java.lang.IllegalArgumentException: requirement failed: Decimal precision 35 exceeds max precision 20

GitHub | crazylab | 4 months ago
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    java.lang.IllegalArgumentException: requirement failed: Decimal precision 35 exceeds max precision 20

    GitHub | 4 months ago | crazylab
    java.lang.IllegalArgumentException: requirement failed: Decimal precision 35 exceeds max precision 20
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    java.lang.IllegalArgumentException: requirement failed: No output operations registered, so nothing to execute
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Root Cause Analysis

  1. java.lang.IllegalArgumentException

    requirement failed: Decimal precision 35 exceeds max precision 20

    at scala.Predef$.require()
  2. Scala
    Predef$.require
    1. scala.Predef$.require(Predef.scala:233)
    1 frame
  3. org.apache.spark
    CSVFileFormat$$anonfun$buildReader$1$$anonfun$apply$1.apply
    1. org.apache.spark.sql.types.Decimal.set(Decimal.scala:112)
    2. org.apache.spark.sql.types.Decimal$.apply(Decimal.scala:405)
    3. org.apache.spark.sql.execution.datasources.csv.CSVTypeCast$.castTo(CSVInferSchema.scala:278)
    4. org.apache.spark.sql.execution.datasources.csv.CSVRelation$$anonfun$csvParser$3.apply(CSVRelation.scala:115)
    5. org.apache.spark.sql.execution.datasources.csv.CSVRelation$$anonfun$csvParser$3.apply(CSVRelation.scala:84)
    6. org.apache.spark.sql.execution.datasources.csv.CSVFileFormat$$anonfun$buildReader$1$$anonfun$apply$1.apply(CSVFileFormat.scala:125)
    7. org.apache.spark.sql.execution.datasources.csv.CSVFileFormat$$anonfun$buildReader$1$$anonfun$apply$1.apply(CSVFileFormat.scala:124)
    7 frames
  4. Scala
    Iterator$$anon$11.hasNext
    1. scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
    2. scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
    2 frames
  5. org.apache.spark
    FileScanRDD$$anon$1.hasNext
    1. org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:91)
    1 frame
  6. Spark Project Catalyst
    GeneratedClass$GeneratedIterator.processNext
    1. org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithoutKey$(Unknown Source)
    2. org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
    2 frames
  7. Spark Project SQL
    WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext
    1. org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
    2. org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370)
    2 frames
  8. Scala
    Iterator$$anon$11.hasNext
    1. scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
    1 frame
  9. Spark
    Executor$TaskRunner.run
    1. org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125)
    2. org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79)
    3. org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47)
    4. org.apache.spark.scheduler.Task.run(Task.scala:85)
    5. org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
    5 frames
  10. Java RT
    Thread.run
    1. java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
    2. java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
    3. java.lang.Thread.run(Thread.java:745)
    3 frames