错误执行器:阶段 6.0 spark scala 中任务 0.0 中的异常? [英] ERROR Executor: Exception in task 0.0 in stage 6.0 spark scala?

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问题描述

我有一个像下面这样的 json 文件.

I have a json file like below.

{"name":"method2","name1":"test","parameter1":"C:/Users/test/Desktop/Online.csv","parameter2": 1.0}

我正在加载我的 json 文件.

I am loading my json file.

val sqlContext = new org.apache.spark.sql.SQLContext(sc)
val df = sqlContext.read.json("C:/Users/test/Desktop/data.json")
val df1=df.select($"name",$"parameter1",$"parameter2").toDF()
df1.show()

我有如下3个功能:

def method1(P1:String, P2:Double) {
val data = spark.read.option("header", true).csv(P1).toDF()
val rs= data.select("CID", "Sc").dropDuplicates("CID", "Sc").withColumn("Rat", lit(P2))
val outPutPath="C:/Users/test/Desktop/output"
rs.coalesce(1).write.format("com.databricks.spark.csv").option("header", "true").save(outPutPath)
}
def method2(P1:String, P2:Double){
val data = spark.read.option("header", true).csv(P1).toDF()
val rs= data.select("CID", "Sc").withColumn("r", lit(P2))
val rs1= rs.filter($"CID" =!= "").groupBy("CID","Sc").agg(sum(rs("r")).alias("R"))
val outPutPath="C:/Users/test/Desktop/output"
rs1.coalesce(1).write.format("com.databricks.spark.csv").option("header", "true").save(outPutPath)
}
def methodn(P1:String, P2:Double) {
println("method 2 printhing")
println(P2)
}

我正在尝试使用以下代码调用上述函数

i am trying to call the above functions using below code

df1.map( row => (row.getString(0), row.getString(1), row.getDouble(2) ) ).foreach { x =>
      x._1.trim.toLowerCase match {
          case "method1" => method1(x._2, x._3) 
          case "method2" => method2(x._2, x._3)
          case _ => methodn(x._2, x._3)
      }
   }

基于我的 json 对象，它应该调用 method2，但是当我尝试执行上面的代码时，我遇到了以下错误.

based on my json object it should call method2 but when i am trying to execute above code i am getting below error.

17/11/22 16:15:44 ERROR Executor: Exception in task 0.0 in stage 6.0 (TID 6)
java.lang.NullPointerException
        at $line36.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw.method2(<console>:24)
        at $line38.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$anonfun$2.apply(<console>:40)
        at $line38.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$anonfun$2.apply(<console>:37)
        at scala.collection.Iterator$class.foreach(Iterator.scala:893)
        at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
        at org.apache.spark.rdd.RDD$$anonfun$foreach$1$$anonfun$apply$28.apply(RDD.scala:918)
        at org.apache.spark.rdd.RDD$$anonfun$foreach$1$$anonfun$apply$28.apply(RDD.scala:918)
        at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2062)
        at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2062)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
        at org.apache.spark.scheduler.Task.run(Task.scala:108)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
        at java.lang.Thread.run(Thread.java:745)
17/11/22 16:15:44 WARN TaskSetManager: Lost task 0.0 in stage 6.0 (TID 6, localhost, executor driver): java.lang.NullPointerException
        at $line36.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw.method2(<console>:24)
        at $line38.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$anonfun$2.apply(<console>:40)
        at $line38.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$anonfun$2.apply(<console>:37)
        at scala.collection.Iterator$class.foreach(Iterator.scala:893)
        at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
        at org.apache.spark.rdd.RDD$$anonfun$foreach$1$$anonfun$apply$28.apply(RDD.scala:918)
        at org.apache.spark.rdd.RDD$$anonfun$foreach$1$$anonfun$apply$28.apply(RDD.scala:918)
        at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2062)
        at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2062)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
        at org.apache.spark.scheduler.Task.run(Task.scala:108)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
        at java.lang.Thread.run(Thread.java:745)

