Question

我正在尝试在Apache Flink上准备一个小样本应用程序，主要目的是演示如何使用Broadcast变量。此应用程序读取CSV文件并准备 DataSet [BuildingInformation]

case class BuildingInformation(
     buildingID: Int, buildingManager: String, buildingAge: Int,
     productID: String, country: String
)

这就是我现在正在创建 BuildingInformation DataSet的方法：

val buildingsBroadcastSet =
      envDefault
      .fromElements(
                     readBuildingInfo(
                        envDefault,
                        "./SensorFiles/building.csv")
                   )

然后，我开始转变：

val hvacStream = readHVACReadings(envDefault,"./SensorFiles/HVAC.csv")

    hvacStream
      .map(new HVACToBuildingMapper)
      .withBroadcastSet(buildingsBroadcastSet,"buildingData")
      .writeAsCsv("./hvacTemp.csv")

（ buildingID - ＆gt; BuildingInformation ）的地图是我想要作为广播的参考数据。为了做好准备，我实现了一个RichMapFunction：

 class HVACToBuildingMapper
    extends RichMapFunction  [HVACData,EnhancedHVACTempReading] {

    var allBuildingDetails: Map[Int, BuildingInformation] = _

    override def open(configuration: Configuration): Unit = {

      allBuildingDetails =
        getRuntimeContext
        .getBroadcastVariableWithInitializer(
          "buildingData",
          new BroadcastVariableInitializer [BuildingInformation,Map[Int,BuildingInformation]] {

            def initializeBroadcastVariable(valuesPushed:java.lang.Iterable[BuildingInformation]): Map[Int,BuildingInformation] = {
              valuesPushed
                .asScala
                .toList
              .map(nextBuilding => (nextBuilding.buildingID,nextBuilding))(breakOut)
            }
          }
        )
    }
    override def map(nextReading: HVACData): EnhancedHVACTempReading = {
      val buildingDetails = allBuildingDetails.getOrElse(nextReading.buildingID,UndefinedBuildingInformation)
      // ... more intermediate data creation logic here
      EnhancedHVACTempReading(
        nextReading.buildingID,
        rangeOfTempRecorded,
        isExtremeTempRecorded,
        buildingDetails.country,
        buildingDetails.productID,
        buildingDetails.buildingAge,
        buildingDetails.buildingManager
      )
    }

  }

在功能签名

中

def initializeBroadcastVariable(valuesPushed:java.lang.Iterable[BuildingInformation]): Map[Int,BuildingInformation]

java.lang.Iterable 的

资格是我的补充。如果没有这个，编译器就会在Intellij中抱怨。

在运行时，应用程序失败，我正在创建一个由Iterable [BuildingInformation]构建的地图，该地图由框架传递给 open（）函数：

java.lang.Exception: The user defined 'open()' method caused an exception: scala.collection.immutable.$colon$colon cannot be cast to org.nirmalya.hortonworks.tutorial.BuildingInformation
    at org.apache.flink.runtime.operators.BatchTask.run(BatchTask.java:475)
    at org.apache.flink.runtime.operators.BatchTask.invoke(BatchTask.java:345)
    at org.apache.flink.runtime.taskmanager.Task.run(Task.java:559)
    at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.ClassCastException: scala.collection.immutable.$colon$colon cannot be cast to org.nirmalya.hortonworks.tutorial.BuildingInformation
    at org.nirmalya.hortonworks.tutorial.HVACReadingsAnalysis$HVACToBuildingMapper$$anon$7$$anonfun$initializeBroadcastVariable$1.apply(HVACReadingsAnalysis.scala:139)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
    at scala.collection.immutable.List.foreach(List.scala:318)
    at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
    at scala.collection.AbstractTraversable.map(Traversable.scala:105)
    at org.nirmalya.hortonworks.tutorial.HVACReadingsAnalysis$HVACToBuildingMapper$$anon$7.initializeBroadcastVariable(HVACReadingsAnalysis.scala:139)
    at org.nirmalya.hortonworks.tutorial.HVACReadingsAnalysis$HVACToBuildingMapper$$anon$7.initializeBroadcastVariable(HVACReadingsAnalysis.scala:133)
    at org.apache.flink.runtime.broadcast.BroadcastVariableMaterialization.getVariable(BroadcastVariableMaterialization.java:234)
    at org.apache.flink.runtime.operators.util.DistributedRuntimeUDFContext.getBroadcastVariableWithInitializer(DistributedRuntimeUDFContext.java:84)
    at org.nirmalya.hortonworks.tutorial.HVACReadingsAnalysis$HVACToBuildingMapper.open(HVACReadingsAnalysis.scala:131)
    at org.apache.flink.api.common.functions.util.FunctionUtils.openFunction(FunctionUtils.java:38)
    at org.apache.flink.runtime.operators.BatchTask.run(BatchTask.java:471)
    ... 3 more
09:28:54,389 INFO  org.apache.flink.runtime.client.JobClientActor                - 04/29/2016 09:28:54  Job execution switched to status FAILED.

假设它可能是从（Java）Iterable转换案例类失败的特殊情况（虽然我不相信自己），但我尝试用其所有成员字段的Tuple5替换BuildingInformation。行为没有改变。

我可以通过提供 CanBuildFrom 来尝试，但我没有做到这一点。我的思绪拒绝了一个简单的案例类无法映射到另一个数据结构。有些不对劲，这对我来说并不明显。

为了完成帖子，我尝试使用与Scala 2.11.x和Scala 2.10.x相对应的Flink版本：行为是一样的。

此外，这里是EnhancedHVACTempReading（为了更好地理解代码）：

case class EnhancedHVACTempReading(buildingID: Int, rangeOfTemp: String, extremeIndicator: Boolean,country: String, productID: String,buildingAge: Int, buildingManager: String)

我有一种预感，JVM的紊乱与Java的Iterable被用作Scala的List有关，但是，当然，我当然不确定。

有人可以帮我发现错误吗？

Answer 1

问题是您必须在map中的readBuildingInfo函数中返回一些内容。此外，如果您提供fromElements，则不应使用List[BuildingInformation]，而是在要展平列表时使用fromCollection。以下代码段显示了必要的更改。

def main(args: Array[String]): Unit = {
    val envDefault = ExecutionEnvironment.getExecutionEnvironment

    val buildingsBroadcastSet = readBuildingInfo(envDefault,"./SensorFiles/building.csv")

    val hvacStream = readHVACReadings(envDefault,"./SensorFiles/HVAC.csv")

    hvacStream
      .map(new HVACToBuildingMapper)
      .withBroadcastSet(buildingsBroadcastSet,"buildingData")
      .writeAsCsv("./hvacTemp.csv")

    envDefault.execute("HVAC Simulation")
}

和

private def readBuildingInfo(env: ExecutionEnvironment, inputPath: String): DataSet[BuildingInformation] = {
    val input = Source.fromFile(inputPath).getLines.drop(1).map(datum => {

      val fields = datum.split(",")
      BuildingInformation(
          fields(0).toInt,     // buildingID
          fields(1),           // buildingManager
          fields(2).toInt,     // buildingAge
          fields(3),           // productID
          fields(4)            // Country
        )
    })
    env.fromCollection(input.toList)
}

Apache Flink：转换广播变量失败，但我无法确定原因

1 个答案: