grundprinzip commented on code in PR #38946:
URL: https://github.com/apache/spark/pull/38946#discussion_r1044356233
##########
python/pyspark/sql/tests/connect/test_connect_function.py:
##########
@@ -645,6 +645,153 @@ def test_string_functions(self):
sdf.select(SF.encode("c", "UTF-8")).toPandas(),
)
+ # TODO(SPARK-41283): To compare toPandas for test cases with dtypes marked
+ def test_date_ts_functions(self):
+ from pyspark.sql import functions as SF
+ from pyspark.sql.connect import functions as CF
+
+ query = """
+ SELECT * FROM VALUES
+ ('1997/02/28 10:30:00', '2023/03/01 06:00:00', 'JST', 1428476400,
2020, 12, 6),
+ ('2000/01/01 04:30:05', '2020/05/01 12:15:00', 'PST', 1403892395,
2022, 12, 6)
+ AS tab(ts1, ts2, tz, seconds, Y, M, D)
+ """
+ # +-------------------+-------------------+---+----------+----+---+---+
+ # | ts1| ts2| tz| seconds| Y| M| D|
+ # +-------------------+-------------------+---+----------+----+---+---+
+ # |1997/02/28 10:30:00|2023/03/01 06:00:00|JST|1428476400|2020| 12| 6|
+ # |2000/01/01 04:30:05|2020/05/01 12:15:00|PST|1403892395|2022| 12| 6|
+ # +-------------------+-------------------+---+----------+----+---+---+
+
+ cdf = self.connect.sql(query)
+ sdf = self.spark.sql(query)
+
+ # With no parameters
+ for cfunc, sfunc in [
+ (CF.current_date, SF.current_date),
+ ]:
+ self.assert_eq(
+ cdf.select(cfunc()).toPandas(),
+ sdf.select(sfunc()).toPandas(),
+ )
+
+ # current_timestamp
+ # [left]: datetime64[ns, America/Los_Angeles]
+ # [right]: datetime64[ns]
+ plan = cdf.select(CF.current_timestamp())._plan.to_proto(self.connect)
+ self.assertEqual(
+ plan.root.project.expressions.unresolved_function.function_name,
"current_timestamp"
Review Comment:
you could do something along the lines that you call first spark, then
connect then spark again and make sure that connect is in the middle between
all values and that the second spark one is after the first one.
##########
python/pyspark/sql/tests/connect/test_connect_function.py:
##########
@@ -645,6 +645,153 @@ def test_string_functions(self):
sdf.select(SF.encode("c", "UTF-8")).toPandas(),
)
+ # TODO(SPARK-41283): To compare toPandas for test cases with dtypes marked
+ def test_date_ts_functions(self):
+ from pyspark.sql import functions as SF
+ from pyspark.sql.connect import functions as CF
+
+ query = """
+ SELECT * FROM VALUES
+ ('1997/02/28 10:30:00', '2023/03/01 06:00:00', 'JST', 1428476400,
2020, 12, 6),
+ ('2000/01/01 04:30:05', '2020/05/01 12:15:00', 'PST', 1403892395,
2022, 12, 6)
+ AS tab(ts1, ts2, tz, seconds, Y, M, D)
+ """
+ # +-------------------+-------------------+---+----------+----+---+---+
+ # | ts1| ts2| tz| seconds| Y| M| D|
+ # +-------------------+-------------------+---+----------+----+---+---+
+ # |1997/02/28 10:30:00|2023/03/01 06:00:00|JST|1428476400|2020| 12| 6|
+ # |2000/01/01 04:30:05|2020/05/01 12:15:00|PST|1403892395|2022| 12| 6|
+ # +-------------------+-------------------+---+----------+----+---+---+
+
+ cdf = self.connect.sql(query)
+ sdf = self.spark.sql(query)
+
+ # With no parameters
+ for cfunc, sfunc in [
+ (CF.current_date, SF.current_date),
+ ]:
+ self.assert_eq(
+ cdf.select(cfunc()).toPandas(),
+ sdf.select(sfunc()).toPandas(),
+ )
+
+ # current_timestamp
+ # [left]: datetime64[ns, America/Los_Angeles]
+ # [right]: datetime64[ns]
+ plan = cdf.select(CF.current_timestamp())._plan.to_proto(self.connect)
+ self.assertEqual(
+ plan.root.project.expressions.unresolved_function.function_name,
"current_timestamp"
+ )
+
+ # localtimestamp
+ plan = cdf.select(CF.localtimestamp())._plan.to_proto(self.connect)
+ self.assertEqual(
+ plan.root.project.expressions.unresolved_function.function_name,
"localtimestamp"
Review Comment:
see above
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