val df = (Seq((1, "a", "10"),(1,"b", "12"),(1,"c", "13"),(2, "a", "14"),
(2,"c", "11"),(1,"b","12" ),(2, "c", "12"),(3,"r", "11")).
toDF("col1", "col2", "col3"))
So I have a spark dataframe with 3 columns.
+----+----+----+
|col1|col2|col3|
+----+----+----+
| 1| a| 10|
| 1| b| 12|
| 1| c| 13|
| 2| a| 14|
| 2| c| 11|
| 1| b| 12|
| 2| c| 12|
| 3| r| 11|
+----+----+----+
My requirement is actually I need to perform two levels of groupby as explained below.
Level1: If I do groupby on col1 and do a sum of Col3. I will get below two columns. 1. col1 2. sum(col3) I will loose col2 here.
Level2: If i want to again group by on col1 and col2 and do a sum of Col3 I will get below 3 columns. 1. col1 2. col2 3. sum(col3)
My requirement is actually I need to perform two levels of groupBy and have these two columns(sum(col3) of level1, sum(col3) of level2) in a final one dataframe.
How can I do this, can anyone explain?
spark : 1.6.2 Scala : 2.10