Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/20588#discussion_r167631828
--- Diff: python/pyspark/sql/tests.py ---
@@ -4325,15 +4333,16 @@ def data(self):
.withColumn("vs", array([lit(i) for i in range(20, 30)])) \
.withColumn("v", explode(col('vs'))).drop('vs')
- def test_simple(self):
- from pyspark.sql.functions import pandas_udf, PandasUDFType
- df = self.data
+ def test_supported_types(self):
--- End diff --
I start to worry about the test coverage of vectorized udfs and arrow-based
to/from pandas df. Do we have any plan in PySpark to test all the data types?
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