infer.scala

// fails with:
// $ /opt/scala-2.10.4/bin/scalac -d /tmp src/main/scala/infer.scala -cp ../spark/assembly/target/scala-2.10/spark-assembly-1.6.0-SNAPSHOT-hadoop2.2.0.jar 
// src/main/scala/infer.scala:27: error: missing parameter type for expanded function ((x$2) => x$2._2)
//		ds.groupBy(_._1).agg(sum(_._2), sum(_._3)).collect()
//                                         ^
// one error found
//


import org.apache.spark.sql.functions._
import org.apache.spark.sql.Encoder
import org.apache.spark.sql.expressions.Aggregator
import org.apache.spark.sql.TypedColumn
import org.apache.spark._
import org.apache.spark.sql._


/** An `Aggregator` that adds up any numeric type returned by the given function. */
class SumOf[I, N : Numeric](f: I => N) extends Aggregator[I, N, N] with Serializable {
  val numeric = implicitly[Numeric[N]]
  override def zero: N = numeric.zero
  override def reduce(b: N, a: I): N = numeric.plus(b, f(a))
  override def merge(b1: N,b2: N): N = numeric.plus(b1, b2)
  override def finish(reduction: N): N = reduction
}

class Main {

	val sc = new SparkContext(new SparkConf(true))
	val sqlContext = new SQLContext(sc)
	import sqlContext.implicits._

	def test() {
		def sum[I, N : Numeric : Encoder](f: I => N): TypedColumn[I, N] = new SumOf(f).toColumn
		val ds = Seq((1, 1, 2L), (1, 2, 3L), (1, 3, 4L), (2, 1, 5L)).toDS()
		ds.groupBy(_._1).agg(sum(_._2), sum(_._3)).collect()
	}
}