Using PySpark,
I've got a string which looks like:
+-------------------------+
|2022-12-07050641 |
+-------------------------+
But need it to be in this format:
+-------------------------+
|2022-11-11 08:48:00.707 |
+-------------------------+
It seems that the to_timestamp()
function requires the formatting to be in the format of a timestamp.
I've been trying to use the to_timestamp()
function to convert the string to timestamp but the value then returns nulls. I figured its because of the format of the value (2022-12-07050641). How can I use regex to fix my value to be as the desired value?
To use the to_timestamp function in PySpark to convert the string '2022-12-07050641' to a timestamp, you can use a regular expression to extract the date and time parts of the string, and then use the to_timestamp function to convert them to a timestamp.
import re
from pyspark.sql.functions import to_timestamp, regexp_extract
# Define the regular expression pattern to extract the date and time parts
pattern = r'(\d{4}-\d{2}-\d{2})(\d{6})'
# Extract the date and time parts using the regular expression
df = df.withColumn('date', regexp_extract('string_column', pattern, 1))
df = df.withColumn('time', regexp_extract('string_column', pattern, 2))
# Convert the date and time parts to a timestamp
df = df.withColumn('timestamp', to_timestamp(df['date'] + ' ' + df['time'], 'yyyy-MM-dd HHmmss'))
# Drop the date and time columns
df = df.drop('date').drop('time')
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