Spark 任务不可序列化

Question

我已经尝试了在 Whosebug 上找到的解决此问题的所有方法，但尽管如此，我还是无法解决它。我有一个实例化 "Recommendation" 对象的 "MainObj" 对象。当我调用 "recommendationProducts" 方法时，我总是会收到错误消息。这是该方法的代码：

def recommendationProducts(item: Int): Unit = {

val aMatrix = new DoubleMatrix(Array(1.0, 2.0, 3.0))

def cosineSimilarity(vec1: DoubleMatrix, vec2: DoubleMatrix): Double = {
  vec1.dot(vec2) / (vec1.norm2() * vec2.norm2())
}

val itemFactor = model.productFeatures.lookup(item).head
val itemVector = new DoubleMatrix(itemFactor)

//Here is where I get the error:
val sims = model.productFeatures.map { case (id, factor) =>
  val factorVector = new DoubleMatrix(factor)
  val sim = cosineSimilarity(factorVector, itemVector)
  (id, sim)
}

val sortedSims = sims.top(10)(Ordering.by[(Int, Double), Double] {
  case (id, similarity) => similarity
})

println("\nTop 10 products:")
sortedSims.map(x => (x._1, x._2)).foreach(println)

这是错误：

Exception in thread "main" org.apache.spark.SparkException: Task not serializable
at org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:298)
at org.apache.spark.util.ClosureCleaner$.org$apache$spark$util$ClosureCleaner$$clean(ClosureCleaner.scala:288)
at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:108)
at org.apache.spark.SparkContext.clean(SparkContext.scala:2094)
at org.apache.spark.rdd.RDD$$anonfun$map.apply(RDD.scala:370)
at org.apache.spark.rdd.RDD$$anonfun$map.apply(RDD.scala:369)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
at org.apache.spark.rdd.RDD.map(RDD.scala:369)
at RecommendationObj.recommendationProducts(RecommendationObj.scala:269)
at MainObj$.analisiIUNGO(MainObj.scala:257)
at MainObj$.menu(MainObj.scala:54)
at MainObj$.main(MainObj.scala:37)
at MainObj.main(MainObj.scala)
Caused by: java.io.NotSerializableException: org.apache.spark.SparkContext
Serialization stack:
- object not serializable (class: org.apache.spark.SparkContext, value: org.apache.spark.SparkContext@7c2312fa)
- field (class: RecommendationObj, name: sc, type: class org.apache.spark.SparkContext)
- object (class MainObj$$anon, MainObj$$anon@615bad16)
- field (class: RecommendationObj$$anonfun, name: $outer, type: class RecommendationObj)
- object (class RecommendationObj$$anonfun, <function1>)
at org.apache.spark.serializer.SerializationDebugger$.improveException(SerializationDebugger.scala:40)
at org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:46)
at org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:100)
at org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:295)
... 14 more

我试着补充： 1) "extends Serializable" (Scala) 到我的 Class 2) "extends extends java.io.Serializable" 到我的 Class 3）某些部分的“@transient” 4) 在这个 class 中获取模型（和其他功能）（现在我从另一个对象获取它们并将它们传递给我的 Class 就像参数一样）

我该如何解决？我快疯了！提前致谢！

Answer 1

钥匙在这里：

 field (class: RecommendationObj, name: sc, type: class org.apache.spark.SparkContext)

所以您有一个名为 sc 的 SparkContext 类型的字段。 Spark 想要序列化 class，因此他也尝试序列化所有字段。

你应该：

使用@transient 注释并检查是否为空，然后重新创建
不使用字段中的 SparkContext，而是将其放入方法的参数中。但是请记住，永远不要在 map、flatMap 等闭包中使用 SparkContext

Spark 任务不可序列化

Spark task not serializable

serialization

scala

exception

serializable

apache-spark