sadhen commented on a change in pull request #32026:
URL: https://github.com/apache/spark/pull/32026#discussion_r606075743
##########
File path: python/pyspark/sql/tests/test_arrow.py
##########
@@ -196,6 +197,33 @@ def test_pandas_round_trip(self):
pdf_arrow = df.toPandas()
assert_frame_equal(pdf_arrow, pdf)
+ def test_udt_roundtrip(self):
+ pdf = pd.DataFrame({'point': pd.Series([ExamplePoint(1.0, 1.0),
ExamplePoint(2.0, 2.0)])})
+ schema = StructType([StructField('point', ExamplePointUDT(), False)])
+ with
self.sql_conf({"spark.sql.execution.arrow.pyspark.fallback.enabled": True}):
+ df = self.spark.createDataFrame(pdf, schema)
+ pdf_arrow = df.toPandas()
+ assert_frame_equal(pdf_arrow, pdf)
+ with
self.sql_conf({"spark.sql.execution.arrow.pyspark.fallback.enabled": False}):
+ df = self.spark.createDataFrame(pdf, schema)
+ pdf_arrow = df.toPandas()
+ assert_frame_equal(pdf_arrow, pdf)
+
+ def test_array_udt_roundtrip(self):
+ pdf = pd.DataFrame({'points': pd.Series([
+ [ExamplePoint(1.0, 1.0), ExamplePoint(1.0, 2.0), ExamplePoint(1.0,
3.0)],
Review comment:
For primitive data type, it is not a good practice to wrap it in UDT. As
a result, I do not think we should spend too much time on support UDT which is
actually primitive data type. This part can be postponed.
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