Details
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Bug
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Status: Open
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Major
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Resolution: Unresolved
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2.0.0
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None
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None
Description
Dates before 1538 (julian/gregorian calendar transition) are processed incorrectly.
- With python udf (datetime.strptime), .show() returns wrong dates but .collect() returns correct dates
- With pyspark.sql.functions.to_date, .show() shows correct dates but .collect() returns wrong dates. Additionally, collecting '0001-01-01' returns error when collecting dataframe.
from pyspark.sql.types import DateType
from pyspark.sql.functions import to_date, udf
from datetime import datetime
strToDate = udf (lambda x: datetime.strptime(x, '%Y-%m-%d'), DateType())
l = [('0002-01-01', 1), ('1581-01-01', 2), ('1582-01-01', 3), ('1583-01-01', 4), ('1584-01-01', 5), ('2012-01-21', 6)]
l_older = [('0001-01-01', 1)]
test_df = spark.createDataFrame(l, ["date_string", "number"])
test_df_older = spark.createDataFrame(l_older, ["date_string", "number"])
test_df_strptime = test_df.withColumn( "date_cast", strToDate(test_df["date_string"]))
test_df_todate = test_df.withColumn( "date_cast", to_date(test_df["date_string"]))
test_df_older_todate = test_df_older.withColumn( "date_cast", to_date(test_df_older["date_string"]))
test_df_strptime.show()
test_df_todate.show()
print test_df_strptime.collect()
print test_df_todate.collect()
print test_df_older_todate.collect()
+-----------+------+----------+
|date_string|number| date_cast|
+-----------+------+----------+
| 0002-01-01| 1|0002-01-03|
| 1581-01-01| 2|1580-12-22|
| 1582-01-01| 3|1581-12-22|
| 1583-01-01| 4|1583-01-01|
| 1584-01-01| 5|1584-01-01|
| 2012-01-21| 6|2012-01-21|
+-----------+------+----------+
+-----------+------+----------+
|date_string|number| date_cast|
+-----------+------+----------+
| 0002-01-01| 1|0002-01-01|
| 1581-01-01| 2|1581-01-01|
| 1582-01-01| 3|1582-01-01|
| 1583-01-01| 4|1583-01-01|
| 1584-01-01| 5|1584-01-01|
| 2012-01-21| 6|2012-01-21|
+-----------+------+----------+
[Row(date_string=u'0002-01-01', number=1, date_cast=datetime.date(2, 1, 1)), Row(date_string=u'1581-01-01', number=2, date_cast=datetime.date(1581, 1, 1)), Row(date_string=u'1582-01-01', number=3, date_cast=datetime.date(1582, 1, 1)), Row(date_string=u'1583-01-01', number=4, date_cast=datetime.date(1583, 1, 1)), Row(date_string=u'1584-01-01', number=5, date_cast=datetime.date(1584, 1, 1)), Row(date_string=u'2012-01-21', number=6, date_cast=datetime.date(2012, 1, 21))]
[Row(date_string=u'0002-01-01', number=1, date_cast=datetime.date(1, 12, 30)), Row(date_string=u'1581-01-01', number=2, date_cast=datetime.date(1581, 1, 11)), Row(date_string=u'1582-01-01', number=3, date_cast=datetime.date(1582, 1, 11)), Row(date_string=u'1583-01-01', number=4, date_cast=datetime.date(1583, 1, 1)), Row(date_string=u'1584-01-01', number=5, date_cast=datetime.date(1584, 1, 1)), Row(date_string=u'2012-01-21', number=6, date_cast=datetime.date(2012, 1, 21))]
Traceback (most recent call last):
File "/tmp/zeppelin_pyspark-6043517212596195478.py", line 267, in <module>
raise Exception(traceback.format_exc())
Exception: Traceback (most recent call last):
File "/tmp/zeppelin_pyspark-6043517212596195478.py", line 265, in <module>
exec(code)
File "<stdin>", line 15, in <module>
File "/usr/local/spark/python/pyspark/sql/dataframe.py", line 311, in collect
return list(_load_from_socket(port, BatchedSerializer(PickleSerializer())))
File "/usr/local/spark/python/pyspark/rdd.py", line 142, in _load_from_socket
for item in serializer.load_stream(rf):
File "/usr/local/spark/python/pyspark/serializers.py", line 139, in load_stream
yield self._read_with_length(stream)
File "/usr/local/spark/python/pyspark/serializers.py", line 164, in _read_with_length
return self.loads(obj)
File "/usr/local/spark/python/pyspark/serializers.py", line 422, in loads
return pickle.loads(obj)
File "/usr/local/spark/python/pyspark/sql/types.py", line 1354, in <lambda>
return lambda *a: dataType.fromInternal(a)
File "/usr/local/spark/python/pyspark/sql/types.py", line 600, in fromInternal
values = [f.fromInternal(v) for f, v in zip(self.fields, obj)]
File "/usr/local/spark/python/pyspark/sql/types.py", line 439, in fromInternal
return self.dataType.fromInternal(obj)
File "/usr/local/spark/python/pyspark/sql/types.py", line 176, in fromInternal
return datetime.date.fromordinal(v + self.EPOCH_ORDINAL)
ValueError: ('ordinal must be >= 1', <function <lambda> at 0x7fa21bf7baa0>, (u'0001-01-01', 1, -719164))
Attachments
Issue Links
- is related to
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SPARK-26651 Use Proleptic Gregorian calendar
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- Resolved
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