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I have a Spark dataframe with several columns. I want to add a column on to the dataframe that is a sum of a certain number of the columns.

For example, my data looks like this:

ID var1 var2 var3 var4 var5
a   5     7    9    12   13
b   6     4    3    20   17
c   4     9    4    6    9
d   1     2    6    8    1

I want a column added summing the rows for specific columns:

ID var1 var2 var3 var4 var5   sums
a   5     7    9    12   13    46
b   6     4    3    20   17    50
c   4     9    4    6    9     32
d   1     2    6    8    10    27

I know it is possible to add columns together if you know the specific columns to add:

val newdf = df.withColumn("sumofcolumns", df("var1") + df("var2"))

But is it possible to pass a list of column names and add them together? Based off of this answer which is basically what I want but it is using the python API instead of scala (Add column sum as new column in PySpark dataframe) I think something like this would work:

//Select columns to sum
val columnstosum = ("var1", "var2","var3","var4","var5")

// Create new column called sumofcolumns which is sum of all columns listed in columnstosum
val newdf = df.withColumn("sumofcolumns", df.select(columstosum.head, columnstosum.tail: _*).sum)

This throws the error value sum is not a member of org.apache.spark.sql.DataFrame. Is there a way to sum across columns?

Thanks in advance for your help.

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1 Answer

You should try the following:

import org.apache.spark.sql.functions._

val sc: SparkContext = ...
val sqlContext = new SQLContext(sc)

import sqlContext.implicits._

val input = sc.parallelize(Seq(
  ("a", 5, 7, 9, 12, 13),
  ("b", 6, 4, 3, 20, 17),
  ("c", 4, 9, 4, 6 , 9),
  ("d", 1, 2, 6, 8 , 1)
)).toDF("ID", "var1", "var2", "var3", "var4", "var5")

val columnsToSum = List(col("var1"), col("var2"), col("var3"), col("var4"), col("var5"))

val output = input.withColumn("sums", columnsToSum.reduce(_ + _))

output.show()

Then the result is:

+---+----+----+----+----+----+----+
| ID|var1|var2|var3|var4|var5|sums|
+---+----+----+----+----+----+----+
|  a|   5|   7|   9|  12|  13|  46|
|  b|   6|   4|   3|  20|  17|  50|
|  c|   4|   9|   4|   6|   9|  32|
|  d|   1|   2|   6|   8|   1|  18|
+---+----+----+----+----+----+----+

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