Michael,
you are right, there is definitely some limit at 2GB. Here is a trivial
example to demonstrate it:
import org.apache.spark.storage.StorageLevel
val d = sc.parallelize(1 to 1e6.toInt, 1).map{i => new
Array[Byte](5e3.toInt)}.persist(StorageLevel.DISK_ONLY)
d.count()
It gives the same error you are observing. I was under the same impression
as Sean about the limits only being on blocks, not partitions -- but
clearly that isn't the case here.
I don't know the whole story yet, but I just wanted to at least let you
know you aren't crazy :)
At the very least this suggests that you might need to make smaller
partitions for now.
Imran
On Tue, Feb 3, 2015 at 4:58 AM, Michael Albert <
m_albert...@yahoo.com.invalid> wrote:
> Greetings!
>
> Thanks for the response.
>
> Below is an example of the exception I saw.
> I'd rather not post code at the moment, so I realize it is completely
> unreasonable to ask for a diagnosis.
> However, I will say that adding a "partitionBy()" was the last change
> before this error was created.
>
>
> Thanks for your time and any thoughts you might have.
>
> Sincerely,
> Mike
>
>
>
> Exception in thread "main" org.apache.spark.SparkException: Job aborted
> due to stage failure: Task 4 in stage 5.0 failed 4 times, most recent
> failure: Lost task 4.3 in stage 5.0 (TID 6012,
> ip-10-171-0-31.ec2.internal): java.lang.RuntimeException:
> java.lang.IllegalArgumentException: Size exceeds Integer.MAX_VALUE
> at sun.nio.ch.FileChannelImpl.map(FileChannelImpl.java:828)
> at org.apache.spark.storage.DiskStore.getBytes(DiskStore.scala:123)
> at org.apache.spark.storage.DiskStore.getBytes(DiskStore.scala:132)
> at
> org.apache.spark.storage.BlockManager.doGetLocal(BlockManager.scala:517)
> at
> org.apache.spark.storage.BlockManager.getBlockData(BlockManager.scala:307)
> at
> org.apache.spark.network.netty.NettyBlockRpcServer$$anonfun$2.apply(NettyBlockRpcServer.scala:57)
> at
> org.apache.spark.network.netty.NettyBlockRpcServer$$anonfun$2.apply(NettyBlockRpcServer.scala:57)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at
> scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
> at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
> at
> scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
> at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:108)
> at
> org.apache.spark.network.netty.NettyBlockRpcServer.receive(NettyBlockRpcServer.scala:57)
>
>
> ------------------------------
> *From:* Sean Owen <so...@cloudera.com>
> *To:* Michael Albert <m_albert...@yahoo.com>
> *Cc:* "user@spark.apache.org" <user@spark.apache.org>
> *Sent:* Monday, February 2, 2015 10:13 PM
> *Subject:* Re: 2GB limit for partitions?
>
> The limit is on blocks, not partitions. Partitions have many blocks.
>
> It sounds like you are creating very large values in memory, but I'm
> not sure given your description. You will run into problems if a
> single object is more than 2GB, of course. More of the stack trace
> might show what is mapping that much memory.
>
> If you simply want data into 1000 files it's a lot simpler. Just
> repartition into 1000 partitions and save the data. If you need more
> control over what goes into which partition, use a Partitioner, yes.
>
>
>
> On Mon, Feb 2, 2015 at 8:40 PM, Michael Albert
> <m_albert...@yahoo.com.invalid> wrote:
> > Greetings!
> >
> > SPARK-1476 says that there is a 2G limit for "blocks".
> > Is this the same as a 2G limit for partitions (or approximately so?)?
> >
> >
> > What I had been attempting to do is the following.
> > 1) Start with a moderately large data set (currently about 100GB, but
> > growing).
> > 2) Create about 1,000 files (yes, files) each representing a subset of
> the
> > data.
> >
> > The current attempt I am working on is something like this.
> > 1) Do a "map" whose output key indicates which of the 1,000 files it
> will go
> > into and whose value is what I will want to stick into the file.
> > 2) Partition the data and use the body of mapPartition to open a file and
> > save the data.
> >
> > My apologies, this is actually embedded in a bigger mess, so I won't post
> > it.
> >
> > However, I get errors telling me that there is an
> "IllegalArgumentException:
> > Size exceeds Inter.MAX_VALUE", with sun.nio.ch.FileChannelImpl.map at the
> > top of the stack. This leads me to think that I have hit the limit or
> > partition and/or block size.
> >
> > Perhaps this is not a good way to do it?
> >
> > I suppose I could run 1,000 passes over the data, each time collecting
> the
> > output for one of my 1,000 final files, but that seems likely to be
> > painfully slow to run.
> >
> > Am I missing something?
> >
> > Admittedly, this is an odd use case....
> >
> > Thanks!
> >
> > Sincerely,
> > Mike Albert
>
>
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