Hi Nick,
Can you check that the call to "collect()" works as well as
"printSchema()"? I actually experience that "printSchema()" works fine,
but then it crashes on "collect()".
In general, should I expect the master (which seems to be on branch-1.1) to
be any more/less stable than branch-1.0? While it would be great to have
this fixed, it would be good to know if I should expect lots of other
instability.
best,
-Brad
On Tue, Aug 5, 2014 at 4:15 PM, Nicholas Chammas <nicholas.cham...@gmail.com
> wrote:
> This looks to be fixed in master:
>
> >>> from pyspark.sql import SQLContext>>> sqlContext = SQLContext(sc)
> >>> sc.parallelize(['{"foo":[[1,2,3], [4,5,6]]}', '{"foo":[[1,2,3], [4,5,6]]}'
> ])
> ParallelCollectionRDD[5] at parallelize at PythonRDD.scala:315>>>
> sqlContext.jsonRDD(sc.parallelize(['{"foo":[[1,2,3], [4,5,6]]}',
> '{"foo":[[1,2,3], [4,5,6]]}']))
> MapPartitionsRDD[14] at mapPartitions at SchemaRDD.scala:408>>>
> sqlContext.jsonRDD(sc.parallelize(['{"foo":[[1,2,3], [4,5,6]]}',
> '{"foo":[[1,2,3], [4,5,6]]}'])).printSchema()
> root
> |-- foo: array (nullable = true)
> | |-- element: array (containsNull = false)
> | | |-- element: integer (containsNull = false)
>
> >>>
>
> Nick
>
>
>
> On Tue, Aug 5, 2014 at 7:12 PM, Brad Miller <bmill...@eecs.berkeley.edu>
> wrote:
>
>> Hi All,
>>
>> I've built and deployed the current head of branch-1.0, but it seems to
>> have only partly fixed the bug.
>>
>> This code now runs as expected with the indicated output:
>> > srdd = sqlCtx.jsonRDD(sc.parallelize(['{"foo":[1,2,3]}',
>> '{"foo":[4,5,6]}']))
>> > srdd.printSchema()
>> root
>> |-- foo: ArrayType[IntegerType]
>> > srdd.collect()
>> [{u'foo': [1, 2, 3]}, {u'foo': [4, 5, 6]}]
>>
>> This code still crashes:
>> > srdd = sqlCtx.jsonRDD(sc.parallelize(['{"foo":[[1,2,3], [4,5,6]]}',
>> '{"foo":[[1,2,3], [4,5,6]]}']))
>> > srdd.printSchema()
>> root
>> |-- foo: ArrayType[ArrayType(IntegerType)]
>> > srdd.collect()
>> Py4JJavaError: An error occurred while calling o63.collect.
>> : org.apache.spark.SparkException: Job aborted due to stage failure: Task
>> 3.0:29 failed 4 times, most recent failure: Exception failure in TID 67 on
>> host kunitz.research.intel-research.net:
>> net.razorvine.pickle.PickleException: couldn't introspect javabean:
>> java.lang.IllegalArgumentException: wrong number of arguments
>>
>> I may be able to see if this is fixed in master, but since it's not fixed
>> in 1.0.3 it seems unlikely to be fixed in master either. I previously tried
>> master as well, but ran into a build problem that did not occur with the
>> 1.0 branch.
>>
>> Can anybody else verify that the second example still crashes (and is
>> meant to work)? If so, would it be best to modify JIRA-2376 or start a new
>> bug?
>> https://issues.apache.org/jira/browse/SPARK-2376
>>
>> best,
>> -Brad
>>
>>
>>
>>
>>
>> On Tue, Aug 5, 2014 at 12:10 PM, Brad Miller <bmill...@eecs.berkeley.edu>
>> wrote:
>>
>>> Nick: Thanks for both the original JIRA bug report and the link.
>>>
>>> Michael: This is on the 1.0.1 release. I'll update to master and
>>> follow-up if I have any problems.
>>>
>>> best,
>>> -Brad
>>>
>>>
>>> On Tue, Aug 5, 2014 at 12:04 PM, Michael Armbrust <
>>> mich...@databricks.com> wrote:
>>>
>>>> Is this on 1.0.1? I'd suggest running this on master or the 1.1-RC
>>>> which should be coming out this week. Pyspark did not have good support
>>>> for nested data previously. If you still encounter issues using a more
>>>> recent version, please file a JIRA. Thanks!
>>>>
>>>>
>>>> On Tue, Aug 5, 2014 at 11:55 AM, Brad Miller <
>>>> bmill...@eecs.berkeley.edu> wrote:
>>>>
>>>>> Hi All,
>>>>>
>>>>> I am interested to use jsonRDD and jsonFile to create a SchemaRDD out
>>>>> of some JSON data I have, but I've run into some instability involving the
>>>>> following java exception:
>>>>>
>>>>> An error occurred while calling o1326.collect.
>>>>> : org.apache.spark.SparkException: Job aborted due to stage failure:
>>>>> Task 181.0:29 failed 4 times, most recent failure: Exception failure in
>>>>> TID
>>>>> 1664 on host neal.research.intel-research.net:
>>>>> net.razorvine.pickle.PickleException: couldn't introspect javabean:
>>>>> java.lang.IllegalArgumentException: wrong number of arguments
>>>>>
>>>>> I've pasted code which produces the error as well as the full
>>>>> traceback below. Note that I don't have any problem when I parse the JSON
>>>>> myself and use inferSchema.
