org.apache.spark.SparkException: Items in a transaction must be unique but got WrappedArray(13873775, 4, 99, 9909, 102113020, 15704, 2012-03-19:00, 6.25, OZ, 4, 11.96).

Data Science | SaCvP | 3 months ago
  1. 0

    Items in a transaction must be unique but got WrappedArray

    Data Science | 3 months ago | SaCvP
    org.apache.spark.SparkException: Items in a transaction must be unique but got WrappedArray(13873775, 4, 99, 9909, 102113020, 15704, 2012-03-19:00, 6.25, OZ, 4, 11.96).
  2. 0

    Drop elements with malformatted Strings for TimestampType in DROPMALFORMED

    GitHub | 1 year ago | fabboe
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 399 in stage 7.0 failed 4 times, most recent failure: Lost task 399.3 in stage 7.0 (TID 1337, worker03): java.lang.IllegalArgumentException: Timestamp format must be yyyy-mm-dd hh:mm:ss[.fffffffff]
  3. 0

    SparkException: A master URL must be set in your configuration

    GitHub | 1 year ago | nano4711
    org.apache.spark.SparkException: A master URL must be set in your configuration
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  5. 0

    GitHub comment 1#155710976

    GitHub | 1 year ago | Juliana123
    org.apache.spark.SparkException: A master URL must be set in your configuration
  6. 0

    Simple PySpark regression fails because of scala.MatchError on Spark 2.0?

    Stack Overflow | 3 months ago | Patrick McCarthy
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 19 in stage 188.0 failed 4 times, most recent failure: Lost task 19.3 in stage 188.0 (TID 375286, rs119.hadoop.pvt): scala.MatchError: [25,1.0,(5,[1],[1.0])] (of class org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema)

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    Root Cause Analysis

    1. org.apache.spark.SparkException

      Items in a transaction must be unique but got WrappedArray(13873775, 4, 99, 9909, 102113020, 15704, 2012-03-19:00, 6.25, OZ, 4, 11.96).

      at org.apache.spark.mllib.fpm.FPGrowth$$anonfun$1.apply()
    2. org.apache.spark
      FPGrowth$$anonfun$1.apply
      1. org.apache.spark.mllib.fpm.FPGrowth$$anonfun$1.apply(FPGrowth.scala:143)
      2. org.apache.spark.mllib.fpm.FPGrowth$$anonfun$1.apply(FPGrowth.scala:140)
      2 frames
    3. Scala
      Iterator$$anon$11.hasNext
      1. scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
      2. scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
      2 frames
    4. Spark
      Executor$TaskRunner.run
      1. org.apache.spark.util.collection.ExternalSorter.insertAll(ExternalSorter.scala:189)
      2. org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:64)
      3. org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
      4. org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
      5. org.apache.spark.scheduler.Task.run(Task.scala:89)
      6. org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
      6 frames
    5. Java RT
      Thread.run
      1. java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
      2. java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
      3. java.lang.Thread.run(Thread.java:745)
      3 frames