col("bar"), 0.25, 42),
+ percentile_approx(col("bar"), [0.25, 0.5, 0.75]),
+ percentile_approx(col("foo"), [0.05, 0.95], 100),
+ percentile_approx("foo", 0.5),
+ percentile_approx("bar", [0.1, 0.9], 10),
+ ]]))
+
+ expected = [
+ "percentile_approx(foo, 0.5, 10000)",
+ "percentile_approx(bar, 0.25, 42)",
+ "percentile_approx(bar, [0.25,0.5,0.75], 10000)",
+ "percentile_approx(foo, [0.05,0.95], 100)",
+ "percentile_approx(foo, 0.5, 10000)",
+ "percentile_approx(bar, [0.1,0.9], 10)"
+ ]
+
+ self.assertListEqual(actual, expected)
Review comment:
Same as in case of R we want to check if data is properly passed to JVM.
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