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Posted to user@spark.apache.org by "deenar.toraskar" <de...@db.com> on 2014/03/21 18:53:39 UTC
Re: SequenceFileRDDFunctions cannot be used output of spark package
Hi Aureliano
If you have managed to get a custom version of saveAsObject() that handles
compression working, would appreciate if you could share the code. I have
come across the same issue and it would help me some time having to reinvent
the wheel.
Deenar
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Re: SequenceFileRDDFunctions cannot be used output of spark package
Posted by Aureliano Buendia <bu...@gmail.com>.
On Fri, Mar 21, 2014 at 5:53 PM, deenar.toraskar <de...@db.com>wrote:
> Hi Aureliano
>
> If you have managed to get a custom version of saveAsObject() that handles
> compression working, would appreciate if you could share the code. I have
> come across the same issue and it would help me some time having to
> reinvent
> the wheel.
>
>
My problem was not about compression.
> Deenar
>
>
>
> --
> View this message in context:
> http://apache-spark-user-list.1001560.n3.nabble.com/SequenceFileRDDFunctions-cannot-be-used-output-of-spark-package-tp250p3005.html
> Sent from the Apache Spark User List mailing list archive at Nabble.com.
>
Re: SequenceFileRDDFunctions cannot be used output of spark package
Posted by pradeeps8 <sr...@gmail.com>.
Hi Sonal,
There are no custom objects in saveRDD, it is of type RDD[(String, String)].
Thanks,
Pradeep
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Re: SequenceFileRDDFunctions cannot be used output of spark package
Posted by Sonal Goyal <so...@gmail.com>.
What does your saveRDD contain? If you are using custom objects, they
should be serializable.
Best Regards,
Sonal
Nube Technologies <http://www.nubetech.co>
<http://in.linkedin.com/in/sonalgoyal>
On Sat, Mar 29, 2014 at 12:02 AM, pradeeps8 <sr...@gmail.com>wrote:
> Hi Aureliano,
>
> I followed this thread to create a custom saveAsObjectFile.
> The following is the code.
> /new org.apache.spark.rdd.SequenceFileRDDFunctions[NullWritable,
> BytesWritable](saveRDD.mapPartitions(iter =>
> iter.grouped(10).map(_.toArray)).map(x => (NullWritable.get(), new
> BytesWritable(serialize(x))))).saveAsSequenceFile("objFiles") /
>
> But, I get the following error when executed.
> /
> org.apache.spark.SparkException: Job aborted: Task not serializable:
> java.io.NotSerializableException: org.apache.hadoop.mapred.JobConf
> at
>
> org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$abortStage$1.apply(DAGScheduler.scala:1028)
> at
>
> org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$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.org
> $apache$spark$scheduler$DAGScheduler$$abortStage(DAGScheduler.scala:1026)
> at
> org.apache.spark.scheduler.DAGScheduler.org
> $apache$spark$scheduler$DAGScheduler$$submitMissingTasks(DAGScheduler.scala:794)
> at
> org.apache.spark.scheduler.DAGScheduler.org
> $apache$spark$scheduler$DAGScheduler$$submitStage(DAGScheduler.scala:737)
> at
>
> org.apache.spark.scheduler.DAGScheduler.processEvent(DAGScheduler.scala:569)
> at
>
> org.apache.spark.scheduler.DAGScheduler$$anonfun$start$1$$anon$2$$anonfun$receive$1.applyOrElse(DAGScheduler.scala:207)
> at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
> at akka.actor.ActorCell.invoke(ActorCell.scala:456)
> at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
> at akka.dispatch.Mailbox.run(Mailbox.scala:219)
> at
>
> akka.dispatch.ForkJoinExecutorConfigurator$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)
> /
>
> Any idea about this error?
> or
> Is there anything wrong in the line of code?
>
> Thanks,
> Pradeep
>
>
>
>
> --
> View this message in context:
> http://apache-spark-user-list.1001560.n3.nabble.com/SequenceFileRDDFunctions-cannot-be-used-output-of-spark-package-tp250p3442.html
> Sent from the Apache Spark User List mailing list archive at Nabble.com.
