1
Je continue à rencontrer quelques bogues étranges tout en utilisant des valeurs différentes pour le paramètre layers [] de MultilayerPerceptronClassifier.MultilayerPerceptronClassifier dans Spark. Calques et erreurs étranges
par exemple. pour les mêmes données:
int[] layers = {100, 98, 2}
new MultilayerPerceptronClassifier().setLayers(layers).setLabelCol(targetColumn).fit(data);
Je reçois: java.lang.ArrayIndexOutOfBoundsException
With stack trace:
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1442)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1441)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1441)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:811)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1667)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1622)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1611)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:632)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1890)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1903)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1916)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1930)
at org.apache.spark.rdd.RDD.count(RDD.scala:1134)
at org.apache.spark.mllib.optimization.LBFGS$.runLBFGS(LBFGS.scala:195)
at org.apache.spark.mllib.optimization.LBFGS.optimize(LBFGS.scala:142)
at org.apache.spark.ml.ann.FeedForwardTrainer.train(Layer.scala:819)
at org.apache.spark.ml.classification.MultilayerPerceptronClassifier.train(MultilayerPerceptronClassifier.scala:262)
at org.apache.spark.ml.classification.MultilayerPerceptronClassifier.train(MultilayerPerceptronClassifier.scala:147)
Maintenant, je passe à
int[] layers = {10,8,2}
tout semble fonctionner. Maintenant, la prochaine tentative est:
int[] layers = {9,6,2}
et a obtenu la sortie qui ont l'air beaucoup plus bizarre:
org.apache.spark.SparkException: Failed to execute user defined function($anonfun$1: (vector) => double)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:246)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:240)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:803)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:803)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
at org.apache.spark.scheduler.Task.run(Task.scala:86)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.IllegalArgumentException: requirement failed: A & B Dimension mismatch!
at scala.Predef$.require(Predef.scala:224)
at org.apache.spark.ml.ann.BreezeUtil$.dgemm(BreezeUtil.scala:41)
at org.apache.spark.ml.ann.AffineLayerModel.eval(Layer.scala:164)
at org.apache.spark.ml.ann.FeedForwardModel.forward(Layer.scala:483)
at org.apache.spark.ml.ann.FeedForwardModel.predict(Layer.scala:530)
at org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel.predict(MultilayerPerceptronClassifier.scala:322)
at org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel.predict(MultilayerPerceptronClassifier.scala:296)
at org.apache.spark.ml.PredictionModel$$anonfun$1.apply(Predictor.scala:187)
at org.apache.spark.ml.PredictionModel$$anonfun$1.apply(Predictor.scala:186)
... 16 more
17/02/08 12:55:34 WARN TaskSetManager: Lost task 0.0 in stage 68.0 (TID 68, localhost): org.apache.spark.SparkException: Failed to execute user defined function($anonfun$1: (vector) => double)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:246)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:240)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:803)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:803)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
at org.apache.spark.scheduler.Task.run(Task.scala:86)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.IllegalArgumentException: requirement failed: A & B Dimension mismatch!
at scala.Predef$.require(Predef.scala:224)
at org.apache.spark.ml.ann.BreezeUtil$.dgemm(BreezeUtil.scala:41)
at org.apache.spark.ml.ann.AffineLayerModel.eval(Layer.scala:164)
at org.apache.spark.ml.ann.FeedForwardModel.forward(Layer.scala:483)
at org.apache.spark.ml.ann.FeedForwardModel.predict(Layer.scala:530)
at org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel.predict(MultilayerPerceptronClassifier.scala:322)
at org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel.predict(MultilayerPerceptronClassifier.scala:296)
at org.apache.spark.ml.PredictionModel$$anonfun$1.apply(Predictor.scala:187)
at org.apache.spark.ml.PredictionModel$$anonfun$1.apply(Predictor.scala:186)
... 16 more
17/02/08 12:55:34 ERROR TaskSetManager: Task 0 in stage 68.0 failed 1 times; aborting job
17/02/08 12:55:34 INFO TaskSchedulerImpl: Removed TaskSet 68.0, whose tasks have all completed, from pool
17/02/08 12:55:34 INFO TaskSchedulerImpl: Cancelling stage 68
17/02/08 12:55:34 INFO DAGScheduler: ResultStage 68 (show at DataPipeline.java:213) failed in 0,910 s
17/02/08 12:55:34 INFO DAGScheduler: Job 67 failed: show at DataPipeline.java:213, took 0,914385 s
Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 68.0 failed 1 times, most recent failure: Lost task 0.0 in stage 68.0 (TID 68, localhost): org.apache.spark.SparkException: Failed to execute user defined function($anonfun$1: (vector) => double)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:246)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:240)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:803)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:803)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
at org.apache.spark.scheduler.Task.run(Task.scala:86)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.IllegalArgumentException: requirement failed: A & B Dimension mismatch!