>>>>>
>>>>> Is anybody able to reproduce this bug?
>>>>>
>>>>> -Brad
>>>>>
>>>>> > srdd = sqlCtx.jsonRDD(sc.parallelize(['{"foo":"bar",
>>>>> "baz":[1,2,3]}', '{"foo":"boom", "baz":[1,2,3]}']))
>>>>> > srdd.printSchema()
>>>>>
>>>>> root
>>>>> |-- baz: ArrayType[IntegerType]
>>>>> |-- foo: StringType
>>>>>
>>>>> > srdd.collect()
>>>>>
>>>>>
>>>>> ---------------------------------------------------------------------------
>>>>> Py4JJavaError Traceback (most recent call
>>>>> last)
>>>>> <ipython-input-89-ec7e8e8c68c4> in <module>()
>>>>> ----> 1 srdd.collect()
>>>>>
>>>>> /home/spark/spark-1.0.1-bin-hadoop1/python/pyspark/rdd.py in
>>>>> collect(self)
>>>>> 581 """
>>>>> 582 with _JavaStackTrace(self.context) as st:
>>>>> --> 583 bytesInJava = self._jrdd.collect().iterator()
>>>>> 584 return
>>>>> list(self._collect_iterator_through_file(bytesInJava))
>>>>> 585
>>>>>
>>>>> /usr/local/lib/python2.7/dist-packages/py4j/java_gateway.pyc in
>>>>> __call__(self, *args)
>>>>> 535 answer = self.gateway_client.send_command(command)
>>>>> 536 return_value = get_return_value(answer,
>>>>> self.gateway_client,
>>>>> --> 537 self.target_id, self.name)
>>>>> 538
>>>>> 539 for temp_arg in temp_args:
>>>>>
>>>>> /usr/local/lib/python2.7/dist-packages/py4j/protocol.pyc in
>>>>> get_return_value(answer, gateway_client, target_id, name)
>>>>> 298 raise Py4JJavaError(
>>>>> 299 'An error occurred while calling
>>>>> {0}{1}{2}.\n'.
>>>>> --> 300 format(target_id, '.', name), value)
>>>>> 301 else:
>>>>> 302 raise Py4JError(
>>>>>
>>>>> Py4JJavaError: An error occurred while calling o1326.collect.
>>>>> : org.apache.spark.SparkException: Job aborted due to stage failure:
>>>>> Task 181.0:29 failed 4 times, most recent failure: Exception failure in
>>>>> TID
>>>>> 1664 on host neal.research.intel-research.net:
>>>>> 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:322)
>>>>> net.razorvine.pickle.Pickler.dispatch(Pickler.java:286)
>>>>> net.razorvine.pickle.Pickler.save(Pickler.java:125)
>>>>>
>>>>> net.razorvine.pickle.Pickler.put_arrayOfObjects(Pickler.java:392)
>>>>> 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$3.apply(SchemaRDD.scala:385)
>>>>>
>>>>> org.apache.spark.sql.SchemaRDD$anonfun$javaToPython$1$anonfun$apply$3.apply(SchemaRDD.scala:385)
>>>>> scala.collection.Iterator$anon$11.next(Iterator.scala:328)
>>>>>
>>>>> org.apache.spark.api.python.PythonRDD$.writeIteratorToStream(PythonRDD.scala:294)
>>>>>
>>>>> org.apache.spark.api.python.PythonRDD$WriterThread$anonfun$run$1.apply$mcV$sp(PythonRDD.scala:200)
>>>>>
>>>>> org.apache.spark.api.python.PythonRDD$WriterThread$anonfun$run$1.apply(PythonRDD.scala:175)
>>>>>
>>>>> org.apache.spark.api.python.PythonRDD$WriterThread$anonfun$run$1.apply(PythonRDD.scala:175)
>>>>>
>>>>> org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1160)
>>>>>
>>>>> org.apache.spark.api.python.PythonRDD$WriterThread.run(PythonRDD.scala:174)
>>>>> Driver stacktrace:
>>>>> at org.apache.spark.scheduler.DAGScheduler.org
>>>>> $apache$spark$scheduler$DAGScheduler$failJobAndIndependentStages(DAGScheduler.scala:1044)
>>>>> at
>>>>> org.apache.spark.scheduler.DAGScheduler$anonfun$abortStage$1.apply(DAGScheduler.scala:1028)
>>>>> at
>>>>> org.apache.spark.scheduler.DAGScheduler$anonfun$abortStage$1.apply(DAGScheduler.scala:1026)
>>>>> at
>>>>> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
>>>>> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
>>>>> at
>>>>> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1026)
>>>>> at
>>>>> org.apache.spark.scheduler.DAGScheduler$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:634)
>>>>> at
>>>>> org.apache.spark.scheduler.DAGScheduler$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:634)
>>>>> at scala.Option.foreach(Option.scala:236)
>>>>> at
>>>>> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:634)
>>>>> at
>>>>> org.apache.spark.scheduler.DAGSchedulerEventProcessActor$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1229)
>>>>> at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
>>>>> at akka.actor.ActorCell.invoke(ActorCell.scala:456)
>>>>> at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
>>>>> at akka.dispatch.Mailbox.run(Mailbox.scala:219)
>>>>> at
>>>>> akka.dispatch.ForkJoinExecutorConfigurator$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)
>>>>>
>>>>
>>>>
>>>
>>
>
