Sorry, I had a typo. I can conform that using ADD_JARS together with SPARK_CLASSPATH works as expected in spark-shell.
It'd make sense to have the two combined as one option. On Sun, Jan 5, 2014 at 3:51 AM, Aaron Davidson <ilike...@gmail.com> wrote: > 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 <buendia...@gmail.com>wrote: > >> >> >> >> On Sun, Jan 5, 2014 at 2:28 AM, Aaron Davidson <ilike...@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 <ilike...@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 <buendia...@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 < >>>>> buendia...@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? >>>>>> >>>>> >>>>> >>>> >>> >> >
