How to calculate total across columns but one?

问题:

I want to create a "Total" row in a dataframe.

This will add all rows EXCEPT the uid cell.

uid  val1 val2 val3 
3213 1    2    3

To create this:

uid  val1 val2 val3 Total
3213 1    2    3     6

So, I need to filter out the UID, then sum. However, if I drop the UID before summing, then I won't be able to rejoin the tables after summing (as the join would have to be on UID).

I was playing with filter, but I cannot find a way to get the Column Name in filter.

So what I have so far is:

   val dfvReducedTotalled = dfvReduced.withColumn("TOTAL", dfvReduced.columns
  .filter(col=> !col.?????? == "UID")
  .map(c => col(c)).reduce((c1, c2) => c1 + c2))

回答1:

You can collect column names that are not uid firstly, build the sum expressions using reduce and then create the Total column:

val row_sum_expr = df.columns.collect{ case x if x != "uid" => col(x) }.reduce(_ + _)
df.withColumn("Total", row_sum_expr).show
+----+----+----+----+-----+
| uid|val1|val2|val3|Total|
+----+----+----+----+-----+
|3213|   1|   2|   3|    6|
+----+----+----+----+-----+