org.apache.spark.SparkException: Job aborted due to stage failure: Task 2 in stage 6.0 failed 1 times, most recent failure: Lost task 2.0 in stage 6.0 (TID 42, localhost): java.lang.NoSuchMethodError: breeze.linalg.sum$.sumSummableThings(Lscala/Predef$$less$colon$less;Lbreeze/generic/UFunc$UImpl2;)Lbreeze/generic/UFunc$UImpl;

GitHub | ryan-williams | 6 months ago
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  1. 0

    Breeze NoSuchMethodError

    GitHub | 6 months ago | ryan-williams
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 2 in stage 6.0 failed 1 times, most recent failure: Lost task 2.0 in stage 6.0 (TID 42, localhost): java.lang.NoSuchMethodError: breeze.linalg.sum$.sumSummableThings(Lscala/Predef$$less$colon$less;Lbreeze/generic/UFunc$UImpl2;)Lbreeze/generic/UFunc$UImpl;
  2. 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)
  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 6.0 failed 1 times, most recent failure: Lost task 2.0 in stage 6.0 (TID 42, localhost): java.lang.NoSuchMethodError: breeze.linalg.sum$.sumSummableThings(Lscala/Predef$$less$colon$less;Lbreeze/generic/UFunc$UImpl2;)Lbreeze/generic/UFunc$UImpl;

      at org.hammerlab.guacamole.likelihood.Likelihood$$anonfun$4.apply()
    2. org.hammerlab.guacamole
      Likelihood$$anonfun$4.apply
      1. org.hammerlab.guacamole.likelihood.Likelihood$$anonfun$4.apply(Likelihood.scala:161)
      2. org.hammerlab.guacamole.likelihood.Likelihood$$anonfun$4.apply(Likelihood.scala:156)
      2 frames
    3. Scala
      ArrayOps$ofRef.map
      1. scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
      2. scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
      3. scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
      4. scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
      5. scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
      6. scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:108)
      6 frames
    4. org.hammerlab.guacamole
      WindowFlatMapUtils$$anonfun$splitPartitionByContigAndMap$2.apply
      1. org.hammerlab.guacamole.likelihood.Likelihood$.likelihoodsOfGenotypes(Likelihood.scala:156)
      2. org.hammerlab.guacamole.likelihood.Likelihood$.likelihoodsOfAllPossibleGenotypesFromPileup(Likelihood.scala:78)
      3. org.hammerlab.guacamole.commands.SomaticStandard$Caller$.findPotentialVariantAtLocus(SomaticStandardCaller.scala:182)
      4. org.hammerlab.guacamole.commands.SomaticStandard$Caller$$anonfun$1.apply(SomaticStandardCaller.scala:95)
      5. org.hammerlab.guacamole.commands.SomaticStandard$Caller$$anonfun$1.apply(SomaticStandardCaller.scala:94)
      6. org.hammerlab.guacamole.distributed.PileupFlatMapUtils$$anonfun$pileupFlatMapTwoSamples$1.apply(PileupFlatMapUtils.scala:84)
      7. org.hammerlab.guacamole.distributed.PileupFlatMapUtils$$anonfun$pileupFlatMapTwoSamples$1.apply(PileupFlatMapUtils.scala:79)
      8. org.hammerlab.guacamole.distributed.WindowFlatMapUtils$$anonfun$windowFlatMapWithState$1$$anonfun$apply$1.apply(WindowFlatMapUtils.scala:65)
      9. org.hammerlab.guacamole.distributed.WindowFlatMapUtils$$anonfun$windowFlatMapWithState$1$$anonfun$apply$1.apply(WindowFlatMapUtils.scala:55)
      10. org.hammerlab.guacamole.distributed.WindowFlatMapUtils$$anonfun$splitPartitionByContigAndMap$2.apply(WindowFlatMapUtils.scala:141)
      11. org.hammerlab.guacamole.distributed.WindowFlatMapUtils$$anonfun$splitPartitionByContigAndMap$2.apply(WindowFlatMapUtils.scala:131)
      11 frames
    5. Scala
      Iterator$$anon$13.hasNext
      1. scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
      1 frame
    6. Spark
      Executor$TaskRunner.run
      1. org.apache.spark.storage.MemoryStore.unrollSafely(MemoryStore.scala:284)
      2. org.apache.spark.CacheManager.putInBlockManager(CacheManager.scala:171)
      3. org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:78)
      4. org.apache.spark.rdd.RDD.iterator(RDD.scala:268)
      5. org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
      6. org.apache.spark.scheduler.Task.run(Task.scala:89)
      7. org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
      7 frames
    7. Java RT
      Thread.run
      1. java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
      2. java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
      3. java.lang.Thread.run(Thread.java:745)
      3 frames