Thanks Jacob, I've looked into the source code here and found that I miss this property there: spark.repl.class.uri
Putting it solved the problem Cheers 2016-03-17 18:14 GMT-03:00 Jakob Odersky <ja...@odersky.com>: > The error is very strange indeed, however without code that reproduces > it, we can't really provide much help beyond speculation. > > One thing that stood out to me immediately is that you say you have an > RDD of Any where every Any should be a BigDecimal, so why not specify > that type information? > When using Any, a whole class of errors, that normally the typechecker > could catch, can slip through. > > On Thu, Mar 17, 2016 at 10:25 AM, Dirceu Semighini Filho > <dirceu.semigh...@gmail.com> wrote: > > Hi Ted, thanks for answering. > > The map is just that, whenever I try inside the map it throws this > > ClassNotFoundException, even if I do map(f => f) it throws the exception. > > What is bothering me is that when I do a take or a first it returns the > > result, which make me conclude that the previous code isn't wrong. > > > > Kind Regards, > > Dirceu > > > > > > 2016-03-17 12:50 GMT-03:00 Ted Yu <yuzhih...@gmail.com>: > >> > >> bq. $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1 > >> > >> Do you mind showing more of your code involving the map() ? > >> > >> On Thu, Mar 17, 2016 at 8:32 AM, Dirceu Semighini Filho > >> <dirceu.semigh...@gmail.com> wrote: > >>> > >>> Hello, > >>> I found a strange behavior after executing a prediction with MLIB. > >>> My code return an RDD[(Any,Double)] where Any is the id of my dataset, > >>> which is BigDecimal, and Double is the prediction for that line. > >>> When I run > >>> myRdd.take(10) it returns ok > >>> res16: Array[_ >: (Double, Double) <: (Any, Double)] = > >>> Array((1921821857196754403.000000000000000000,0.1690292052496703), > >>> (4545756323742222427.000000000000000000,0.16902820241892452), > >>> (989198096568001939.000000000000000000,0.16903432789699502), > >>> (14284129652106187990.000000000000000000,0.16903517653451386), > >>> (17980228074225252497.000000000000000000,0.16903151028332508), > >>> (3861345958263692781.000000000000000000,0.16903056986183976), > >>> (17558198701997383205.000000000000000000,0.1690295450319745), > >>> (10651576092054552310.000000000000000000,0.1690286445174418), > >>> (4534494349035056215.000000000000000000,0.16903303401862327), > >>> (5551671513234217935.000000000000000000,0.16902303368995966)) > >>> But when I try to run some map on it: > >>> myRdd.map(_._1).take(10) > >>> It throws a ClassCastException: > >>> org.apache.spark.SparkException: Job aborted due to stage failure: > Task 0 > >>> in stage 72.0 failed 4 times, most recent failure: Lost task 0.3 in > stage > >>> 72.0 (TID 1774, 172.31.23.208): java.lang.ClassNotFoundException: > >>> $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1 > >>> at java.net.URLClassLoader$1.run(URLClassLoader.java:366) > >>> at java.net.URLClassLoader$1.run(URLClassLoader.java:355) > >>> at java.security.AccessController.doPrivileged(Native Method) > >>> at java.net.URLClassLoader.findClass(URLClassLoader.java:354) > >>> at java.lang.ClassLoader.loadClass(ClassLoader.java:425) > >>> at java.lang.ClassLoader.loadClass(ClassLoader.java:358) > >>> at java.lang.Class.forName0(Native Method) > >>> at java.lang.Class.forName(Class.java:278) > >>> at > >>> > org.apache.spark.serializer.JavaDeserializationStream$$anon$1.resolveClass(JavaSerializer.scala:67) > >>> at > >>> java.io.ObjectInputStream.readNonProxyDesc(ObjectInputStream.java:1612) > >>> at java.io.ObjectInputStream.readClassDesc(ObjectInputStream.java:1517) > >>> at > >>> > java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1771) > >>> at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350) > >>> at > >>> > java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1997) > >>> at > java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1921) > >>> at > >>> > java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798) > >>> at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350) > >>> at > >>> > java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1997) > >>> at > java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1921) > >>> at > >>> > java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798) > >>> at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350) > >>> at > >>> > java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1997) > >>> at > java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1921) > >>> at > >>> > java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798) > >>> at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350) > >>> at java.io.ObjectInputStream.readObject(ObjectInputStream.java:370) > >>> at > >>> > org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:72) > >>> at > >>> > org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:98) > >>> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61) > >>> at org.apache.spark.scheduler.Task.run(Task.scala:88) > >>> at > org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214) > >>> at > >>> > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) > >>> at > >>> > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) > >>> at java.lang.Thread.run(Thread.java:745) > >>> Driver stacktrace: > >>> at > >>> org.apache.spark.scheduler.DAGScheduler.org > $apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1283) > >>> at > >>> > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1271) > >>> at > >>> > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1270) > >>> at > >>> > scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) > >>> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) > >>> at > >>> > org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1270) > >>> at > >>> > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:697) > >>> at > >>> > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:697) > >>> at scala.Option.foreach(Option.scala:236) > >>> at > >>> > org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:697) > >>> at > >>> > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1496) > >>> at > >>> > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1458) > >>> at > >>> > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1447) > >>> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) > >>> at > org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:567) > >>> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1824) > >>> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1837) > >>> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1850) > >>> at org.apache.spark.rdd.RDD$$anonfun$take$1.apply(RDD.scala:1302) > >>> at > >>> > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147) > >>> at > >>> > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108) > >>> at org.apache.spark.rdd.RDD.withScope(RDD.scala:310) > >>> at org.apache.spark.rdd.RDD.take(RDD.scala:1276) > >>> at org.apache.spark.rdd.RDD$$anonfun$first$1.apply(RDD.scala:1316) > >>> at > >>> > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147) > >>> at > >>> > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108) > >>> at org.apache.spark.rdd.RDD.withScope(RDD.scala:310) > >>> at org.apache.spark.rdd.RDD.first(RDD.scala:1315) > >>> at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:34) > >>> at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:39) > >>> at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:41) > >>> at $iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:43) > >>> at $iwC$$iwC$$iwC$$iwC.<init>(<console>:45) > >>> at $iwC$$iwC$$iwC.<init>(<console>:47) > >>> at $iwC$$iwC.<init>(<console>:49) > >>> at $iwC.<init>(<console>:51) > >>> at <init>(<console>:53) > >>> at .<init>(<console>:57) > >>> at .<clinit>(<console>) > >>> at .<init>(<console>:7) > >>> at .<clinit>(<console>) > >>> at $print(<console>) > >>> 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:497) > >>> at > >>> > org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:1065) > >>> at > >>> > org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1340) > >>> at > org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:840) > >>> at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:871) > >>> at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:819) > >>> at > >>> > org.apache.zeppelin.spark.IUberSparkInterpreter.interpretInput(IUberSparkInterpreter.java:865) > >>> at > >>> > org.apache.zeppelin.spark.IUberSparkInterpreter.interpret(IUberSparkInterpreter.java:830) > >>> at > >>> > org.apache.zeppelin.spark.IUberSparkInterpreter.interpret(IUberSparkInterpreter.java:818) > >>> at > >>> > org.apache.zeppelin.interpreter.ClassloaderInterpreter.interpret(ClassloaderInterpreter.java:57) > >>> at > >>> > org.apache.zeppelin.interpreter.LazyOpenInterpreter.interpret(LazyOpenInterpreter.java:93) > >>> at > >>> > org.apache.zeppelin.interpreter.remote.RemoteInterpreterServer$InterpretJob.jobRun(RemoteInterpreterServer.java:331) > >>> at org.apache.zeppelin.scheduler.Job.run(Job.java:171) > >>> at > >>> > org.apache.zeppelin.scheduler.FIFOScheduler$1.run(FIFOScheduler.java:139) > >>> at > >>> java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511) > >>> at java.util.concurrent.FutureTask.run(FutureTask.java:266) > >>> at > >>> > java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$201(ScheduledThreadPoolExecutor.java:180) > >>> at > >>> > java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:293) > >>> 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.ClassNotFoundException: > >>> $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1 > >>> at java.net.URLClassLoader$1.run(URLClassLoader.java:366) > >>> at java.net.URLClassLoader$1.run(URLClassLoader.java:355) > >>> at java.security.AccessController.doPrivileged(Native Method) > >>> at java.net.URLClassLoader.findClass(URLClassLoader.java:354) > >>> at java.lang.ClassLoader.loadClass(ClassLoader.java:425) > >>> at java.lang.ClassLoader.loadClass(ClassLoader.java:358) > >>> at java.lang.Class.forName0(Native Method) > >>> at java.lang.Class.forName(Class.java:278) > >>> at > >>> > org.apache.spark.serializer.JavaDeserializationStream$$anon$1.resolveClass(JavaSerializer.scala:67) > >>> at > >>> java.io.ObjectInputStream.readNonProxyDesc(ObjectInputStream.java:1612) > >>> at java.io.ObjectInputStream.readClassDesc(ObjectInputStream.java:1517) > >>> at > >>> > java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1771) > >>> at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350) > >>> at > >>> > java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1997) > >>> at > java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1921) > >>> at > >>> > java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798) > >>> at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350) > >>> at > >>> > java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1997) > >>> at > java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1921) > >>> at > >>> > java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798) > >>> at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350) > >>> at > >>> > java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1997) > >>> at > java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1921) > >>> at > >>> > java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798) > >>> at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350) > >>> at java.io.ObjectInputStream.readObject(ObjectInputStream.java:370) > >>> at > >>> > org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:72) > >>> at > >>> > org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:98) > >>> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61) > >>> at org.apache.spark.scheduler.Task.run(Task.scala:88) > >>> at > org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214) > >>> at > >>> > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) > >>> at > >>> > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) > >>> ... 1 more > >>> > >>> I'm using spark 1.5.2 compiled with hadoop 2.6. > >>> Does anybody know how to avoid this exception? > >>> > >>> Kind Regards, > >>> Dirceu > >> > >> > > >
