How to extract year and week number from a columns in a sparkDataFrame?

[dshosseinyousef]

I have the following sparkdataframe :

sale_id/ created_at

1 /2016-05-28T05:53:31.042Z

2 /2016-05-30T12:50:58.184Z

3/ 2016-05-23T10:22:18.858Z

4 /2016-05-27T09:20:15.158Z

5 /2016-05-21T08:30:17.337Z

6 /2016-05-28T07:41:14.361Z

i need t add a year-week columns where it contains year and week number of each row in created_at column:

sale_id/ created_at /year_week

1 /2016-05-28T05:53:31.042Z /2016-21

2 /2016-05-30T12:50:58.184Z /2016-22

3/ 2016-05-23T10:22:18.858Z /2016-21

4 /2016-05-27T09:20:15.158Z /2016-21

5 /2016-05-21T08:30:17.337Z /2016-20

6 /2016-05-28T07:41:14.361Z /2016-21

Both pyspark pr SparkR or sparkSql are desirable, i have already tried lubridate package but as my columns are S4 i receive the follwing error:

Error in as.Date.default(head_df$created_at) :

Error in as.Date.default(head_df$created_at) : 
  do not know how to convert 'head_df$created_at' to class “Date”

[theodondre]

val data = spark.read.option("header","true").option("inferSchema","true").csv("location of file")

import spark.implicits._

//creates year column

val year = data.withColumn("Year",year(data("created_at")))

//creates weekof year column

val week = data.withColumn("Week",weekofyear(data("created_at")))

// concatenate year and week columns

val new_df = year + "-" +week

new_df.show()

//NOTE CODE IN SCALA. I DID NOT TEST THIS CODE ON IDE, BUT IT SHOULD WORK FINE.

[theodondre]

THIS IS HOW HE DOCUMENTATION LOOKS LIKE