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From Davies Liu <dav...@databricks.com>
Subject Re: Error when Applying schema to a dictionary with a Tuple as key
Date Tue, 16 Dec 2014 20:44:38 GMT
It's a bug, could you file a JIRA for this? thanks!

On Tue, Dec 16, 2014 at 5:49 AM, sahanbull <sahan@skimlinks.com> wrote:
>
> Hi Guys,
>
> Im running a spark cluster in AWS with Spark 1.1.0 in EC2
>
> I am trying to convert a an RDD with tuple
>
> (u'string', int , {(int, int): int, (int, int): int})
>
> to a schema rdd using the schema:
>
> fields = [StructField('field1',StringType(),True),
>                 StructField('field2',IntegerType(),True),
>
> StructField('field3',MapType(StructType([StructField('field31',IntegerType(),True),
>                         StructField('field32',IntegerType(),True)]),IntegerType(),True),True)
>                 ]
>
> schema = StructType(fields)
> # generate the schemaRDD with the defined schema
> schemaRDD = sqc.applySchema(RDD, schema)
>
> But when I add "field3" to the schema, it throws an execption:
>
> Traceback (most recent call last):
>   File "<stdin>", line 1, in <module>
>   File "/root/spark/python/pyspark/rdd.py", line 1153, in take
>     res = self.context.runJob(self, takeUpToNumLeft, p, True)
>   File "/root/spark/python/pyspark/context.py", line 770, in runJob
>     it = self._jvm.PythonRDD.runJob(self._jsc.sc(), mappedRDD._jrdd,
> javaPartitions, allowLocal)
>   File "/root/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py",
> line 538, in __call__
>   File "/root/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py", line
> 300, in get_return_value
> py4j.protocol.Py4JJavaError: An error occurred while calling
> z:org.apache.spark.api.python.PythonRDD.runJob.
> : org.apache.spark.SparkException: Job aborted due to stage failure: Task 0
> in stage 28.0 failed 4 times, most recent failure: Lost task 0.3 in stage
> 28.0 (TID 710, ip-172-31-29-120.ec2.internal):
> net.razorvine.pickle.PickleException: couldn't introspect javabean:
> java.lang.IllegalArgumentException: wrong number of arguments
>         net.razorvine.pickle.Pickler.put_javabean(Pickler.java:603)
>         net.razorvine.pickle.Pickler.dispatch(Pickler.java:299)
>         net.razorvine.pickle.Pickler.save(Pickler.java:125)
>         net.razorvine.pickle.Pickler.put_map(Pickler.java:321)
>         net.razorvine.pickle.Pickler.dispatch(Pickler.java:286)
>         net.razorvine.pickle.Pickler.save(Pickler.java:125)
>         net.razorvine.pickle.Pickler.put_arrayOfObjects(Pickler.java:412)
>         net.razorvine.pickle.Pickler.dispatch(Pickler.java:195)
>         net.razorvine.pickle.Pickler.save(Pickler.java:125)
>         net.razorvine.pickle.Pickler.put_arrayOfObjects(Pickler.java:412)
>         net.razorvine.pickle.Pickler.dispatch(Pickler.java:195)
>         net.razorvine.pickle.Pickler.save(Pickler.java:125)
>         net.razorvine.pickle.Pickler.dump(Pickler.java:95)
>         net.razorvine.pickle.Pickler.dumps(Pickler.java:80)
>
> org.apache.spark.sql.SchemaRDD$$anonfun$javaToPython$1$$anonfun$apply$2.apply(SchemaRDD.scala:417)
>
> org.apache.spark.sql.SchemaRDD$$anonfun$javaToPython$1$$anonfun$apply$2.apply(SchemaRDD.scala:417)
>         scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
>
> org.apache.spark.api.python.PythonRDD$.writeIteratorToStream(PythonRDD.scala:331)
>
> org.apache.spark.api.python.PythonRDD$WriterThread$$anonfun$run$1.apply$mcV$sp(PythonRDD.scala:209)
>
> org.apache.spark.api.python.PythonRDD$WriterThread$$anonfun$run$1.apply(PythonRDD.scala:184)
>
> org.apache.spark.api.python.PythonRDD$WriterThread$$anonfun$run$1.apply(PythonRDD.scala:184)
>         org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1311)
>
> org.apache.spark.api.python.PythonRDD$WriterThread.run(PythonRDD.scala:183)
> Driver stacktrace:
>         at
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1185)
>         at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1174)
>         at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1173)
>         at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
>         at
> scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
>         at
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1173)
>         at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:688)
>         at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:688)
>         at scala.Option.foreach(Option.scala:236)
>         at
> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:688)
>         at
> org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1391)
>         at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
>         at akka.actor.ActorCell.invoke(ActorCell.scala:456)
>         at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
>         at akka.dispatch.Mailbox.run(Mailbox.scala:219)
>         at
> akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)
>         at
> scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
>         at
> scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
>         at
> scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
>         at
> scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
>
> Can Anybody help me resolve this issue please.. Help is very much
> appreciated.
>
>
>
> --
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>
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