Another problem that I encountered during the same set of experiments(sorry if I am asking too many questions, I am eager to get things fixed): - for the same configuration, a piece of code runs perfectly on 10GB of input, then for 38GB it runs forever (no deadlock).
I believe that may occur because Flink spills information to disk every time it runs out of memory... Is this fixable by increasing the number of buffers? That's the last question for today, promise :) Thanks! On Fri, Jun 19, 2015 at 2:40 PM, Till Rohrmann <trohrm...@apache.org> wrote: > Yes, it was an issue for the milestone release. > > On Fri, Jun 19, 2015 at 2:18 PM Andra Lungu <lungu.an...@gmail.com> wrote: > > > Yes, so I am using flink-0.9.0-milestone-1. Was it a problem for this > > version? > > I'll just fetch the latest master if this is the case. > > > > On Fri, Jun 19, 2015 at 2:12 PM, Till Rohrmann <trohrm...@apache.org> > > wrote: > > > > > Hi Andra, > > > > > > the problem seems to be that the deployment of some tasks takes longer > > than > > > 100s. From the stack trace it looks as if you're not using the latest > > > master. > > > > > > We had problems with previous version where the deployment call waited > > for > > > the TM to completely download the user code jars. For large setups the > > > BlobServer became a bottleneck and some of the deployment calls timed > > out. > > > We updated the deployment logic so that the TM sends an immediate ACK > > backt > > > to the JM when it receives a new task. > > > > > > Could you verify which version of Flink you're running and in case that > > > it's not the latest master, could you please try to run your example > with > > > the latest code? > > > > > > Cheers, > > > Till > > > > > > On Fri, Jun 19, 2015 at 1:42 PM Andra Lungu <lungu.an...@gmail.com> > > wrote: > > > > > > > Hi everyone, > > > > > > > > I ran a job this morning on 30 wally nodes. DOP 224. Worked like a > > charm. > > > > > > > > Then, I ran a similar job, on the exact same configuration, on the > same > > > > input data set. The only difference between them is that the second > job > > > > computes the degrees per vertex and, for vertices with degree higher > > > than a > > > > user-defined threshold, it does a bit of magic(roughly a bunch of > > > > coGroups). The problem is that, even before the extra functions get > > > called, > > > > I get the following type of exception: > > > > > > > > 06/19/2015 12:06:43 CHAIN FlatMap (FlatMap at > > > > fromDataSet(Graph.java:171)) -> Combine(Distinct at > > > > fromDataSet(Graph.java:171))(222/224) switched to FAILED > > > > java.lang.IllegalStateException: Update task on instance > > > > 29073fb0b0957198a2b67569b042d56b @ wally004 - 8 slots - URL: > > akka.tcp:// > > > > flink@130.149.249.14:44528/user/taskmanager failed due to: > > > > at > > > > > > > > > > > > > > org.apache.flink.runtime.executiongraph.Execution$5.onFailure(Execution.java:860) > > > > at akka.dispatch.OnFailure.internal(Future.scala:228) > > > > at akka.dispatch.OnFailure.internal(Future.scala:227) > > > > at akka.dispatch.japi$CallbackBridge.apply(Future.scala:174) > > > > at akka.dispatch.japi$CallbackBridge.apply(Future.scala:171) > > > > at > > > > scala.PartialFunction$class.applyOrElse(PartialFunction.scala:118) > > > > at > > > > > > > > > > > > > > scala.runtime.AbstractPartialFunction.applyOrElse(AbstractPartialFunction.scala:25) > > > > at > > > > scala.concurrent.Future$$anonfun$onFailure$1.apply(Future.scala:136) > > > > at > > > > scala.concurrent.Future$$anonfun$onFailure$1.apply(Future.scala:134) > > > > at > scala.concurrent.impl.CallbackRunnable.run(Promise.scala:32) > > > > at > > > > > > > > > > > > > > scala.concurrent.impl.ExecutionContextImpl$$anon$3.exec(ExecutionContextImpl.scala:107) > > > > at > > > > scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260) > > > > at > > > > > > > > > > > > > > scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339) > > > > at > > > > > > scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979) > > > > at > > > > > > > > > > > > > > scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107) > > > > Caused by: akka.pattern.AskTimeoutException: Ask timed out on > > > > [Actor[akka.tcp:// > flink@130.149.249.14:44528/user/taskmanager#82700874 > > ]] > > > > after [100000 ms] > > > > at > > > > > > > > > > akka.pattern.PromiseActorRef$$anonfun$1.apply$mcV$sp(AskSupport.scala:333) > > > > at akka.actor.Scheduler$$anon$7.run(Scheduler.scala:117) > > > > at > > > > > > > > > > > > > > scala.concurrent.Future$InternalCallbackExecutor$.scala$concurrent$Future$InternalCallbackExecutor$$unbatchedExecute(Future.scala:694) > > > > at > > > > > > > > > > scala.concurrent.Future$InternalCallbackExecutor$.execute(Future.scala:691) > > > > at > > > > > > > > > > > > > > akka.actor.LightArrayRevolverScheduler$TaskHolder.executeTask(Scheduler.scala:467) > > > > at > > > > > > > > > > > > > > akka.actor.LightArrayRevolverScheduler$$anon$8.executeBucket$1(Scheduler.scala:419) > > > > at > > > > > > > > > > > > > > akka.actor.LightArrayRevolverScheduler$$anon$8.nextTick(Scheduler.scala:423) > > > > at > > > > > akka.actor.LightArrayRevolverScheduler$$anon$8.run(Scheduler.scala:375) > > > > at java.lang.Thread.run(Thread.java:722) > > > > > > > > > > > > At first I thought, okay maybe wally004 is down; then I ssh'd into > it. > > > > Works fine. > > > > > > > > The full output can be found here: > > > > https://gist.github.com/andralungu/d222b75cb33aea57955d > > > > > > > > Does anyone have any idea about what may have triggered this? :( > > > > > > > > Thanks! > > > > Andra > > > > > > > > > >
