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From Aaron Davidson <ilike...@gmail.com>
Subject Re: ADD_JARS doesn't properly work for spark-shell
Date Sun, 05 Jan 2014 03:51:05 GMT
Cool. To confirm, you said you can access the class and construct new
objects -- did you do this in the shell itself (i.e., on the driver), or on
the executors?

Specifically, one of the following two should fail in the shell:
> new mypackage.MyClass()
> sc.parallelize(0 until 10, 2).foreach(_ => new mypackage.MyClass())
(or just import it)

You could also try running MASTER=local-cluster[2,1,512] which launches 2
executors, 1 core each, with 512MB in a setup that mimics a real cluster
more closely, in case it's a bug only related to using local mode.


On Sat, Jan 4, 2014 at 7:07 PM, Aureliano Buendia <buendia360@gmail.com>wrote:

>
>
>
> On Sun, Jan 5, 2014 at 2:28 AM, Aaron Davidson <ilikerps@gmail.com> wrote:
>
>> Additionally, which version of Spark are you running?
>>
>
> 0.8.1.
>
> Unfortunately, this doesn't work either:
>
> MASTER=local[2] ADD_JARS=/path/to/my/jar SPARK_CLASSPATH=/path/to/my/jar./spark-shell
>
>
>>
>>
>> On Sat, Jan 4, 2014 at 6:27 PM, Aaron Davidson <ilikerps@gmail.com>wrote:
>>
>>> I am not an expert on these classpath issues, but if you're using local
>>> mode, you might also try to set SPARK_CLASSPATH to include the path to the
>>> jar file as well. This should not really help, since "adding jars" is the
>>> right way to get the jars to your executors (which is where the exception
>>> appears to be happening), but it would sure be interesting if it did.
>>>
>>>
>>> On Sat, Jan 4, 2014 at 4:50 PM, Aureliano Buendia <buendia360@gmail.com>wrote:
>>>
>>>> I should add that I can see in the log that the jar being shipped to
>>>> the workers:
>>>>
>>>> 14/01/04 15:34:52 INFO Executor: Fetching
>>>> http://192.168.1.111:51031/jars/my.jar.jar with timestamp 1388881979092
>>>> 14/01/04 15:34:52 INFO Utils: Fetching
>>>> http://192.168.1.111:51031/jars/my.jar.jar to
>>>> /var/folders/3g/jyx81ctj3698wbvphxhm4dw40000gn/T/fetchFileTemp8322008964976744710.tmp
>>>> 14/01/04 15:34:53 INFO Executor: Adding
>>>> file:/var/folders/3g/jyx81ctj3698wbvphxhm4dw40000gn/T/spark-d8ac8f66-fad6-4b3f-8059-73f13b86b070/my.jar.jar
>>>> to class loader
>>>>
>>>>
>>>> On Sun, Jan 5, 2014 at 12:46 AM, Aureliano Buendia <
>>>> buendia360@gmail.com> wrote:
>>>>
>>>>> Hi,
>>>>>
>>>>> I'm trying to access my stand alone spark app from spark-shell. I
>>>>> tried starting the shell by:
>>>>>
>>>>> MASTER=local[2] ADD_JARS=/path/to/my/jar ./spark-shell
>>>>>
>>>>> The log shows that the jar file was loaded. Also, I can access and
>>>>> create a new instance of mypackage.MyClass.
>>>>>
>>>>> The problem is that myRDD.collect() returns RDD[MyClass], and that
>>>>> throws this exception:
>>>>>
>>>>> java.lang.ClassNotFoundException: mypackage.MyClass
>>>>>   at java.net.URLClassLoader$1.run(URLClassLoader.java:366)
>>>>>   at java.net.URLClassLoader$1.run(URLClassLoader.java:355)
>>>>>   at java.security.AccessController.doPrivileged(Native Method)
>>>>>   at java.net.URLClassLoader.findClass(URLClassLoader.java:354)
>>>>>   at java.lang.ClassLoader.loadClass(ClassLoader.java:423)
>>>>>   at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:308)
>>>>>   at java.lang.ClassLoader.loadClass(ClassLoader.java:356)
>>>>>   at java.lang.Class.forName0(Native Method)
>>>>>   at java.lang.Class.forName(Class.java:264)
>>>>>   at java.io.ObjectInputStream.resolveClass(ObjectInputStream.java:622)
>>>>>   at
>>>>> java.io.ObjectInputStream.readNonProxyDesc(ObjectInputStream.java:1593)
>>>>>   at
>>>>> java.io.ObjectInputStream.readClassDesc(ObjectInputStream.java:1514)
>>>>>   at java.io.ObjectInputStream.readArray(ObjectInputStream.java:1642)
>>>>>   at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1341)
>>>>>   at java.io.ObjectInputStream.readObject(ObjectInputStream.java:369)
>>>>>   at org.apache.spark.util.Utils$.deserialize(Utils.scala:59)
>>>>>   at
>>>>> org.apache.spark.SparkContext$$anonfun$objectFile$1.apply(SparkContext.scala:573)
>>>>>   at
>>>>> org.apache.spark.SparkContext$$anonfun$objectFile$1.apply(SparkContext.scala:573)
>>>>>   at scala.collection.Iterator$$anon$21.hasNext(Iterator.scala:440)
>>>>>   at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:702)
>>>>>   at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:698)
>>>>>   at
>>>>> org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:872)
>>>>>   at
>>>>> org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:872)
>>>>>   at
>>>>> org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:107)
>>>>>   at org.apache.spark.scheduler.Task.run(Task.scala:53)
>>>>>   at
>>>>> org.apache.spark.executor.Executor$TaskRunner$$anonfun$run$1.apply$mcV$sp(Executor.scala:215)
>>>>>   at
>>>>> org.apache.spark.deploy.SparkHadoopUtil.runAsUser(SparkHadoopUtil.scala:50)
>>>>>   at
>>>>> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:182)
>>>>>   at
>>>>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1110)
>>>>>   at
>>>>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:603)
>>>>>   at java.lang.Thread.run(Thread.java:722)
>>>>>
>>>>> Does this mean that my jar was not shipped to the workers? Is this a
>>>>> known issue, or am I doing something wrong here?
>>>>>
>>>>
>>>>
>>>
>>
>

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