at scala.Predef$.require(Predef.scala:224)
at org.apache.spark.ml.ann.BreezeUtil$.dgemm(BreezeUtil.scala:41)
at org.apache.spark.ml.ann.AffineLayerModel.eval(Layer.scala:164)
at org.apache.spark.ml.ann.FeedForwardModel.forward(Layer.scala:483)
at org.apache.spark.ml.ann.FeedForwardModel.predict(Layer.scala:530)
at org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel.predict(MultilayerPerceptronClassifier.scala:322)
at org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel.predict(MultilayerPerceptronClassifier.scala:296)
at org.apache.spark.ml.PredictionModel$$anonfun$1.apply(Predictor.scala:187)
at org.apache.spark.ml.PredictionModel$$anonfun$1.apply(Predictor.scala:186)
... 16 more
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1454)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1442)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1441)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1441)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:811)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1667)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1622)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1611)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:632)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1890)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1903)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1916)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:347)
at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:39)
at org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2193)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2546)
at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2192)
at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Dataset.scala:2199)
at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:1935)
at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:1934)
at org.apache.spark.sql.Dataset.withTypedCallback(Dataset.scala:2576)
at org.apache.spark.sql.Dataset.head(Dataset.scala:1934)
at org.apache.spark.sql.Dataset.take(Dataset.scala:2149)
at org.apache.spark.sql.Dataset.showString(Dataset.scala:239)
at org.apache.spark.sql.Dataset.show(Dataset.scala:526)
at org.apache.spark.sql.Dataset.show(Dataset.scala:486)
at org.apache.spark.sql.Dataset.show(Dataset.scala:495)
at org.sparkexample.DataPipeline.trainNeuralNetwork(DataPipeline.java:213)
at org.sparkexample.DataPipeline.selectModel(DataPipeline.java:184)
at org.sparkexample.DataPipeline.main(DataPipeline.java:131)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:736)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:185)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:210)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:124)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: org.apache.spark.SparkException: Failed to execute user defined function($anonfun$1: (vector) => double)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:246)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:240)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:803)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:803)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
at org.apache.spark.scheduler.Task.run(Task.scala:86)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.IllegalArgumentException: requirement failed: A & B Dimension mismatch!
at scala.Predef$.require(Predef.scala:224)
at org.apache.spark.ml.ann.BreezeUtil$.dgemm(BreezeUtil.scala:41)
at org.apache.spark.ml.ann.AffineLayerModel.eval(Layer.scala:164)
at org.apache.spark.ml.ann.FeedForwardModel.forward(Layer.scala:483)
at org.apache.spark.ml.ann.FeedForwardModel.predict(Layer.scala:530)
at org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel.predict(MultilayerPerceptronClassifier.scala:322)
at org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel.predict(MultilayerPerceptronClassifier.scala:296)
at org.apache.spark.ml.PredictionModel$$anonfun$1.apply(Predictor.scala:187)
at org.apache.spark.ml.PredictionModel$$anonfun$1.apply(Predictor.scala:186)
... 16 more
Alors qu'est-ce exactement dois-je passer aux couches. De docs je vois que le dernier paramètre est le nombre de classes, et le reste est un tableau arbitraire de différents neurones.
Le montant réel des caractéristiques que j'ai et passe comme 1 caractéristique vecteur est 9