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- current_timestamp(fractional_precision)
- DESCRIPTION:
Function returns the current timestamp when the request started.
If function is invoked more than once during the request, the same timestamp is returned.
The timestamp returned does not change during the duration of the request.
The value returned depends on the setting of the DBS Control flag TimeDateWZControl as follows:
* If the TimeDateWZControl flag is enabled, function returns a timestamp constructed from
the session time and session time zone.
* If the TimeDateWZControl flag is disabled, function returns a timestamp constructed from
the time value local to the Vantage server and the session time zone.
PARAMETERS:
fractional_precision:
Optional Argument.
Specifies a precision range for the returned value. The valid range
is 0 through 6. The default is 0.
NOTE:
Function accepts positional arguments only.
EXAMPLES:
# Load the data to run the example.
>>> load_example_data("dataframe", "admissions_train")
>>>
# Create a DataFrame on 'admissions_train' table.
>>> admissions_train = DataFrame("admissions_train")
>>> admissions_train
masters gpa stats programming admitted
id
22 yes 3.46 Novice Beginner 0
36 no 3.00 Advanced Novice 0
15 yes 4.00 Advanced Advanced 1
38 yes 2.65 Advanced Beginner 1
5 no 3.44 Novice Novice 0
17 no 3.83 Advanced Advanced 1
34 yes 3.85 Advanced Beginner 0
13 no 4.00 Advanced Novice 1
26 yes 3.57 Advanced Advanced 1
19 yes 1.98 Advanced Advanced 0
>>>
# Import func from sqlalchemy to execute current_timestamp() function.
>>> from sqlalchemy import func
# Create a sqlalchemy Function object.
>>> current_timestamp_ = func.current_timestamp()
>>>
# Pass the Function object as input to DataFrame.assign().
>>> df = admissions_train.assign(current_timestamp_col=current_timestamp_)
>>> print(df)
masters gpa stats programming admitted current_timestamp_col
id
13 no 4.00 Advanced Novice 1 02:32:17+00:00
36 no 3.00 Advanced Novice 0 02:32:17+00:00
15 yes 4.00 Advanced Advanced 1 02:32:17+00:00
40 yes 3.95 Novice Beginner 0 02:32:17+00:00
22 yes 3.46 Novice Beginner 0 02:32:17+00:00
38 yes 2.65 Advanced Beginner 1 02:32:17+00:00
26 yes 3.57 Advanced Advanced 1 02:32:17+00:00
5 no 3.44 Novice Novice 0 02:32:17+00:00
7 yes 2.33 Novice Novice 1 02:32:17+00:00
19 yes 1.98 Advanced Advanced 0 02:32:17+00:00
>>>
# Get current timestamp value with fractional precision set to 6.
>>> df = admissions_train.assign(current_timestamp_col=func.current_timestamp(6))
>>> print(df)
masters gpa stats programming admitted current_timestamp_col
id
5 no 3.44 Novice Novice 0 2020-07-28 02:55:07.140000+00:00
34 yes 3.85 Advanced Beginner 0 2020-07-28 02:55:07.140000+00:00
13 no 4.00 Advanced Novice 1 2020-07-28 02:55:07.140000+00:00
40 yes 3.95 Novice Beginner 0 2020-07-28 02:55:07.140000+00:00
22 yes 3.46 Novice Beginner 0 2020-07-28 02:55:07.140000+00:00
19 yes 1.98 Advanced Advanced 0 2020-07-28 02:55:07.140000+00:00
36 no 3.00 Advanced Novice 0 2020-07-28 02:55:07.140000+00:00
15 yes 4.00 Advanced Advanced 1 2020-07-28 02:55:07.140000+00:00
7 yes 2.33 Novice Novice 1 2020-07-28 02:55:07.140000+00:00
17 no 3.83 Advanced Advanced 1 2020-07-28 02:55:07.140000+00:00
>>>
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