scala - Spark - Sum of row values

Question

I have the following DataFrame:

January | February | March
-----------------------------
  10    |    10    |  10
  20    |    20    |  20
  50    |    50    |  50

I'm trying to add a column to this which is the sum of the values of each row.

January | February | March  | TOTAL
----------------------------------
  10    |    10    |   10   |  30
  20    |    20    |   20   |  60
  50    |    50    |   50   |  150

As far as I can see, all the built in aggregate functions seem to be for calculating values in single columns. How do I go about using values across columns on a per row basis (using Scala)?

I've gotten as far as

val newDf: DataFrame = df.select(colsToSum.map(col):_*).foreach ...

Answer 1

You were very close with this:

val newDf: DataFrame = df.select(colsToSum.map(col):_*).foreach ...

Instead, try this:

val newDf = df.select(colsToSum.map(col).reduce((c1, c2) => c1 + c2) as "sum")

I think this is the best of the the answers, because it is as fast as the answer with the hard-coded SQL query, and as convenient as the one that uses the UDF. It's the best of both worlds -- and I didn't even add a full line of code!