make_timestamp_ltz

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

Syntax

Python

from pyspark.databricks.sql import functions as dbf

dbf.make_timestamp_ltz(years=<years>, months=<months>, days=<days>, hours=<hours>, mins=<mins>, secs=<secs>, timezone=<timezone>)

Parameters

Parameter	Type	Description
years	pyspark.sql.Column or str	The year to represent, from 1 to 9999
months	pyspark.sql.Column or str	The month-of-year to represent, from 1 (January) to 12 (December)
days	pyspark.sql.Column or str	The day-of-month to represent, from 1 to 31
hours	pyspark.sql.Column or str	The hour-of-day to represent, from 0 to 23
mins	pyspark.sql.Column or str	The minute-of-hour to represent, from 0 to 59
secs	pyspark.sql.Column 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.
timezone	pyspark.sql.Column or str, optional	The time zone identifier. For example, CET, UTC and etc.

Returns

pyspark.sql.Column: A new column that contains a current timestamp.

Examples

Python

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

Python

from pyspark.databricks.sql import functions as dbf
df = spark.createDataFrame([[2014, 12, 28, 6, 30, 45.887, 'CET']],
['year', 'month', 'day', 'hour', 'min', 'sec', 'tz'])
df.select(
dbf.make_timestamp_ltz(df.year, df.month, 'day', df.hour, df.min, df.sec, 'tz')
).show(truncate=False)
df = spark.createDataFrame([[2014, 12, 28, 6, 30, 45.887, 'CET']],
['year', 'month', 'day', 'hour', 'min', 'sec', 'tz'])
df.select(
dbf.make_timestamp_ltz(df.year, df.month, 'day', df.hour, df.min, df.sec)
).show(truncate=False)
spark.conf.unset("spark.sql.session.timeZone")