This looks like a specific Spray configuration issue (or how Spray reads config files). Maybe Spray is reading some local config file that doesn't exist on your executors?
You might need to email the Spray list. On Fri, Apr 24, 2015 at 2:38 PM, Yang Lei <genia...@gmail.com> wrote: > forward to dev. > > On Mon, Apr 20, 2015 at 10:46 AM, Yang Lei <genia...@gmail.com> wrote: > > > I implemented two kinds of DataSource, one load data during buildScan, > > the other returning my RDD class with partition information for future > > loading. > > > > My RDD's compute gets actorSystem from SparkEnv.get.actorSystem, then > > use Spray to interact with a HTTP endpoint, which is the same flow as > > loading data in buildScan. All the Spray dependencies are included in a > > jar and passes to spark-submit using --jar. > > > > The Job is define in python. > > > > Both scenarios work testing locally using --master local[4]. For mesos, > > the not partitioned loading works too, but the partitioned loading hits > the > > following exception. > > > > Traceback (most recent call last): > > > > File "/root/spark-1.3.1-bin-hadoop2.4/../CloudantApp.py", line 78, in > > <module> > > > > for code in airportData.collect(): > > > > File "/root/spark-1.3.1-bin-hadoop2.4/python/pyspark/sql/dataframe.py", > > line 293, in collect > > > > port = > > self._sc._jvm.PythonRDD.collectAndServe(self._jdf.javaToPython().rdd()) > > > > File > > > "/root/spark-1.3.1-bin-hadoop2.4/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py", > > line 538, in __call__ > > > > File > > > "/root/spark-1.3.1-bin-hadoop2.4/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py", > > line 300, in get_return_value > > > > py4j.protocol.Py4JJavaError: An error occurred while calling > > o60.javaToPython. > > > > : org.apache.spark.SparkException: Job aborted due to stage failure: Task > > 0 in stage 36.0 failed 4 times, most recent failure: Lost task 0.3 in > stage > > 36.0 (TID 147, 198.11.207.72): > com.typesafe.config.ConfigException$Missing: > > No configuration setting found for key 'spray' > > > > at com.typesafe.config.impl.SimpleConfig.findKey(SimpleConfig.java:124) > > > > at com.typesafe.config.impl.SimpleConfig.find(SimpleConfig.java:147) > > > > at com.typesafe.config.impl.SimpleConfig.find(SimpleConfig.java:159) > > > > at com.typesafe.config.impl.SimpleConfig.find(SimpleConfig.java:164) > > > > at com.typesafe.config.impl.SimpleConfig.getObject(SimpleConfig.java:218) > > > > at com.typesafe.config.impl.SimpleConfig.getConfig(SimpleConfig.java:224) > > > > at com.typesafe.config.impl.SimpleConfig.getConfig(SimpleConfig.java:33) > > > > at spray.can.HttpExt.<init>(Http.scala:143) > > > > at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method) > > > > at > > > sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:57) > > > > at > > > sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45) > > > > at java.lang.reflect.Constructor.newInstance(Constructor.java:526) > > > > at > > > akka.actor.ReflectiveDynamicAccess$$anonfun$createInstanceFor$2.apply(DynamicAccess.scala:78) > > > > at scala.util.Try$.apply(Try.scala:161) > > > > at > > > akka.actor.ReflectiveDynamicAccess.createInstanceFor(DynamicAccess.scala:73) > > > > at akka.actor.ExtensionKey.createExtension(Extension.scala:153) > > > > at akka.actor.ActorSystemImpl.registerExtension(ActorSystem.scala:711) > > > > at akka.actor.ExtensionId$class.apply(Extension.scala:79) > > > > at akka.actor.ExtensionKey.apply(Extension.scala:149) > > > > at akka.io.IO$.apply(IO.scala:30) > > > > at spray.client.pipelining$.sendReceive(pipelining.scala:35) > > > > at > > > com.cloudant.spark.common.JsonStoreDataAccess.getQueryResult(JsonStoreDataAccess.scala:118) > > > > at > > > com.cloudant.spark.common.JsonStoreDataAccess.getIterator(JsonStoreDataAccess.scala:71) > > > > at com.cloudant.spark.common.JsonStoreRDD.compute(JsonStoreRDD.scala:86) > > > > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277) > > > > at org.apache.spark.rdd.RDD.iterator(RDD.scala:244) > > > > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61) > > > > at org.apache.spark.scheduler.Task.run(Task.scala:64) > > > > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203) > > > > 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) > > > > Is this due to some kind of classpath setup issue on the executor for the > > external jar for handing RDD? > > > > Thanks in advance for any suggestions on how to resolve this. > > > > Yang > > >
