org.apache.spark.SparkException: Job aborted due to stage failure: Task 2 in stage 2.0 failed 1 times, most recent failure: Lost task 2.0 in stage 2.0 (TID 11, localhost): ml.dmlc.xgboost4j.java.XGBoostError: [14:43:22] src/metric/elementwise_metric.cc:28: Check failed: (preds.size()) == (info.labels.size()) label and prediction size not match, hint: use merror or mlogloss for multi-class classification

GitHub | geoHeil | 7 months ago
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  1. 0

    xgboost 4j spark test failure version v0.6.0

    GitHub | 7 months ago | geoHeil
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 2 in stage 2.0 failed 1 times, most recent failure: Lost task 2.0 in stage 2.0 (TID 11, localhost): ml.dmlc.xgboost4j.java.XGBoostError: [14:43:22] src/metric/elementwise_metric.cc:28: Check failed: (preds.size()) == (info.labels.size()) label and prediction size not match, hint: use merror or mlogloss for multi-class classification
  2. 0

    RE: Not Serializable exception when integrating SQL and Spark Streaming

    apache.org | 2 years ago
    org.apache.spark.SparkException: Task not serializable at org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:166) at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:158) at org.apache.spark.SparkContext.clean(SparkContext.scala:1435) at org.apache.spark.rdd.RDD.map(RDD.scala:271) at org.apache.spark.api.java.JavaRDDLike$class.map(JavaRDDLike.scala:78) at org.apache.spark.sql.api.java.JavaSchemaRDD.map(JavaSchemaRDD.scala:42) at com.basic.spark.NumberCount$2.call(NumberCount.java:79) at com.basic.spark.NumberCount$2.call(NumberCount.java:67) at org.apache.spark.streaming.api.java.JavaDStreamLike$anonfun$foreachRDD$1.apply(JavaDStreamLike.scala:274) at org.apache.spark.streaming.api.java.JavaDStreamLike$anonfun$foreachRDD$1.apply(JavaDStreamLike.scala:274) at org.apache.spark.streaming.dstream.DStream$anonfun$foreachRDD$1.apply(DStream.scala:529) at org.apache.spark.streaming.dstream.DStream$anonfun$foreachRDD$1.apply(DStream.scala:529) at org.apache.spark.streaming.dstream.ForEachDStream$anonfun$1.apply$mcV$sp(ForEachDStream.scala:42) at org.apache.spark.streaming.dstream.ForEachDStream$anonfun$1.apply(ForEachDStream.scala:40) at org.apache.spark.streaming.dstream.ForEachDStream$anonfun$1.apply(ForEachDStream.scala:40) at scala.util.Try$.apply(Try.scala:161) at org.apache.spark.streaming.scheduler.Job.run(Job.scala:32) at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler.run(JobScheduler.scala:171) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
  3. 0

    RE: Not Serializable exception when integrating SQL and Spark Streaming

    apache.org | 1 year ago
    org.apache.spark.SparkException: Task not serializable at org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:166) at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:158) at org.apache.spark.SparkContext.clean(SparkContext.scala:1435) at org.apache.spark.rdd.RDD.map(RDD.scala:271) at org.apache.spark.api.java.JavaRDDLike$class.map(JavaRDDLike.scala:78) at org.apache.spark.sql.api.java.JavaSchemaRDD.map(JavaSchemaRDD.scala:42) at com.basic.spark.NumberCount$2.call(NumberCount.java:79) at com.basic.spark.NumberCount$2.call(NumberCount.java:67) at org.apache.spark.streaming.api.java.JavaDStreamLike$anonfun$foreachRDD$1.apply(JavaDStreamLike.scala:274) at org.apache.spark.streaming.api.java.JavaDStreamLike$anonfun$foreachRDD$1.apply(JavaDStreamLike.scala:274) at org.apache.spark.streaming.dstream.DStream$anonfun$foreachRDD$1.apply(DStream.scala:529) at org.apache.spark.streaming.dstream.DStream$anonfun$foreachRDD$1.apply(DStream.scala:529) at org.apache.spark.streaming.dstream.ForEachDStream$anonfun$1.apply$mcV$sp(ForEachDStream.scala:42) at org.apache.spark.streaming.dstream.ForEachDStream$anonfun$1.apply(ForEachDStream.scala:40) at org.apache.spark.streaming.dstream.ForEachDStream$anonfun$1.apply(ForEachDStream.scala:40) at scala.util.Try$.apply(Try.scala:161) at org.apache.spark.streaming.scheduler.Job.run(Job.scala:32) at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler.run(JobScheduler.scala:171) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
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    Root Cause Analysis

    1. org.apache.spark.SparkException

      Job aborted due to stage failure: Task 2 in stage 2.0 failed 1 times, most recent failure: Lost task 2.0 in stage 2.0 (TID 11, localhost): ml.dmlc.xgboost4j.java.XGBoostError: [14:43:22] src/metric/elementwise_metric.cc:28: Check failed: (preds.size()) == (info.labels.size()) label and prediction size not match, hint: use merror or mlogloss for multi-class classification

      at ml.dmlc.xgboost4j.java.JNIErrorHandle.checkCall()
    2. ml.dmlc.xgboost4j
      XGBoostModel$$anonfun$1.apply
      1. ml.dmlc.xgboost4j.java.JNIErrorHandle.checkCall(JNIErrorHandle.java:48)
      2. ml.dmlc.xgboost4j.java.Booster.evalSet(Booster.java:178)
      3. ml.dmlc.xgboost4j.scala.Booster.evalSet(Booster.scala:97)
      4. ml.dmlc.xgboost4j.scala.spark.XGBoostModel$$anonfun$1.apply(XGBoostModel.scala:80)
      5. ml.dmlc.xgboost4j.scala.spark.XGBoostModel$$anonfun$1.apply(XGBoostModel.scala:62)
      5 frames
    3. Spark
      Executor$TaskRunner.run
      1. org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:766)
      2. org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:766)
      3. org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
      4. org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
      5. org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
      6. org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
      7. org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
      8. org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
      9. org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
      10. org.apache.spark.scheduler.Task.run(Task.scala:85)
      11. org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
      11 frames
    4. 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