Pyspark changing type of column from date to string

Question

I have the following dataframe:

corr_temp_df
[(\'vacationdate\', \'date\'),
 (\'valueE\', \'string\'),
 (\'valueD\', \'string\'),
 (\'valueC\', \'string\'),
         


        

Answer 1

Lets create some dummy data:

import datetime
from pyspark.sql import Row
from pyspark.sql.functions import col

row = Row("vacationdate")

df = sc.parallelize([
    row(datetime.date(2015, 10, 07)),
    row(datetime.date(1971, 01, 01))
]).toDF()

If you Spark >= 1.5.0 you can use date_format function:

from pyspark.sql.functions import date_format

(df
   .select(date_format(col("vacationdate"), "dd-MM-YYYY")
   .alias("date_string"))
   .show())

In Spark < 1.5.0 it can be done using Hive UDF:

df.registerTempTable("df")
sqlContext.sql(
    "SELECT date_format(vacationdate, 'dd-MM-YYYY') AS date_string FROM df")

It is of course still available in Spark >= 1.5.0.

If you don't use HiveContext you can mimic date_format using UDF:

from pyspark.sql.functions import udf, lit
my_date_format = udf(lambda d, fmt: d.strftime(fmt))

df.select(
    my_date_format(col("vacationdate"), lit("%d-%m-%Y")).alias("date_string")
).show()

Please note it is using C standard format not a Java simple date format