I believe that is not going to solve the problem. If you need to run spark on Yarn (assuming that it is your requirement) ensure that you run it in Yarn Client mode. Yarn Clustre mode is not supported with Zeppelin yet.
Regards, Sourav On Tue, Dec 15, 2015 at 9:32 AM, Felix Cheung <[email protected]> wrote: > If you are not using YARN, try building your Spark distribution without > this: > -Pyarn > ? > > > > On Tue, Dec 15, 2015 at 12:31 AM -0800, "cs user" <[email protected]> > wrote: > > Hi Folks, > > We've been playing around with this project: > > https://github.com/datalayer/zeppelin-R > > However when we try and write a notebook using R which requires hive, we > run into the following: > > Error in value[[3L]](cond): Spark SQL is not built with Hive support > > This is when we are using the pre compiled spark with hadoop 2.6 support. > > To work around this, I've tried recompiling spark with hive support. > Accessing the hive context within an R notebook now works fine. > > However, it is then impossible to run existing notebooks which try to > submit jobs via yarn, the following error is encountered: > > java.lang.NoSuchMethodException: > org.apache.spark.repl.SparkILoop$SparkILoopInterpreter.classServerUri() at > java.lang.Class.getMethod(Class.java:1678) at > org.apache.zeppelin.spark.SparkInterpreter.createSparkContext(SparkInterpreter.java:271) > at > org.apache.zeppelin.spark.SparkInterpreter.getSparkContext(SparkInterpreter.java:145) > at > org.apache.zeppelin.spark.SparkInterpreter.open(SparkInterpreter.java:464) > at > org.apache.zeppelin.interpreter.ClassloaderInterpreter.open(ClassloaderInterpreter.java:74) > at > org.apache.zeppelin.interpreter.LazyOpenInterpreter.open(LazyOpenInterpreter.java:68) > at > org.apache.zeppelin.interpreter.LazyOpenInterpreter.interpret(LazyOpenInterpreter.java:92) > at > org.apache.zeppelin.interpreter.remote.RemoteInterpreterServer$InterpretJob.jobRun(RemoteInterpreterServer.java:292) > at org.apache.zeppelin.scheduler.Job.run(Job.java:170) at > org.apache.zeppelin.scheduler.FIFOScheduler$1.run(FIFOScheduler.java:118) > at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471) > at java.util.concurrent.FutureTask.run(FutureTask.java:262) at > java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$201(ScheduledThreadPoolExecutor.java:178) > at > java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:292) > 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) > > If I switch back to the old spark home, these jobs then work fine again. > > I am compiling our custom version of spark with the following: > > ./make-distribution.sh --name custom-spark --tgz -Phadoop-2.6 > -Dhadoop.version=2.6.0 -Pyarn -Phive -Phive-thriftserver > > Are there any other switches I need to add to overcome the above error? > > Thanks! > > >
