pyspark.sql.functions.try_make_timestamp_ntz#

pyspark.sql.functions.try_make_timestamp_ntz(years, months, days, hours, mins, secs)[source]#

Try to create local date-time from years, months, days, hours, mins, secs fields. The function returns NULL on invalid inputs.

New in version 4.0.0.

Parameters

yearsColumn or column name: The year to represent, from 1 to 9999
monthsColumn or column name: The month-of-year to represent, from 1 (January) to 12 (December)
daysColumn or column name: The day-of-month to represent, from 1 to 31
hoursColumn or column name: The hour-of-day to represent, from 0 to 23
minsColumn or column name: The minute-of-hour to represent, from 0 to 59
secsColumn or column name: The second-of-minute and its micro-fraction to represent, from 0 to 60. The value can be either an integer like 13 , or a fraction like 13.123. If the sec argument equals to 60, the seconds field is set to 0 and 1 minute is added to the final timestamp.

Returns

Column: A new column that contains a local date-time, or NULL in case of an error.

See also

pyspark.sql.functions.make_timestamp()
pyspark.sql.functions.make_timestamp_ltz()
pyspark.sql.functions.make_timestamp_ntz()
pyspark.sql.functions.try_make_timestamp()
pyspark.sql.functions.try_make_timestamp_ltz()
pyspark.sql.functions.make_interval()
pyspark.sql.functions.try_make_interval()

Examples

>>> spark.conf.set("spark.sql.session.timeZone", "America/Los_Angeles")

Example 1: Make local date-time from years, months, days, hours, mins, secs.

>>> import pyspark.sql.functions as sf
>>> df = spark.createDataFrame([[2014, 12, 28, 6, 30, 45.887]],
...     ['year', 'month', 'day', 'hour', 'min', 'sec'])
>>> df.select(
...     sf.try_make_timestamp_ntz('year', 'month', df.day, df.hour, df.min, df.sec)
... ).show(truncate=False)
+--------------------------------------------------------+
|try_make_timestamp_ntz(year, month, day, hour, min, sec)|
+--------------------------------------------------------+
|2014-12-28 06:30:45.887                                 |
+--------------------------------------------------------+

Example 2: Make local date-time with invalid input

>>> import pyspark.sql.functions as sf
>>> df = spark.createDataFrame([[2014, 13, 28, 6, 30, 45.887]],
...     ['year', 'month', 'day', 'hour', 'min', 'sec'])
>>> df.select(
...     sf.try_make_timestamp_ntz('year', 'month', df.day, df.hour, df.min, df.sec)
... ).show(truncate=False)
+--------------------------------------------------------+
|try_make_timestamp_ntz(year, month, day, hour, min, sec)|
+--------------------------------------------------------+
|NULL                                                    |
+--------------------------------------------------------+

>>> spark.conf.unset("spark.sql.session.timeZone")