[jira] [Created] (ARROW-6704) [C++] Cast from timestamp to higher resolution does not check out of bounds timestamps

["Joris Van den Bossche (Jira)" <ji...@apache.org>]

Joris Van den Bossche created ARROW-6704:
--------------------------------------------

             Summary: [C++] Cast from timestamp to higher resolution does not check out of bounds timestamps
                 Key: ARROW-6704
                 URL: https://issues.apache.org/jira/browse/ARROW-6704
             Project: Apache Arrow
          Issue Type: Bug
          Components: C++
            Reporter: Joris Van den Bossche


When casting eg {{timestamp('s')}} to {{timestamp('ns')}}, we do not check for out of bounds timestamps, giving "garbage" timestamps in the result:

{code}
In [74]: a_np = np.array(["2012-01-01", "2412-01-01"], dtype="datetime64[s]")                                                                                                                                      

In [75]: arr = pa.array(a_np)                                                                                                                                                                                      

In [76]: arr                                                                                                                                                                                                       
Out[76]: 
<pyarrow.lib.TimestampArray object at 0x7f3d1f07cb88>
[
  2012-01-01 00:00:00,
  2412-01-01 00:00:00
]

In [77]: arr.cast(pa.timestamp('ns'))                                                                                                                                                                              
Out[77]: 
<pyarrow.lib.TimestampArray object at 0x7f3d1f07cfa8>
[
  2012-01-01 00:00:00.000000000,
  1827-06-13 00:25:26.290448384
]
{code}

Now, this is the same behaviour as numpy, so not sure we should do this. However, since we have a {{safe=True/False}}, I would expect that for {{safe=True}} we check this and for {{safe=False}} we do not check this.  
(numpy has a similiar {{casting='safe'}} but also does not raise an error in that case).




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