spark-user mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Gary Malouf <malouf.g...@gmail.com>
Subject Re: When using spark shell, classpath on workers does not seem to see all of my custom classes
Date Mon, 09 Sep 2013 17:13:34 GMT
Will test and report back.  Is this the same issue as:
https://groups.google.com/forum/#!topic/spark-users/fEcgIrL-gII?


On Mon, Sep 9, 2013 at 1:03 PM, Matei Zaharia <matei.zaharia@gmail.com>wrote:

> No, I think this might be an actual bug. The problem seems to be with the
> classpath on the driver program actually, not on the executors. You might
> be able to fix it as follows: export SPARK_CLASSPATH=<your JAR> before
> running spark-shell, in addition to doing ADD_JARS. But even if that fixes
> it you should report the issue.
>
> Matei
>
> On Sep 9, 2013, at 5:18 AM, Gary Malouf <malouf.gary@gmail.com> wrote:
>
> Any other checks I should do before filing this as an issue?  I know for
> my team it's a significant blocker right now.
>
>
> On Sun, Sep 8, 2013 at 7:59 PM, Gary Malouf <malouf.gary@gmail.com> wrote:
>
>> Hi Matei,
>>
>> We are using Spark 0.7.3 on a Mesos cluster.
>>
>> The logs when I start Spark shell include:
>>
>> 13/09/08 23:44:17 INFO spark.SparkContext: Added JAR
>> /opt/spark/mx-lib/verrazano_2.9.3-0.1-SNAPSHOT-assembly.jar at
>> http://10.236.136.202:31658/jars/verrazano_2.9.3-0.1-SNAPSHOT-assembly.jarwith timestamp
1378683857701
>>
>> I can also confirm that the 'verrazano' jar (my custom one) is in a mesos
>> slave temp directory on all of the slave nodes.
>>
>>
>>
>>
>> On Sun, Sep 8, 2013 at 7:01 PM, Matei Zaharia <matei.zaharia@gmail.com>wrote:
>>
>>> Which version of Spark is this with? Did the logs print something about
>>> sending the JAR you added with ADD_JARS to the cluster?
>>>
>>> Matei
>>>
>>> On Sep 8, 2013, at 8:56 AM, Gary Malouf <malouf.gary@gmail.com> wrote:
>>>
>>> > I built a custom jar with among other things, nscalatime and joda time
>>> packed inside of it.  Using the ADD_JARS variable, I have added this super
>>> jar to my classpath on the scheduler when running spark-shell.  I wrote a
>>> function that grabs protobuf data, filters and then maps each message to a
>>> (LocalDate, Option[String]) format.  Unfortunately, this does not run and I
>>> get the following:
>>> >
>>> > 13/09/08 15:50:43 INFO cluster.TaskSetManager: Finished TID 6 in 348
>>> ms (progress: 7/576)
>>> > Exception in thread "Thread-159" java.lang.ClassNotFoundException:
>>> org.joda.time.LocalDate
>>> >     at java.net.URLClassLoader$1.run(URLClassLoader.java:366)
>>> >     at java.net.URLClassLoader$1.run(URLClassLoader.java:355)
>>> >     at java.security.AccessController.doPrivileged(Native Method)
>>> >     at java.net.URLClassLoader.findClass(URLClassLoader.java:354)
>>> >     at
>>> scala.tools.nsc.util.ScalaClassLoader$URLClassLoader.scala$tools$nsc$util$ScalaClassLoader$$super$findClass(ScalaClassLoader.scala:88)
>>> >     at
>>> scala.tools.nsc.util.ScalaClassLoader$class.findClass(ScalaClassLoader.scala:44)
>>> >     at
>>> scala.tools.nsc.util.ScalaClassLoader$URLClassLoader.findClass(ScalaClassLoader.scala:88)
>>> >     at java.lang.ClassLoader.loadClass(ClassLoader.java:423)
>>> >     at
>>> scala.tools.nsc.util.ScalaClassLoader$URLClassLoader.scala$tools$nsc$util$ScalaClassLoader$$super$loadClass(ScalaClassLoader.scala:88)
>>> >     at
>>> scala.tools.nsc.util.ScalaClassLoader$class.loadClass(ScalaClassLoader.scala:50)
>>> >     at
>>> scala.tools.nsc.util.ScalaClassLoader$URLClassLoader.loadClass(ScalaClassLoader.scala:88)
>>> >     at java.lang.ClassLoader.loadClass(ClassLoader.java:356)
>>> >     at java.lang.Class.forName0(Native Method)
>>> >     at java.lang.Class.forName(Class.java:266)
>>> >     at
>>> spark.JavaDeserializationStream$$anon$1.resolveClass(JavaSerializer.scala:20)
>>> >     at
>>> java.io.ObjectInputStream.readNonProxyDesc(ObjectInputStream.java:1610)
>>> >     at
>>> java.io.ObjectInputStream.readClassDesc(ObjectInputStream.java:1515)
>>> >     at
>>> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1769)
>>> >     at
>>> java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1348)
>>> >     at java.io.ObjectInputStream.readObject(ObjectInputStream.java:370)
>>> >     at
>>> it.unimi.dsi.fastutil.objects.Object2LongOpenHashMap.readObject(Object2LongOpenHashMap.java:757)
>>> >     at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>>> >     at
>>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
>>> >     at
>>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
>>> >     at java.lang.reflect.Method.invoke(Method.java:601)
>>> >     at
>>> java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:1004)
>>> >     at
>>> java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1891)
>>> >     at
>>> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1796)
>>> >     at
>>> java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1348)
>>> >     at
>>> java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1989)
>>> >     at
>>> java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1913)
>>> >     at
>>> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1796)
>>> >     at
>>> java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1348)
>>> >     at java.io.ObjectInputStream.readObject(ObjectInputStream.java:370)
>>> >     at spark.scheduler.TaskResult.readExternal(TaskResult.scala:26)
>>> >     at
>>> java.io.ObjectInputStream.readExternalData(ObjectInputStream.java:1835)
>>> >     at
>>> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1794)
>>> >     at
>>> java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1348)
>>> >     at java.io.ObjectInputStream.readObject(ObjectInputStream.java:370)
>>> >     at
>>> spark.JavaDeserializationStream.readObject(JavaSerializer.scala:23)
>>> >     at
>>> spark.JavaSerializerInstance.deserialize(JavaSerializer.scala:45)
>>> >     at
>>> spark.scheduler.cluster.TaskSetManager.taskFinished(TaskSetManager.scala:261)
>>> >     at
>>> spark.scheduler.cluster.TaskSetManager.statusUpdate(TaskSetManager.scala:236)
>>> >     at
>>> spark.scheduler.cluster.ClusterScheduler.statusUpdate(ClusterScheduler.scala:219)
>>> >     at
>>> spark.scheduler.mesos.MesosSchedulerBackend.statusUpdate(MesosSchedulerBackend.scala:264)
>>> > 13/09/08 15:50:43 INFO mesos.MesosSchedulerBackend: driver.run()
>>> returned with code DRIVER_ABORTED
>>> >
>>> >
>>> > The code definitely compiles in the interpreter and the executors seem
>>> to find the protobuf messages which are in the same jar - any idea what
>>> could be causing the problem?
>>>
>>>
>>
>
>

Mime
View raw message