Standard deviation on multiple columns

[Naveen Kumar Pokala]

Hi,

I am using spark 1.6.0

I want to find standard deviation of columns that will come dynamically.

  val stdDevOnAll = columnNames.map { x => stddev(x }

    causalDf.groupBy(causalDf("A"),causalDf("B"),causalDf("C"))
    .agg(stdDevOnAll:_*) //error line


I am trying to do as above.

But it is giving me compilation error as below.

overloaded method value agg with alternatives: (expr: 
org.apache.spark.sql.Column,exprs: 
org.apache.spark.sql.Column*)org.apache.spark.sql.DataFrame <and> (exprs: 
java.util.Map[String,String])org.apache.spark.sql.DataFrame <and> (exprs: 
scala.collection.immutable.Map[String,String])org.apache.spark.sql.DataFrame 
<and> (aggExpr: (String, String),aggExprs: (String, 
String)*)org.apache.spark.sql.DataFrame cannot be applied to 
(org.apache.spark.sql.Column)


Naveen