How to add a current timestamp column to pyspark DataFrame

The current timestamp can be added as a new column to spark Dataframe using the current_timestamp() function of the sql module in pyspark.

The method returns the timestamp in the yyyy-mm-dd hh:mm:ss. nnn format.

Syntax

pyspark.sql.functions.current_timestamp()

Parameters

This method has no parameters.

Return value

This method returns the current timestamp.

Code example

Let’s see the code below:

import pyspark
from pyspark.sql import SparkSession
from pyspark.sql.functions import current_timestamp
spark = SparkSession.builder.appName('edpresso').getOrCreate()
data = [("James","Smith","USA","CA"),
    ("Michael","Rose","USA","NY"),
    ("Robert","Williams","USA","CA"),
    ("Maria","Jones","USA","FL")
  ]
columns = ["firstname","lastname","country","state"]
df = spark.createDataFrame(data = data, schema = columns)
df_with_ts = df.withColumn("curr_timestamp", current_timestamp())
df_with_ts.show(truncate=False)

Code explanation

Line 4: A spark session with the app’s Educative Answers is created.
Lines 6–10: We define data for the DataFrame.
Line 12: We define the columns of the DataFrame.
Line 13: We create a DataFrame using the createDataframe() method.
Line 15: We add a new column to the data frame using the withColumn() method passing the new column name curr_timestamp and the value to assign to the column the timestamp value returned by the method current_timestamp().
Line 17: We print the DataFrame.

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