Cudf: [BUG] to_timestamps not handling format correctly when there is a truncated string
Describe the bug
We use to_timestamps to convert a string into a datetime column. This is primarily done incase of type-casting a string column to datetime column. In this case we try to infer format from first row and pass the format to to_timestamps api. It appears to be that when %.9f exists the corresponding value is not being inferred correctly.
Steps/Code to reproduce bug
>>> import cudf
>>> s = cudf.Series([ "1970-01-01 00:00:00.000001", "1970-01-01 00:00:00.000001000"])
>>> s
0 1970-01-01 00:00:00.000001
1 1970-01-01 00:00:00.000001000
dtype: object
# CORRECT CASE
>>> s.astype('datetime64[ns]')
# Inferred Format from 1st Value is: %Y-%m-%d %H:%M:%S.%f
0 1970-01-01 00:00:00.000001
1 1970-01-01 00:00:00.000001
dtype: datetime64[ns]
>>> s.to_pandas().astype('datetime64[ns]')
0 1970-01-01 00:00:00.000001
1 1970-01-01 00:00:00.000001
dtype: datetime64[ns]
# INCORRECT CASE - When the inferred format has %9f
>>> s = cudf.Series(["1970-01-01 00:00:00.000001000", "1970-01-01 00:00:00.000001"])
>>> s
0 1970-01-01 00:00:00.000001000
1 1970-01-01 00:00:00.000001
dtype: object
>>> s.astype('datetime64[ns]')
# Inferred Format from 1st Value is: %Y-%m-%d %H:%M:%S.%9f
0 1970-01-01 00:00:00.000001000
1 1970-01-01 00:00:00.000000001 # <- Incorrect inference
dtype: datetime64[ns]
>>> s.to_pandas().astype('datetime64[ns]')
0 1970-01-01 00:00:00.000001
1 1970-01-01 00:00:00.000001
dtype: datetime64[ns]
Expected behavior
The expected behavior is the result should be:
>>> s = cudf.Series(["1970-01-01 00:00:00.000001000", "1970-01-01 00:00:00.000001"])
>>> s
0 1970-01-01 00:00:00.000001000
1 1970-01-01 00:00:00.000001
dtype: object
>>> s.astype('datetime64[ns]')
0 1970-01-01 00:00:00.000001000
1 1970-01-01 00:00:00.000001000
dtype: datetime64[ns]
Environment overview (please complete the following information)
- Environment location: Bare-metal
- Method of cuDF install: from source
Environment details
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**git***
commit b3c642f6e5fa15d5f422d82ad1c79acd7bee436d (HEAD -> 1892, origin/1892)
Author: galipremsagar <[email protected]>
Date: Sun Sep 13 03:50:17 2020 -0700
adapt changed signatures
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galipremsagar
All 6 comments
The data must always match the format.
The format tells the code how many characters are required for each specifier. The %9f requires 9 characters for the fractional-second field. It is not expected that the data from each row have a different format. For example, if the format was the following "%H%M%S%9f%j" this would require the data to be like "121100123456001" (Jan 1 12:11:00.123456). There is data after the %9f so if the data appear as follows "121100123001" then there is no way to know that 123 is the fractional second part that is truncated.
If you know there is nothing after the last field, then you could provide a %#f for the row with the least number of digits for fractional seconds.
davidwendt
on 16 Sep 2020
Okay, understood. THen this is the limitation due to guessing date-format based on first string only.
@kkraus14 Should we have a warning when this kind of type-cast occurs? or should we infer the # value for %#f based on all values in the string column?
an example case where this could be a problem:
>>> s = cudf.Series([ "1970-01-01 00:00:00.000001", "1970-01-01 00:00:00.000001000"])
>>> s = cudf.Series([ "1970-01-01 00:00:00.000001", "1970-01-01 00:00:00.000001234"])
>>> s.astype('datetime64[ns]')
0 1970-01-01 00:00:00.000001
1 1970-01-01 00:00:00.000001
dtype: datetime64[ns]
>>> s.to_pandas().astype('datetime64[ns]')
0 1970-01-01 00:00:00.000001000
1 1970-01-01 00:00:00.000001234
dtype: datetime64[ns]
@galipremsagar I just tried modifying the libcudf code to account for the end-of-string case for the fractional specifier. So looks like this can be fixed for this case. But supporting variable length decimals for fractions would still not work if the %f specifier is not at the end.
davidwendt
on 17 Sep 2020
🎉1
Most of the generic cases would %f at the end from python end.
But supporting variable length decimals for fractions would still not work if the %f specifier is not at the end.
I think that should be fine and expected as this case would arise only when the user hits cudf.to_datetime API where the user is responsible for specifying the correct format specifier.
galipremsagar
on 17 Sep 2020
Ok. I will create a PR with the change today.
davidwendt
on 17 Sep 2020
The reason we're only inferring from the first element is to avoid the cost of slower CPU inference. If we had a GPU function that returned the format that should be used it would be ideal to handle situations where we get mixed strings like: [ "1970-01-01 00:00:00.000001", "1970-01-01 00:00:00.000001000"]
kkraus14
on 17 Sep 2020
👍1
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