scheduler.TaskSetManager: Lost task 2.0 in stage 0.0 (TID 2, euw1z1pl004): org.apache.spark.SparkException: Task failed while writing rows.

GitHub | wwinnicki | 3 months ago
  1. 0

    NumberFormatException when reading NaN value

    GitHub | 3 months ago | wwinnicki
    scheduler.TaskSetManager: Lost task 2.0 in stage 0.0 (TID 2, euw1z1pl004): org.apache.spark.SparkException: Task failed while writing rows.
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    Stack Overflow | 4 years ago | fbl
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    Stack Overflow | 3 years ago | Tanny
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Root Cause Analysis

  1. java.lang.NumberFormatException

    For input string: "nan"

    at sun.misc.FloatingDecimal.readJavaFormatString()
  2. Java RT
    Double.parseDouble
    1. sun.misc.FloatingDecimal.readJavaFormatString(FloatingDecimal.java:2043)
    2. sun.misc.FloatingDecimal.parseDouble(FloatingDecimal.java:110)
    3. java.lang.Double.parseDouble(Double.java:538)
    3 frames
  3. Scala
    StringOps.toDouble
    1. scala.collection.immutable.StringLike$class.toDouble(StringLike.scala:232)
    2. scala.collection.immutable.StringOps.toDouble(StringOps.scala:31)
    2 frames
  4. com.databricks.spark
    Conversions$$anonfun$createRowConverter$1.apply
    1. com.databricks.spark.redshift.Conversions$$anonfun$1$$anonfun$apply$4.apply(Conversions.scala:87)
    2. com.databricks.spark.redshift.Conversions$$anonfun$1$$anonfun$apply$4.apply(Conversions.scala:87)
    3. com.databricks.spark.redshift.Conversions$$anonfun$createRowConverter$1.apply(Conversions.scala:105)
    4. com.databricks.spark.redshift.Conversions$$anonfun$createRowConverter$1.apply(Conversions.scala:101)
    4 frames
  5. Scala
    Iterator$$anon$11.next
    1. scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
    2. scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
    3. scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
    3 frames
  6. org.apache.spark
    InsertIntoHadoopFsRelation$$anonfun$run$1$$anonfun$apply$mcV$sp$3.apply
    1. org.apache.spark.sql.execution.datasources.DefaultWriterContainer.writeRows(WriterContainer.scala:263)
    2. org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1$$anonfun$apply$mcV$sp$3.apply(InsertIntoHadoopFsRelation.scala:150)
    3. org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1$$anonfun$apply$mcV$sp$3.apply(InsertIntoHadoopFsRelation.scala:150)
    3 frames
  7. Spark
    Executor$TaskRunner.run
    1. org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
    2. org.apache.spark.scheduler.Task.run(Task.scala:89)
    3. org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
    3 frames
  8. Java RT
    Thread.run
    1. java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    2. java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    3. java.lang.Thread.run(Thread.java:745)
    3 frames