在 Amazon EMR 集群中运行时，Spark 广播变量返回 NullPointerException

Posted 2023-04-14

【中文标题】在 Amazon EMR 集群中运行时，Spark 广播变量返回 NullPointerException

【英文标题】：Spark broadcasted variable returns NullPointerException when run in Amazon EMR cluster

【发布时间】：2015-09-27 00:32:06

【问题描述】：

我通过广播共享的变量在集群中为空。

我的应用程序相当复杂，但是我编写了这个小例子，当我在本地运行它时可以完美运行，但在集群中却失败了：

package com.gonzalopezzi.bigdata.bicing

import org.apache.spark.broadcast.Broadcast
import org.apache.spark.rdd.RDD
import org.apache.spark.SparkContext, SparkConf

object PruebaBroadcast2 extends App 
  val conf = new SparkConf().setAppName("PruebaBroadcast2")
  val sc = new SparkContext(conf)

  val arr : Array[Int] = (6 to 9).toArray
  val broadcasted = sc.broadcast(arr)

  val rdd : RDD[Int] = sc.parallelize((1 to 4).toSeq, 2) // a small integer array [1, 2, 3, 4] is paralellized in two machines
  rdd.flatMap((a : Int) => List((a, broadcasted.value(0)))).reduceByKey(_+_).collect().foreach(println)  // NullPointerException in the flatmap. broadcasted is null

我不知道问题是编码错误还是配置问题。

这是我得到的堆栈跟踪：

15/07/07 20:55:13 INFO scheduler.DAGScheduler: Job 0 failed: collect at PruebaBroadcast2.scala:24, took 0.992297 s
Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 6, ip-172-31-36-49.ec2.internal): java.lang.NullPointerException
    at com.gonzalopezzi.bigdata.bicing.PruebaBroadcast2$$anonfun$2.apply(PruebaBroadcast2.scala:24)
    at com.gonzalopezzi.bigdata.bicing.PruebaBroadcast2$$anonfun$2.apply(PruebaBroadcast2.scala:24)
    at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
    at org.apache.spark.util.collection.ExternalSorter.insertAll(ExternalSorter.scala:202)
    at org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:56)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:68)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
    at org.apache.spark.scheduler.Task.run(Task.scala:64)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
    at java.lang.Thread.run(Thread.java:745)

Driver stacktrace:
    at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1204)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1193)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1192)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1192)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
    at scala.Option.foreach(Option.scala:236)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:693)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1393)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1354)
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
Command exiting with ret '1'

谁能帮我解决这个问题？ 至少，你能告诉我你是否在代码中看到了奇怪的东西吗？ 如果您认为代码没问题，请告诉我，因为这意味着问题出在集群的配置中。

提前致谢。

【参考方案1】：

我终于让它工作了。

这样声明对象是行不通的：

object MyObject extends App 

但是，如果你声明一个带有 main 函数的对象：

object MyObject 
    def main (args : Array[String]) 
    /* ... */
    

所以，如果我以这种方式重写问题中的简短示例：

object PruebaBroadcast2 

  def main (args: Array[String]) 
    val conf = new SparkConf().setAppName("PruebaBroadcast2")
    val sc = new SparkContext(conf)

    val arr : Array[Int] = (6 to 9).toArray
    val broadcasted = sc.broadcast(arr)

    val rdd : RDD[Int] = sc.parallelize((1 to 4).toSeq, 2)

    rdd.flatMap((a : Int) => List((a, broadcasted.value(0)))).reduceByKey(_+_).collect().foreach(println)
  

这个问题似乎与这个错误有关： https://issues.apache.org/jira/browse/SPARK-4170

【讨论】：

错误状态为“已修复”，但我似乎仍然遇到同样的问题 (cdh 5.5.2)

该错误状态为“已修复”，但该修复仅显示警告：“scala.App 的子类可能无法正常工作。请改用 main() 方法。”

这是一个技巧，但在美学上我更喜欢一点，你可以这样做object PruebaBroadcast2 extends App /* your code */

【参考方案2】：

我有类似的问题。问题是我有一个变量，并在 RDD 映射函数中使用它，我得到了空值。这是我的原始代码：

object MyClass extends App 
    ...
    val prefix = "prefix" 
    val newRDD = inputRDD.map(s => prefix + s) // got null for prefix
    ...

我发现它适用于任何函数，而不仅仅是 ma​​in()：

object MyClass extends App 
    ...
    val prefix = "prefix" 
    val newRDD = addPrefix(input, prefix)
    def addPrefix(input: RDD[String], prefix: String): RDD[String] = 
        inputRDD.map(s => prefix + s)