pyspark.sql.functions.make_timestamp_ntz¶

pyspark.sql.functions.make_timestamp_ntz(years: ColumnOrName, months: ColumnOrName, days: ColumnOrName, hours: ColumnOrName, mins: ColumnOrName, secs: ColumnOrName) → pyspark.sql.column.Column[source]¶

Create local date-time from years, months, days, hours, mins, secs fields. If the configuration spark.sql.ansi.enabled is false, the function returns NULL on invalid inputs. Otherwise, it will throw an error instead.

New in version 3.5.0.

Parameters

yearsColumn or str: the year to represent, from 1 to 9999
monthsColumn or str: the month-of-year to represent, from 1 (January) to 12 (December)
daysColumn or str: the day-of-month to represent, from 1 to 31
hoursColumn or str: the hour-of-day to represent, from 0 to 23
minsColumn or str: the minute-of-hour to represent, from 0 to 59
secsColumn or str: 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.

Examples

>>> import pyspark.sql.functions as sf
>>> spark.conf.set("spark.sql.session.timeZone", "America/Los_Angeles")
>>> df = spark.createDataFrame([[2014, 12, 28, 6, 30, 45.887]],
...     ["year", "month", "day", "hour", "min", "sec"])
>>> df.select(sf.make_timestamp_ntz(
...     df.year, df.month, df.day, df.hour, df.min, df.sec)
... ).show(truncate=False)
+----------------------------------------------------+
|make_timestamp_ntz(year, month, day, hour, min, sec)|
+----------------------------------------------------+
|2014-12-28 06:30:45.887                             |
+----------------------------------------------------+
>>> spark.conf.unset("spark.sql.session.timeZone")

pyspark.sql.functions.make_timestamp_ltz

pyspark.sql.functions.make_ym_interval