火花定制聚合> = 2.0（阶）

Question

我具有以下数据集：

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() 

欲编写自定义集合函数myAvg这需要Tuple3参数和返回sum(_._2)/sum(_._3)。 我知道，它可以用其他方式计算，但我想编写自定义聚合。

我写了这样的事情：

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() 

不幸的是我收到以下错误：

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) 

有什么不对？

在我的本地星火2.1我收到一个警告

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

什么在我的代码已经过时？

感谢您的任何建议。

Answer 1

看来，这里的问题是您使用Java的Integer，而不是Scala的Int的 - 如果你Int替换的Integer所有使用您的聚合执行（与Encoders.scalaInt取代Encoders.INT） - 这个按预期工作：

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 

（也应用了一些语法糖，删除了明确的Tuble引用）。