"NotSerializableException " 在 scala 映射函数中

Question

我正在读取文件并尝试使用函数映射值。但它给出了一个错误 NotSerializableException 下面是我运行ning:

的代码

package com.sundogsoftware.spark

import org.apache.spark._
import org.apache.spark.SparkContext._
import org.apache.log4j._
import scala.math.min

/** Find the minimum temperature by weather station */
object MinTemperatures {

  def parseLine(line: String) = {
    val fields = line.split(",")
    val stationID = fields(0)
    val entryType = fields(2)
    val temperature = fields(3).toFloat * 0.1f * (9.0f / 5.0f) + 32.0f
    (stationID, entryType, temperature)
  }

  /** Our main function where the action happens */
  def main(args: Array[String]) {

    // Set the log level to only print errors
    Logger.getLogger("org").setLevel(Level.ERROR)

    // Create a SparkContext using every core of the local machine
    val sc = new SparkContext("local[*]", "MinTemperatures")

    // Read each line of input data
    val lines = sc.textFile("../DataSet/1800.csv")

    // Convert to (stationID, entryType, temperature) tuples
    val parsedLines = lines.map(parseLine)
}
}

当我运行上面的代码时，它给我以下错误：

Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties Exception in thread "main" org.apache.spark.SparkException: Task not serializable at org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:403) at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:393) at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:162) at org.apache.spark.SparkContext.clean(SparkContext.scala:2326) at org.apache.spark.rdd.RDD.$anonfun$map(RDD.scala:371) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) at org.apache.spark.rdd.RDD.withScope(RDD.scala:363) at org.apache.spark.rdd.RDD.map(RDD.scala:370) at com.sundogsoftware.spark.MinTemperatures$.main(MinTemperatures.scala:32) at com.sundogsoftware.spark.MinTemperatures.main(MinTemperatures.scala)

Caused by: java.io.NotSerializableException:

com.sundogsoftware.spark.MinTemperatures$ Serialization stack: - object not serializable (class: com.sundogsoftware.spark.MinTemperatures$, value: com.sundogsoftware.spark.MinTemperatures$@41fed14f) - element of array (index: 0) - array (class [Ljava.lang.Object;, size 1) - field (class: java.lang.invoke.SerializedLambda, name: capturedArgs, type: class [Ljava.lang.Object;) - object (class java.lang.invoke.SerializedLambda, SerializedLambda[capturingClass=class com.sundogsoftware.spark.MinTemperatures$, functionalInterfaceMethod=scala/Function1.apply:(Ljava/lang/Object;)Ljava/lang/Object;, implementation=invokeStatic com/sundogsoftware/spark/MinTemperatures$.$anonfun$main:(Lcom/sundogsoftware/spark/MinTemperatures$;Ljava/lang/String;)Lscala/Tuple3;, instantiatedMethodType=(Ljava/lang/String;)Lscala/Tuple3;, numCaptured=1]) - writeReplace data (class: java.lang.invoke.SerializedLambda)

但是当我运行使用匿名函数的相同代码时运行ning 成功:

package com.sundogsoftware.spark

import org.apache.spark._
import org.apache.spark.SparkContext._
import org.apache.log4j._
import scala.math.min

/** Find the minimum temperature by weather station */
object MinTemperatures {

  /** Our main function where the action happens */
  def main(args: Array[String]) {

    // Set the log level to only print errors
    Logger.getLogger("org").setLevel(Level.ERROR)

    // Create a SparkContext using every core of the local machine
    val sc = new SparkContext("local[*]", "MinTemperatures")

    // Read each line of input data
    val lines = sc.textFile("../DataSet/1800.csv")

    // Convert to (stationID, entryType, temperature) tuples
    val parsedLines = lines.map(x => {
      val fields = x.split(",");
      val stationID = fields(0);
      val entryType = fields(2);
      val temperature = fields(3).toFloat * 0.1f * (9.0f / 5.0f) + 32.0f;
      (stationID, entryType, temperature)
    })

    // Filter out all but TMIN entries
    val minTemps = parsedLines.filter(x => x._2 == "TMIN")

    // Convert to (stationID, temperature)
    val stationTemps = minTemps.map(x => (x._1, x._3.toFloat))

    // Reduce by stationID retaining the minimum temperature found
    val minTempsByStation = stationTemps.reduceByKey((x, y) => min(x, y))

    // Collect, format, and print the results
    val results = minTempsByStation.collect()

    for (result <- results.sorted) {
      val station = result._1
      val temp = result._2
      val formattedTemp = f"$temp%.2f F"
      println(s"$station minimum temperature: $formattedTemp")
    }

  }
}

输出：

EZE00100082 minimum temperature: 7.70 F
ITE00100554 minimum temperature: 5.36 F

正如您在上面看到的，当我在地图中使用 命名函数 (parseLine) 时，它给出了错误 ，但是当我使用 [=27 时是同一个程序而不是命名函数=]映射中的匿名函数运行成功.

我查看了一些博客，但没有找到错误的原因。谁能帮助我理解这一点？

Answer 1

这个问题似乎与 sbt 或依赖关系无关，正如我检查的那样，当脚本未定义为对象时会发生这种情况（Scala 对象默认是可序列化的）所以这个错误意味着脚本不是可序列化。我创建了一个新对象并粘贴了相同的代码。成功了。

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