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Posted to user@spark.apache.org by sahanbull <sa...@skimlinks.com> on 2014/12/16 14:49:31 UTC
Error when Applying schema to a dictionary with a Tuple as key
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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Re: Error when Applying schema to a dictionary with a Tuple as key
Posted by Davies Liu <da...@databricks.com>.
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 <da...@databricks.com> wrote:
> It's a bug, could you file a JIRA for this? thanks!
>
> On Tue, Dec 16, 2014 at 5:49 AM, sahanbull <sa...@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.
>>
>>
>>
>> --
>> View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Error-when-Applying-schema-to-a-dictionary-with-a-Tuple-as-key-tp20716.html
>> Sent from the Apache Spark User List mailing list archive at Nabble.com.
>>
>> ---------------------------------------------------------------------
>> To unsubscribe, e-mail: user-unsubscribe@spark.apache.org
>> For additional commands, e-mail: user-help@spark.apache.org
>>
---------------------------------------------------------------------
To unsubscribe, e-mail: user-unsubscribe@spark.apache.org
For additional commands, e-mail: user-help@spark.apache.org
Re: Error when Applying schema to a dictionary with a Tuple as key
Posted by Davies Liu <da...@databricks.com>.
It's a bug, could you file a JIRA for this? thanks!
On Tue, Dec 16, 2014 at 5:49 AM, sahanbull <sa...@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.
>
>
>
> --
> View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Error-when-Applying-schema-to-a-dictionary-with-a-Tuple-as-key-tp20716.html
> Sent from the Apache Spark User List mailing list archive at Nabble.com.
>
> ---------------------------------------------------------------------
> To unsubscribe, e-mail: user-unsubscribe@spark.apache.org
> For additional commands, e-mail: user-help@spark.apache.org
>
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