org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0 (TID 0, localhost): java.lang.NullPointerException

github.com | 5 months ago
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  1. 0

    [jira] [Commented] (SPARK-4785) When called with arguments referring column fields, PMOD throws NPE

    spark-issues | 2 years ago | Apache Spark (JIRA)
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0 (TID 0, localhost): java.lang.NullPointerException
  2. 0

    [jira] [Resolved] (SPARK-4785) When called with arguments referring column fields, PMOD throws NPE

    spark-issues | 2 years ago | Michael Armbrust (JIRA)
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0 (TID 0, localhost): java.lang.NullPointerException
  3. 0

    eco-release-metadata/RELEASENOTES.1.2.0.md at master · aw-was-here/eco-release-metadata · GitHub

    github.com | 5 months ago
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0 (TID 0, localhost): java.lang.NullPointerException
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    Root Cause Analysis

    1. org.apache.spark.SparkException

      Job aborted due to stage failure: Task 0 in stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0 (TID 0, localhost): java.lang.NullPointerException

      at org.apache.hadoop.hive.ql.udf.generic.GenericUDFBaseNumeric.initialize()
    2. Hive Query Language
      GenericUDF.initializeAndFoldConstants
      1. org.apache.hadoop.hive.ql.udf.generic.GenericUDFBaseNumeric.initialize(GenericUDFBaseNumeric.java:109)
      2. org.apache.hadoop.hive.ql.udf.generic.GenericUDF.initializeAndFoldConstants(GenericUDF.java:116)
      2 frames
    3. Spark Project Hive
      HiveGenericUdf.eval
      1. org.apache.spark.sql.hive.HiveGenericUdf.returnInspector$lzycompute(hiveUdfs.scala:156)
      2. org.apache.spark.sql.hive.HiveGenericUdf.returnInspector(hiveUdfs.scala:155)
      3. org.apache.spark.sql.hive.HiveGenericUdf.eval(hiveUdfs.scala:174)
      3 frames
    4. Spark Project Catalyst
      InterpretedMutableProjection.apply
      1. org.apache.spark.sql.catalyst.expressions.Alias.eval(namedExpressions.scala:92)
      2. org.apache.spark.sql.catalyst.expressions.InterpretedMutableProjection.apply(Projection.scala:68)
      3. org.apache.spark.sql.catalyst.expressions.InterpretedMutableProjection.apply(Projection.scala:52)
      3 frames
    5. Scala
      AbstractIterator.toArray
      1. scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
      2. scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
      3. scala.collection.Iterator$$anon$10.next(Iterator.scala:312)
      4. scala.collection.Iterator$class.foreach(Iterator.scala:727)
      5. scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
      6. scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
      7. scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
      8. scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
      9. scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
      10. scala.collection.AbstractIterator.to(Iterator.scala:1157)
      11. scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
      12. scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
      13. scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
      14. scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
      14 frames
    6. Spark Project SQL
      Limit$$anonfun$4.apply
      1. org.apache.spark.sql.execution.Limit$$anonfun$4.apply(basicOperators.scala:141)
      2. org.apache.spark.sql.execution.Limit$$anonfun$4.apply(basicOperators.scala:141)
      2 frames
    7. Spark
      Executor$TaskRunner.run
      1. org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1314)
      2. org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1314)
      3. org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
      4. org.apache.spark.scheduler.Task.run(Task.scala:56)
      5. org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:196)
      5 frames
    8. Java RT
      Thread.run
      1. java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
      2. java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
      3. java.lang.Thread.run(Thread.java:745)
      3 frames