MapPartitionsRDD 上的 zipWithIndex

Question

我有words 这是 org.apache.spark.rdd.RDD[Array[String]] = MapPartitionsRDD[11] at map 看起来像

Array(Array(cyber crimes, cyber security, review, india, instances, state, issue), Array(civil society, instances, frequency))

现在在上面执行 flatMap 和 distinct 以从 RDD 中获取所有不同的单词后，我得到了

scala> val uniquewords = words.flatMap(_.distinct)
res17: org.apache.spark.rdd.RDD[String] = MapPartitionsRDD[20] at flatMap at <console>:30

scala> uniquewords.take(10)
res18: Array[String] = Array(cyber crimes, cyber security, review, india, instances, state, issue, civil society, frequency)

现在我正在执行 zipWithIndex 我收到错误

scala> uniquewords.zipWithIndex
17/05/07 09:40:09 ERROR Executor: Exception in task 0.0 in stage 14.0 (TID 17)
java.lang.NullPointerException
    at $line16.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$anonfun$1.apply(<console>:27)
    at $line16.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$anonfun$1.apply(<console>:27)
    at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
    at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434)
    at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
    at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1760)
    at org.apache.spark.rdd.ZippedWithIndexRDD$$anonfun$2.apply(ZippedWithIndexRDD.scala:52)
    at org.apache.spark.rdd.ZippedWithIndexRDD$$anonfun$2.apply(ZippedWithIndexRDD.scala:52)
    at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1944)
    at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1944)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
    at org.apache.spark.scheduler.Task.run(Task.scala:99)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    at java.lang.Thread.run(Thread.java:745)
17/05/07 09:40:09 WARN TaskSetManager: Lost task 0.0 in stage 14.0 (TID 17, localhost, executor driver): java.lang.NullPointerException
    at $line16.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$anonfun$1.apply(<console>:27)
    at $line16.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$anonfun$1.apply(<console>:27)
    at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
    at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434)
    at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
    at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1760)
    at org.apache.spark.rdd.ZippedWithIndexRDD$$anonfun$2.apply(ZippedWithIndexRDD.scala:52)
    at org.apache.spark.rdd.ZippedWithIndexRDD$$anonfun$2.apply(ZippedWithIndexRDD.scala:52)
    at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1944)
    at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1944)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
    at org.apache.spark.scheduler.Task.run(Task.scala:99)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282)
    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)

17/05/07 09:40:09 ERROR TaskSetManager: Task 0 in stage 14.0 failed 1 times; aborting job
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 14.0 failed 1 times, most recent failure: Lost task 0.0 in stage 14.0 (TID 17, localhost, executor driver): java.lang.NullPointerException
    at $anonfun$1.apply(<console>:27)
    at $anonfun$1.apply(<console>:27)
    at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
    at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434)
    at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
    at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1760)
    at org.apache.spark.rdd.ZippedWithIndexRDD$$anonfun$2.apply(ZippedWithIndexRDD.scala:52)
    at org.apache.spark.rdd.ZippedWithIndexRDD$$anonfun$2.apply(ZippedWithIndexRDD.scala:52)
    at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1944)
    at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1944)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
    at org.apache.spark.scheduler.Task.run(Task.scala:99)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282)
    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$$failJobAndIndependentStages(DAGScheduler.scala:1435)
  at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1423)
  at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1422)
  at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
  at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
  at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1422)
  at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
  at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
  at scala.Option.foreach(Option.scala:257)
  at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:802)
  at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1650)
  at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1605)
  at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1594)
  at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
  at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:628)
  at org.apache.spark.SparkContext.runJob(SparkContext.scala:1918)
  at org.apache.spark.SparkContext.runJob(SparkContext.scala:1931)
  at org.apache.spark.SparkContext.runJob(SparkContext.scala:1944)
  at org.apache.spark.rdd.ZippedWithIndexRDD.<init>(ZippedWithIndexRDD.scala:50)
  at org.apache.spark.rdd.RDD$$anonfun$zipWithIndex$1.apply(RDD.scala:1293)
  at org.apache.spark.rdd.RDD$$anonfun$zipWithIndex$1.apply(RDD.scala:1293)
  at org.apache.spark.rdd.RDDOperationScope$.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.zipWithIndex(RDD.scala:1292)
  ... 48 elided
Caused by: java.lang.NullPointerException
  at $anonfun$1.apply(<console>:27)
  at $anonfun$1.apply(<console>:27)
  at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
  at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434)
  at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
  at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1760)
  at org.apache.spark.rdd.ZippedWithIndexRDD$$anonfun$2.apply(ZippedWithIndexRDD.scala:52)
  at org.apache.spark.rdd.ZippedWithIndexRDD$$anonfun$2.apply(ZippedWithIndexRDD.scala:52)
  at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1944)
  at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1944)
  at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
  at org.apache.spark.scheduler.Task.run(Task.scala:99)
  at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282)
  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)

我的问题陈述与this 几乎相似，但我想该解决方案不适用于我。是否有不同的方式来处理MapPartitionsRDD？

Answer 1

MapPartitionsRDD 是从哪里来的，没有任何问题

val rdd = sc.parallelize(Array[Array[String]](Array[String]("cyber", "india", "fourteen"), Array[String]("crime", "india", "twelve")))
rdd.flatMap(_.distinct).zipWithIndex.collect

数组（（网络，0），（印度，1），（十四，2），（犯罪，3），（印度，4），（十二，5））

所以这里肯定有别的东西在起作用。您能否创建一个重现错误的最小工作示例。我猜你的 RDD 中有一些空行应该被过滤掉，当遇到类似的错误时总是这样。那些空行正在产生NullPointerException（我认为），可能是因为试图对它们调用.distinct。该错误是由 anon 函数产生的，这意味着它是您传递给 map 或 flatMap 的一些匿名函数 - 很难准确地说，因为这不是一个完整的示例。

仔细检查您的数据摄取并验证 RDD 是否包含您认为它包含的内容。