Hi Ted,
Unfortunately these two options cause following failure in my environment:
(java.lang.RuntimeException: class
org.apache.hadoop.security.JniBasedUnixGroupsMappingWithFallback not
org.apache.hadoop.security.GroupMappingServiceProvider,java.lang.RuntimeException:
java.lang.RuntimeException: class
org.apache.hadoop.security.JniBasedUnixGroupsMappingWithFallback not
org.apache.hadoop.security.GroupMappingServiceProvider)
2015-10-19 22:23 GMT+08:00 Ted Yu <yuzhih...@gmail.com>:
> 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
>>
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>>
>
--
Yizhi Liu
Senior Software Engineer / Data Mining
www.mvad.com, Shanghai, China
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