Assuming you are using Python in glue, and assuming python understands your field as a date, you could do something like:
from pyspark.sql.functions import date_format
from awsglue.dynamicframe import DynamicFrame
from awsglue.context import GlueContext
def out_date_format(to_format):
"""formats the passed date into MM/dd/yyyy format"""
return date_format(to_format,"MM/dd/yyyy")
#if you have a dynamic frame you will need to convert it to a dataframe first:
#dataframe = dynamic_frame.toDF()
dataframe.withColumn("new_column_name", out_date_format("your_old_date_column_name"))
#assuming you are outputting via glue, you will need to convert the dataframe back into a dynamic frame:
#glue_context = GlueContext(spark_context)
#final = DynamicFrame.fromDF(dataframe, glue_context,"final")
Depending on how you are getting the data, there may be other options to use mapping or formatting.
If python doesn't understand your field as a date object, you will need to parse it first, something like:
import dateutil.parser
#and the convert would change to:
def out_date_format(to_format):
"""formats the passed date into MM/dd/yyyy format"""
yourdate = dateutil.parser.parse(to_format)
return date_format(yourdate,"MM/dd/yyyy")
Note that if the dateutil isn't built into glue, you will need to add it to your job parameters with syntax like:
"--additional-python-modules" = "python-dateutil==2.8.1"