我正在尝试在 Apache Flink 上准备一个小型示例应用程序,主要目的是演示如何使用广播变量。此应用程序读取一个 CSV 文件并准备一个DataSet[BuildingInformation]
case class BuildingInformation(
buildingID: Int, buildingManager: String, buildingAge: Int,
productID: String, country: String
)
这就是我目前正在创建 BuildingInformation 数据集的方式:
val buildingsBroadcastSet =
envDefault
.fromElements(
readBuildingInfo(
envDefault,
"./SensorFiles/building.csv")
)
然后,我开始这样转变:
val hvacStream = readHVACReadings(envDefault,"./SensorFiles/HVAC.csv")
hvacStream
.map(new HVACToBuildingMapper)
.withBroadcastSet(buildingsBroadcastSet,"buildingData")
.writeAsCsv("./hvacTemp.csv")
(buildingID -> BuildingInformation) 的 map 是我想要的广播引用数据。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
)
}
}
在函数签名中
def initializeBroadcastVariable(valuesPushed:java.lang.Iterable[BuildingInformation]): Map[Int,BuildingInformation]
java.lang.Iterable 资格是我的补充。没有这个,编译器会在 Intellij 中报错。
在运行时,应用程序在我从 Iterable[BuildingInformation] 中创建 map 并由框架传递给 open() 函数时失败:
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.
假设这可能是从 (Java) Iterable 转换案例类失败的特定案例(尽管我自己并不相信),我尝试用其所有成员字段的 Tuple5 替换 BuildingInformation。行为没有改变。
我本可以通过提供 CanBuildFrom 来尝试,但我没有这样做。我的想法拒绝了一个简单的案例类不能映射到另一个数据结构。有问题,这对我来说并不明显。
为了完成这篇文章,我尝试了对应于 Scala 2.11.x 和 Scala 2.10.x 的 Flink 版本:行为是相同的。
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 的困惑与 Java 的 Iterable 被用作 Scala 的列表有关,但是,我当然不确定。
谁能帮我找出错误?
最佳答案
问题是您必须在 readBuildingInfo
的 map
函数中返回一些内容。此外,如果您提供了 List[BuildingInformation]
,则不应使用 fromElements
,而如果您想展平列表,则应使用 fromCollection
。以下代码片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)
}
关于java - Apache Flink : transforming Broadcast variables fails, 但我无法确定原因,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/36929423/