火花聚合器无法正常工作

我想在Scala Spark中试用聚合器,但我似乎无法让它们同时使用 select 功能和 groupBy/agg 功能(使用我当前的实现 agg 函数无法编译)。我的聚合器写在下面,应该不言自明。

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

/** Stores the number of true counts (tc) and false counts (fc) */
case class Counts(var tc: Long, var fc: Long)

/** Count the number of true and false occurances of a function */
class BooleanCounter[A](f: A => Boolean) extends Aggregator[A, Counts, Counts] with Serializable {
  // Initialize both counts to zero
  def zero: Counts = Counts(0L, 0L) 
  // Sum counts for intermediate value and new value
  def reduce(acc: Counts, other: A): Counts = { 
    if (f(other)) acc.tc += 1 else acc.fc += 1
    acc 
  }
  // Sum counts for intermediate values
  def merge(acc1: Counts, acc2: Counts): Counts = { 
    acc1.tc += acc2.tc
    acc1.fc += acc2.fc
    acc1
  }
  // Return results
  def finish(acc: Counts): Counts = acc 
  // Encoder for intermediate value type
  def bufferEncoder: Encoder[Counts] = Encoders.product[Counts]
  // Encoder for return type
  def outputEncoder: Encoder[Counts] = Encoders.product[Counts]
}

下面是我的测试代码。

val ds: Dataset[Employee] = Seq(
  Employee("John", 110),
  Employee("Paul", 100),
  Employee("George", 0), 
  Employee("Ringo", 80) 
).toDS()

val salaryCounter = new BooleanCounter[Employee]((r: Employee) => r.salary < 10).toColumn
// Usage works fine 
ds.select(salaryCounter).show()
// Causes an error
ds.groupBy($"name").agg(salaryCounter).show()

首次使用 salaryCounter 工作正常,但第二个会导致以下编译错误。

java.lang.ClassCastException: org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema cannot be cast to Employee 

Databricks有一个 tutorial 这相当复杂,但似乎是Spark 2.3。还有 this 使用Spark 1.6中的实验功能的旧教程。