Have you tried the following options ? --conf spark.driver.userClassPathFirst=true --conf spark.executor. userClassPathFirst=true
Cheers On Mon, Oct 19, 2015 at 5:07 AM, YiZhi Liu <javeli...@gmail.com> wrote: > I'm trying to read a Thrift object from SequenceFile, using > elephant-bird's ThriftWritable. My code looks like > > val rawData = sc.sequenceFile[BooleanWritable, > ThriftWritable[TrainingSample]](input) > val samples = rawData.map { case (key, value) => { > value.setConverter(classOf[TrainingSample]) > val conversion = if (key.get) 1 else 0 > val sample = value.get > (conversion, sample) > }} > > When I spark-submit in local mode, it failed with > > (Job aborted due to stage failure: Task 0 in stage 1.0 failed 1 times, > most recent failure: Lost task 0.0 in stage 1.0 (TID 2, localhost): > java.lang.AbstractMethodError: > > org.apache.thrift.TUnion.standardSchemeReadValue(Lorg/apache/thrift/protocol/TProtocol;Lorg/apache/thrift/protocol/TField;)Ljava/lang/Object; > ... ... > > I'm pretty sure it is caused by the conflict of libthrift, I use > thrift-0.6.1 while spark uses 0.9.2, which requires TUnion object to > implement the abstract 'standardSchemeReadValue' method. > > But when I set spark.files.userClassPathFirst=true, it failed even earlier: > > (Job aborted due to stage failure: Task 1 in stage 0.0 failed 1 times, > most recent failure: Lost task 1.0 in stage 0.0 (TID 1, localhost): > java.lang.ClassCastException: cannot assign instance of scala.None$ to > field org.apache.spark.scheduler.Task.metrics of type scala.Option in > instance of org.apache.spark.scheduler.ResultTask > at > java.io.ObjectStreamClass$FieldReflector.setObjFieldValues(ObjectStreamClass.java:2089) > at java.io.ObjectStreamClass.setObjFieldValues(ObjectStreamClass.java:1261) > at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2006) > at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924) > at > java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801) > at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351) > at java.io.ObjectInputStream.readObject(ObjectInputStream.java:371) > at > org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:69) > at > org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:95) > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:194) > 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) > > It seems I introduced more conflict, but I couldn't figure out which > one caused this failure. > > Interestingly, when I ran mvn test in my project, which test spark job > in locally mode, all worked fine. > > So what is the right way to take user jars precedence over Spark jars? > > -- > Yizhi Liu > Senior Software Engineer / Data Mining > www.mvad.com, Shanghai, China > > --------------------------------------------------------------------- > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org > For additional commands, e-mail: user-h...@spark.apache.org > >