Bryan Cutler created SPARK-22417:
------------------------------------
Summary: createDataFrame from a pandas.DataFrame reads datetime64
values as longs
Key: SPARK-22417
URL: https://issues.apache.org/jira/browse/SPARK-22417
Project: Spark
Issue Type: Bug
Components: PySpark
Affects Versions: 2.2.0
Reporter: Bryan Cutler
Priority: Normal
When trying to create a Spark DataFrame from an existing Pandas DataFrame using
{{createDataFrame}}, columns with datetime64 values are converted as long
values. This is only when the schema is not specified.
{code}
In [2]: import pandas as pd
...: from datetime import datetime
...:
In [3]: pdf = pd.DataFrame({"ts": [datetime(2017, 10, 31, 1, 1, 1)]})
In [4]: df = spark.createDataFrame(pdf)
In [5]: df.show()
+-------------------+
| ts|
+-------------------+
|1509411661000000000|
+-------------------+
In [6]: df.schema
Out[6]: StructType(List(StructField(ts,LongType,true)))
{code}
Spark should interpret a datetime64\[D\] value to DateType and other datetime64
values to TImestampType.
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