Re: Error when Applying schema to a dictionary with a Tuple as key

2014-12-16 Thread Davies Liu 
I had created https://issues.apache.org/jira/browse/SPARK-4866, it
will be fixed by https://github.com/apache/spark/pull/3714.

Thank you for reporting this.

Davies

On Tue, Dec 16, 2014 at 12:44 PM, Davies Liu  wrote:
> It's a bug, could you file a JIRA for this? thanks!
>
> On Tue, Dec 16, 2014 at 5:49 AM, sahanbull  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 "", line 1, in 
>>   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.DAG

Re: Error when Applying schema to a dictionary with a Tuple as key

2014-12-16 Thread Davies Liu 
It's a bug, could you file a JIRA for this? thanks!

On Tue, Dec 16, 2014 at 5:49 AM, sahanbull  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 "", line 1, in 
>   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.r