how to update all the values of a column in a dataFrame - scala

Question

I have a data frame which has a non formated Date column :
+--------+-----------+--------+
|CDOPEINT| bbbbbbbbbb| Date|
+--------+-----------+--------+
| AAA|bbbbbbbbbbb|13190326|
| AAA|bbbbbbbbbbb|10190309|
| AAA|bbbbbbbbbbb|36190908|
| AAA|bbbbbbbbbbb|07190214|
| AAA|bbbbbbbbbbb|13190328|
| AAA|bbbbbbbbbbb|23190608|
| AAA|bbbbbbbbbbb|13190330|
| AAA|bbbbbbbbbbb|26190630|
+--------+-----------+--------+
the date column is formated as : wwyyMMdd (week, year, month, day) which I want to format to YYYYMMdd, for that a have a method : format that do that.
so my question is how could I map all the values of column Date to the needed format? here is the output that I want :
+--------+-----------+----------+
|CDOPEINT| bbbbbbbbbb| Date|
+--------+-----------+----------+
| AAA|bbbbbbbbbbb|2019/03/26|
| AAA|bbbbbbbbbbb|2019/03/09|
| AAA|bbbbbbbbbbb|2019/09/08|
| AAA|bbbbbbbbbbb|2019/02/14|
| AAA|bbbbbbbbbbb|2019/03/28|
| AAA|bbbbbbbbbbb|2019/06/08|
| AAA|bbbbbbbbbbb|2019/03/30|
| AAA|bbbbbbbbbbb|2019/06/30|
+--------+-----------+----------+

Answer 1

Spark 2.4.3 using unix_timestamp you can convert data to the expected output.
scala> var df2 =spark.createDataFrame(Seq(("AAA","bbbbbbbbbbb","13190326"),("AAA","bbbbbbbbbbb","10190309"),("AAA","bbbbbbbbbbb","36190908"),("AAA","bbbbbbbbbbb","07190214"),("AAA","bbbbbbbbbbb","13190328"),("AAA","bbbbbbbbbbb","23190608"),("AAA","bbbbbbbbbbb","13190330"),("AAA","bbbbbbbbbbb","26190630"))).toDF("CDOPEINT","bbbbbbbbbb","Date")
scala> df2.withColumn("Date",from_unixtime(unix_timestamp(substring(col("Date"),3,7),"yyMMdd"),"yyyy/MM/dd")).show
+--------+-----------+----------+
|CDOPEINT| bbbbbbbbbb| Date|
+--------+-----------+----------+
| AAA|bbbbbbbbbbb|2019/03/26|
| AAA|bbbbbbbbbbb|2019/03/09|
| AAA|bbbbbbbbbbb|2019/09/08|
| AAA|bbbbbbbbbbb|2019/02/14|
| AAA|bbbbbbbbbbb|2019/03/28|
| AAA|bbbbbbbbbbb|2019/06/08|
| AAA|bbbbbbbbbbb|2019/03/30|
| AAA|bbbbbbbbbbb|2019/06/30|
+--------+-----------+----------+
let me know if you have any query related to this.

Answer 2

If the date involves values from 2000 and the Date column in your original dataframe is of Integer type,you could try something like this
def getDate =(date:Int) =>{
val dateString = date.toString.drop(2).sliding(2,2)
dateString.zipWithIndex.map{
case(value,index) => if(index ==0) 20+value else value
}.mkString("/")
}
Then create a UDF which calls this function
val updateDateUdf = udf(getDate)
If originalDF is the original Dataframe that you have, you could then change the dataframe like this
val updatedDF = originalDF.withColumn("Date",updateDateUdf(col("Date")))