>
Re: SequenceFileRDDFunctions cannot be used output of spark package
Posted by pradeeps8 <sr...@gmail.com>.
Hi Aureliano,
I followed this thread to create a custom saveAsObjectFile.
The following is the code.
/new org.apache.spark.rdd.SequenceFileRDDFunctions[NullWritable,
BytesWritable](saveRDD.mapPartitions(iter =>
iter.grouped(10).map(_.toArray)).map(x => (NullWritable.get(), new
BytesWritable(serialize(x))))).saveAsSequenceFile("objFiles") /
But, I get the following error when executed.
/
org.apache.spark.SparkException: Job aborted: Task not serializable:
java.io.NotSerializableException: org.apache.hadoop.mapred.JobConf
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$abortStage$1.apply(DAGScheduler.scala:1028)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$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.org$apache$spark$scheduler$DAGScheduler$$abortStage(DAGScheduler.scala:1026)
at
org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitMissingTasks(DAGScheduler.scala:794)
at
org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitStage(DAGScheduler.scala:737)
at
org.apache.spark.scheduler.DAGScheduler.processEvent(DAGScheduler.scala:569)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$start$1$$anon$2$$anonfun$receive$1.applyOrElse(DAGScheduler.scala:207)
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
at akka.actor.ActorCell.invoke(ActorCell.scala:456)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
at akka.dispatch.Mailbox.run(Mailbox.scala:219)
at
akka.dispatch.ForkJoinExecutorConfigurator$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)
/
Any idea about this error?
or
Is there anything wrong in the line of code?
Thanks,
Pradeep
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Re: SequenceFileRDDFunctions cannot be used output of spark package
Posted by Aureliano Buendia <bu...@gmail.com>.
I think you bumped the wrong thread.
As I mentioned in the other thread:
saveAsHadoopFile only applies compression when the codec is available, and
it does not seem to respect the global hadoop compression properties.
I'm not sure if this is a feature, or a bug in spark.
if this is a feature, the docs should make it clear that
mapred.output.compression.* properties are read only.
On Sat, Mar 22, 2014 at 12:20 AM, deenar.toraskar <de...@db.com>wrote:
> Matei
>
> It turns out that saveAsObjectFile(), saveAsSequenceFile() and
> saveAsHadoopFile() currently do not pickup the hadoop settings as Aureliano
> found out in this post
>
>
> http://apache-spark-user-list.1001560.n3.nabble.com/Turning-kryo-on-does-not-decrease-binary-output-tp212p249.html
>
> Deenar
>
>
>
> --
> View this message in context:
> http://apache-spark-user-list.1001560.n3.nabble.com/SequenceFileRDDFunctions-cannot-be-used-output-of-spark-package-tp250p3019.html
> Sent from the Apache Spark User List mailing list archive at Nabble.com.
>
Re: SequenceFileRDDFunctions cannot be used output of spark package
Posted by "deenar.toraskar" <de...@db.com>.
Matei
It turns out that saveAsObjectFile(), saveAsSequenceFile() and
saveAsHadoopFile() currently do not pickup the hadoop settings as Aureliano
found out in this post
http://apache-spark-user-list.1001560.n3.nabble.com/Turning-kryo-on-does-not-decrease-binary-output-tp212p249.html
Deenar
--
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Re: SequenceFileRDDFunctions cannot be used output of spark package
Posted by Matei Zaharia <ma...@gmail.com>.
To use compression here, you might just have to set the correct Hadoop settings in SparkContext.hadoopConf.
Matei
On Mar 21, 2014, at 10:53 AM, deenar.toraskar <de...@db.com> wrote:
> Hi Aureliano
>
> If you have managed to get a custom version of saveAsObject() that handles
> compression working, would appreciate if you could share the code. I have
> come across the same issue and it would help me some time having to reinvent
> the wheel.
>
> Deenar
>
>
>
> --
> View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/SequenceFileRDDFunctions-cannot-be-used-output-of-spark-package-tp250p3005.html
> Sent from the Apache Spark User List mailing list archive at Nabble.com.