17/11/22 16:15:44 ERROR TaskSetManager: Task 0 in stage 6.0 failed 1 times; aborting job
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 6.0 failed 1 times, most recent failure: Lost task 0.0 in stage 6.0 (TID 6, localhost, executor driver): java.lang.NullPointerException
        at method2(<console>:24)
        at $anonfun$2.apply(<console>:40)
        at $anonfun$2.apply(<console>:37)
        at scala.collection.Iterator$class.foreach(Iterator.scala:893)
        at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
        at org.apache.spark.rdd.RDD$$anonfun$foreach$1$$anonfun$apply$28.apply(RDD.scala:918)
        at org.apache.spark.rdd.RDD$$anonfun$foreach$1$$anonfun$apply$28.apply(RDD.scala:918)
        at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2062)
        at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2062)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
        at org.apache.spark.scheduler.Task.run(Task.scala:108)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
        at java.lang.Thread.run(Thread.java:745)

Driver stacktrace:
  at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1499)
  at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1487)
  at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1486)
  at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
  at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
  at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1486)
  at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
  at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
  at scala.Option.foreach(Option.scala:257)
  at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:814)
  at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1714)
  at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1669)
  at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1658)
  at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
  at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:630)
  at org.apache.spark.SparkContext.runJob(SparkContext.scala:2022)
  at org.apache.spark.SparkContext.runJob(SparkContext.scala:2043)
  at org.apache.spark.SparkContext.runJob(SparkContext.scala:2062)
  at org.apache.spark.SparkContext.runJob(SparkContext.scala:2087)
  at org.apache.spark.rdd.RDD$$anonfun$foreach$1.apply(RDD.scala:918)
  at org.apache.spark.rdd.RDD$$anonfun$foreach$1.apply(RDD.scala:916)
  at org.apache.spark.rdd.RDDOperationScope$.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.foreach(RDD.scala:916)
  at org.apache.spark.sql.Dataset$$anonfun$foreach$1.apply$mcV$sp(Dataset.scala:2325)
  at org.apache.spark.sql.Dataset$$anonfun$foreach$1.apply(Dataset.scala:2325)
  at org.apache.spark.sql.Dataset$$anonfun$foreach$1.apply(Dataset.scala:2325)
  at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:65)
  at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2823)
  at org.apache.spark.sql.Dataset.foreach(Dataset.scala:2324)
  ... 54 elided
Caused by: java.lang.NullPointerException
  at method2(<console>:24)
  at $anonfun$2.apply(<console>:40)
  at $anonfun$2.apply(<console>:37)
  at scala.collection.Iterator$class.foreach(Iterator.scala:893)
  at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
  at org.apache.spark.rdd.RDD$$anonfun$foreach$1$$anonfun$apply$28.apply(RDD.scala:918)
  at org.apache.spark.rdd.RDD$$anonfun$foreach$1$$anonfun$apply$28.apply(RDD.scala:918)
  at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2062)
  at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2062)
  at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
  at org.apache.spark.scheduler.Task.run(Task.scala:108)
  at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335)
  at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
  at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
  at java.lang.Thread.run(Thread.java:745)

请帮助我解决这个问题.

please help me on this how to resolve this issue.

推荐答案

您收到 NullPointerException 因为您正在尝试访问 sparkSession(spark) 在 functions(method1, method2) 中.但这不是一个实际问题.主要问题是您从 dataframe 的 map 函数内部调用这些函数.这就是主要问题.

You are getting NullPointerException because you are trying to access sparkSession(spark) inside the functions(method1, method2). Thats not an actual issue though. The main issue is that you are calling those functions from inside map function of dataframe. Thats the main issue.

您不能从 transformations 内部访问在 transformations 之外定义的变量.所有函数都在 transformations 内被调用，Spark 找不到这些函数内使用的 spark 变量的任何定义.这是获得 nullPointerException 的主要原因.

You cannot access variables defined outside transformations from within transformations. All the functions are being called inside transformations and Spark could not find any definition for spark variable being used inside those functions. Thats the main reason for getting nullPointerException.

对此的解决方案是从可以访问 spark 变量的地方调用函数，而不是从 transformation 中调用.因此，将您最后的 transformation 更改为 action 就可以了

The solution to this would be to call the functions from where spark variable can be accessed and not from within a transformation. So changing your last transformation into an action would do the trick

val process = df1.map( row => (row.getString(0), row.getString(1), row.getDouble(2) ) ).collect

process.foreach { x =>
  x._1.trim.toLowerCase match {
    case "method1" => method1(x._2, x._3)
    case "method2" => method2(x._2, x._3)
    case _ => methodn(x._2, x._3)
  }
}

希望回答对你有帮助

这篇关于错误执行器:阶段 6.0 spark scala 中任务 0.0 中的异常?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！

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