CODEWITHSUNDEEP
scalaapache-sparkaggregate-functions
SmallerThan
SmallerThan

Reputation: 33

spark custom Aggregator >=2.0 (scala)

I have following Dataset:

val myDS = List(("a",1,1.1), ("b",2,1.2), ("a",3,3.1), ("b",4,1.4), ("a",5,5.1)).toDS
// and aggregation
// myDS.groupByKey(t2 => t2._1).agg(myAvg).collect()

I want to write custom aggregate function myAvg which takes Tuple3 arguments and return sum(_._2)/sum(_._3). I know, that it can be computed in other ways, but I want to write custom aggregate.

I wrote something like that:

    import org.apache.spark.sql.expressions.Aggregator
    import org.apache.spark.sql.{Encoder, Encoders}

    val myAvg =  new Aggregator[Tuple3[String, Integer, Double], 
                                Tuple2[Integer,Double], 
                                Double] {
      def zero: Tuple2[Integer,Double] = Tuple2(0,0.0)
      def reduce(agg: Tuple2[Integer,Double], 
                 a: Tuple3[String, Integer,Double]): Tuple2[Integer,Double] = 
                              Tuple2(agg._1 + a._2, agg._2 + a._3)
      def merge(agg1: Tuple2[Integer,Double], 
                agg2: Tuple2[Integer,Double]): Tuple2[Integer,Double] = 
                              Tuple2(agg1._1 + agg2._1, agg1._2 + agg2._2) 
      def finish(res: Tuple2[Integer,Double]): Double = res._1/res._2
      def bufferEncoder: Encoder[(Integer, Double)] =
                              Encoders.tuple(Encoders.INT, Encoders.scalaDouble)
      def outputEncoder: Encoder[Double] = Encoders.scalaDouble
    }.toColumn()

Unfortunately I receive the following error:

java.lang.RuntimeException: Unsupported literal type class scala.runtime.BoxedUnit ()
    at org.apache.spark.sql.catalyst.expressions.Literal$.apply(literals.scala:75)
    at org.apache.spark.sql.functions$.lit(functions.scala:101)
    at org.apache.spark.sql.Column.apply(Column.scala:217)

What's wrong?

In my local Spark 2.1 I receive one warning 

warning: there was one deprecation warning; re-run with -deprecation for details

What is deprecated in my code?

Thanks for any advice.

Upvotes: 1

Views: 1054

Answers (1)

Tzach Zohar
Tzach Zohar

Reputation: 37822

It seems that the problem here is your use of Java's Integer instead of Scala's Int - if you replace all usages of Integer in your Aggregator implementation with Int (and replace Encoders.INT with Encoders.scalaInt) - this works as expected:

val myAvg: TypedColumn[(String, Int, Double), Double] =  new Aggregator[(String, Int, Double), (Int, Double), Double] {
  def zero: (Int, Double) = Tuple2(0,0.0)
  def reduce(agg: (Int, Double), a: (String, Int, Double)): (Int, Double) =
    (agg._1 + a._2, agg._2 + a._3)
  def merge(agg1: (Int, Double), agg2: (Int, Double)): (Int, Double) =
    (agg1._1 + agg2._1, agg1._2 + agg2._2)
  def finish(res: (Int, Double)): Double = res._1/res._2
  def bufferEncoder: Encoder[(Int, Double)] =
    Encoders.tuple(Encoders.scalaInt, Encoders.scalaDouble)
  def outputEncoder: Encoder[Double] = Encoders.scalaDouble
}.toColumn

(also applied some syntactic sugar, removing explicit Tuble references).

Upvotes: 1

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