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Posted to user@spark.apache.org by Pat Ferrel <pa...@occamsmachete.com> on 2015/03/02 17:52:03 UTC
Re: Upgrade to Spark 1.2.1 using Guava
Marcelo’s work-around works. So if you are using the itemsimilarity stuff, the CLI has a way to solve the class not found and I can point out how to do the equivalent if you are using the library API. Ping me if you care.
On Feb 28, 2015, at 2:27 PM, Erlend Hamnaberg <er...@hamnaberg.net> wrote:
Yes. I ran into this problem with mahout snapshot and spark 1.2.0 not really trying to figure out why that was a problem, since there were already too many moving parts in my app. Obviously there is a classpath issue somewhere.
/Erlend
On 27 Feb 2015 22:30, "Pat Ferrel" <pat@occamsmachete.com <ma...@occamsmachete.com>> wrote:
@Erlend hah, we were trying to merge your PR and ran into this—small world. You actually compile the JavaSerializer source in your project?
@Marcelo do you mean by modifying spark.executor.extraClassPath on all workers, that didn’t seem to work?
On Feb 27, 2015, at 1:23 PM, Erlend Hamnaberg <erlend@hamnaberg.net <ma...@hamnaberg.net>> wrote:
Hi.
I have had a simliar issue. I had to pull the JavaSerializer source into my own project, just so I got the classloading of this class under control.
This must be a class loader issue with spark.
-E
On Fri, Feb 27, 2015 at 8:52 PM, Pat Ferrel <pat@occamsmachete.com <ma...@occamsmachete.com>> wrote:
I understand that I need to supply Guava to Spark. The HashBiMap is created in the client and broadcast to the workers. So it is needed in both. To achieve this there is a deps.jar with Guava (and Scopt but that is only for the client). Scopt is found so I know the jar is fine for the client.
I pass in the deps.jar to the context creation code. I’ve checked the content of the jar and have verified that it is used at context creation time.
I register the serializer as follows:
class MyKryoRegistrator extends KryoRegistrator {
override def registerClasses(kryo: Kryo) = {
val h: HashBiMap[String, Int] = HashBiMap.create[String, Int]()
//kryo.addDefaultSerializer(h.getClass, new JavaSerializer())
log.info <http://log.info/>("\n\n\nRegister Serializer for " + h.getClass.getCanonicalName + "\n\n\n") // just to be sure this does indeed get logged
kryo.register(classOf[com.google.common.collect.HashBiMap[String, Int]], new JavaSerializer())
}
}
The job proceeds up until the broadcast value, a HashBiMap, is deserialized, which is where I get the following error.
Have I missed a step for deserialization of broadcast values? Odd that serialization happened but deserialization failed. I’m running on a standalone localhost-only cluster.
15/02/27 11:40:34 WARN scheduler.TaskSetManager: Lost task 1.0 in stage 4.0 (TID 9, 192.168.0.2): java.io.IOException: com.esotericsoftware.kryo.KryoException: Error during Java deserialization.
at org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:1093)
at org.apache.spark.broadcast.TorrentBroadcast.readBroadcastBlock(TorrentBroadcast.scala:164)
at org.apache.spark.broadcast.TorrentBroadcast._value$lzycompute(TorrentBroadcast.scala:64)
at org.apache.spark.broadcast.TorrentBroadcast._value(TorrentBroadcast.scala:64)
at org.apache.spark.broadcast.TorrentBroadcast.getValue(TorrentBroadcast.scala:87)
at org.apache.spark.broadcast.Broadcast.value(Broadcast.scala:70)
at my.TDIndexedDatasetReader$$anonfun$5.apply(TextDelimitedReaderWriter.scala:95)
at my.TDIndexedDatasetReader$$anonfun$5.apply(TextDelimitedReaderWriter.scala:94)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at org.apache.spark.util.collection.ExternalSorter.spillToPartitionFiles(ExternalSorter.scala:366)
at org.apache.spark.util.collection.ExternalSorter.insertAll(ExternalSorter.scala:211)
at org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:63)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:68)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:56)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:200)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Caused by: com.esotericsoftware.kryo.KryoException: Error during Java deserialization.
at com.esotericsoftware.kryo.serializers.JavaSerializer.read(JavaSerializer.java:42)
at com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:732)
at org.apache.spark.serializer.KryoDeserializationStream.readObject(KryoSerializer.scala:144)
at org.apache.spark.broadcast.TorrentBroadcast$.unBlockifyObject(TorrentBroadcast.scala:216)
at org.apache.spark.broadcast.TorrentBroadcast$$anonfun$readBroadcastBlock$1.apply(TorrentBroadcast.scala:177)
at org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:1090)
... 19 more
======== root eror ==========
Caused by: java.lang.ClassNotFoundException: com.google.common.collect.HashBiMap
at java.net.URLClassLoader$1.run(URLClassLoader.java:366)
at java.net.URLClassLoader$1.run(URLClassLoader.java:355)
...
On Feb 25, 2015, at 5:24 PM, Marcelo Vanzin <vanzin@cloudera.com <ma...@cloudera.com>> wrote:
Guava is not in Spark. (Well, long version: it's in Spark but it's
relocated to a different package except for some special classes
leaked through the public API.)
If your app needs Guava, it needs to package Guava with it (e.g. by
using maven-shade-plugin, or using "--jars" if only executors use
Guava).
On Wed, Feb 25, 2015 at 5:17 PM, Pat Ferrel <pat@occamsmachete.com <ma...@occamsmachete.com>> wrote:
> The root Spark pom has guava set at a certain version number. It’s very hard
> to read the shading xml. Someone suggested that I try using
> userClassPathFirst but that sounds too heavy handed since I don’t really
> care which version of guava I get, not picky.
>
> When I set my project to use the same version as Spark I get a missing
> classdef, which usually means a version conflict.
>
> At this point I am quite confused about what is actually in Spark as far as
> Guava and how to coexist with it happily.
>
> Let me rephrase my question: Does anyone know how or has anyone used Guava
> in a project? Is there a recommended way to use it in a job?
--
Marcelo
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