Question

在使用Scala 2.12的lightbend kafka-streams-scala移植中使用kafka-streams-scala时，编译器遇到了一个奇怪的问题，即无法正确处理对重载方法的调用

import org.apache.kafka.streams.kstream.Consumed
import org.apache.kafka.streams.scala.StreamsBuilder
import org.apache.kafka.streams.scala.kstream.KTable

object FailingExample {


  private val builder = new StreamsBuilder()

  class MyClass

  class MyClass2

  class MyClass3

  implicit val consumedMyClass1: Consumed[String,MyClass] = null

  implicit val consumedMyClass2: Consumed[String,MyClass2] = null

  val table:KTable[String,MyClass] = builder.table[String,MyClass]("myTopic1")
  val table1:KTable[String,MyClass2] = builder.table[String,MyClass2]("myTopic1")

  table.join(table1)(
    (myClass:MyClass, myClass2:MyClass2) => new MyClass3
  )

编译器失败

[error] /Users/edmondoporcu1/Development/credimi/user-preferences/user-preferences-salesforce-updater/src/main/scala/com/credimi/kafka/FailingExample.scala:25:9: ambiguous reference to overloaded definition,
[error] both method join in class KTable of type [VO, VR](other: org.apache.kafka.streams.scala.kstream.KTable[String,VO])(joiner: (com.credimi.kafka.FailingExample.MyClass, VO) => VR, materialized: org.apache.kafka.streams.kstream.Materialized[String,VR,org.apache.kafka.streams.scala.ByteArrayKeyValueStore])org.apache.kafka.streams.scala.kstream.KTable[String,VR]
[error] and  method join in class KTable of type [VO, VR](other: org.apache.kafka.streams.scala.kstream.KTable[String,VO])(joiner: (com.credimi.kafka.FailingExample.MyClass, VO) => VR)org.apache.kafka.streams.scala.kstream.KTable[String,VR]
[error] match argument types (org.apache.kafka.streams.scala.kstream.KTable[String,com.credimi.kafka.FailingExample.MyClass2])
[error]   table.join(table1)(

但是，这没有多大意义，因为我们仅在第二个参数列表中传递了一个参数，因此编译器不应有任何歧义。我们在org.apache.kafka.streams.scala.kstream.Ktable中包含了两种方法作为参考：

  /**
   * Join records of this [[KTable]] with another [[KTable]]'s records using non-windowed inner equi join.
   *
   * @param other  the other [[KTable]] to be joined with this [[KTable]]
   * @param joiner a function that computes the join result for a pair of matching records
   * @return a [[KTable]] that contains join-records for each key and values computed by the given joiner,
   * one for each matched record-pair with the same key
   * @see `org.apache.kafka.streams.kstream.KTable#join`
   */
  def join[VO, VR](other: KTable[K, VO])(joiner: (V, VO) => VR): KTable[K, VR] =
    inner.join[VO, VR](other.inner, joiner.asValueJoiner)

  /**
   * Join records of this [[KTable]] with another [[KTable]]'s records using non-windowed inner equi join.
   *
   * @param other  the other [[KTable]] to be joined with this [[KTable]]
   * @param joiner a function that computes the join result for a pair of matching records
   * @param materialized  a `Materialized` that describes how the `StateStore` for the resulting [[KTable]]
   *                      should be materialized. 
   * @return a [[KTable]] that contains join-records for each key and values computed by the given joiner,
   * one for each matched record-pair with the same key
   * @see `org.apache.kafka.streams.kstream.KTable#join`
   */
  def join[VO, VR](other: KTable[K, VO])(
    joiner: (V, VO) => VR,
    materialized: Materialized[K, VR, ByteArrayKeyValueStore]
  ): KTable[K, VR] =
    inner.join[VO, VR](other.inner, joiner.asValueJoiner, materialized)

使用kafka-streams-scala时，Scalac 2.12无法解析具有多个参数列表的重载方法

0 个答案: