How to parametrize class and implement method depends on type in Scala

Question

This is what I tried. Depends on what does user put into the function I want to add String or Double to new Chunk.

package org.apache.spark.h2o.utils

import water.fvec.{NewChunk, Frame, Chunk}
import water._
import water.parser.ValueString

class ReplaceNa[T >: Any](a: T) extends MRTask{
  override def map(c: Chunk, nc: NewChunk): Unit = {
    for (row <- 0 until c.len()) {

        a match{
             case s: ValueString if(c.isNA(row)) => nc.addStr(s)           
             case d: Double      if(c.isNA(row)) => nc.addNum(d)

      }
    }
  }
}

But I got error

 error: value outputFrame is not a member of Nothing
          pred.add(new ReplaceNa(3).doAll(1, pred.vec(4)).outputFrame(Array("s"), null))

Thanks for your help!

Answer 1

I have several comments:

• check for NA outside the switch branch
• you are missing non-NA case hence you are generating vector which is shorter than input vector (i expect you would like to generate the same length vector)

Regarding generics, you need to provide type specialization. For example, something like the following snippet:

class ReplaceNA[T](val value: T)(implicit add: TAdd[T]) extends MRTask[ReplaceNA[T]] {
  override def map(c: Chunk, nc: NewChunk): Unit = {
    for (row <- 0 until c.len()) {
      // Replace NAs by given value
      if (c.isNA(row)) {
        add.addValue(nc, value)
      } else {
        // Do something with default value
        nc.addNA()
      }
    }
  }

}

trait TAdd[T] extends Serializable {
  def addValue(nc: NewChunk, value: T)
}

object TAdd extends Serializable {
  implicit val addDouble = new TAdd[Double] { def addValue(nc: NewChunk, value: Double) = nc.addNum(value) }
  implicit val addFloat = new TAdd[Float] { def addValue(nc: NewChunk, value: Float) = nc.addNum(value) }
  implicit val addValueString = new TAdd[ValueString] { def addValue(nc: NewChunk, value: ValueString) = nc.addStr(value) }
}