pyspark.sql.functions.timestamp_nanos#

pyspark.sql.functions.timestamp_nanos(col)[source]#

Creates a nanosecond-precision timestamp (TIMESTAMP_LTZ(9)) from the number of nanoseconds since the UTC epoch.

Added in version 4.3.0.

Parameters:

colColumn or column name: a column of BIGINT or DECIMAL nanosecond values since the UTC epoch. A column that evaluates to an integral or decimal.

Returns:

Column: a TIMESTAMP_LTZ(9) column representing the corresponding point in time. Returns a column that evaluates to a timestamp.

See also

pyspark.sql.functions.timestamp_seconds()
pyspark.sql.functions.timestamp_millis()
pyspark.sql.functions.timestamp_micros()
pyspark.sql.functions.unix_nanos()

Examples

>>> import pyspark.sql.functions as sf
>>> spark.conf.set("spark.sql.session.timeZone", "UTC")
>>> spark.conf.set("spark.sql.timestampNanosTypes.enabled", "true")
>>> df = spark.createDataFrame([(1577885075123456789,)], ['nanos'])
>>> df.select(sf.timestamp_nanos('nanos')).show(truncate=False)
+-----------------------------+
|timestamp_nanos(nanos)       |
+-----------------------------+
|2020-01-01 13:24:35.123456789|
+-----------------------------+

>>> df.select(sf.timestamp_nanos(sf.lit(None).cast('bigint'))).show()
+-------------------------------------+
|timestamp_nanos(CAST(NULL AS BIGINT))|
+-------------------------------------+
|                                 NULL|
+-------------------------------------+

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