I'm getting the same behavior and it's crucial I get it fixed for an evaluation of Spark + Mesos within my company.
I'm bumping +1 for the request of putting this fix in the 1.0.1 if possible! thanks, Federico 2014-06-20 20:51 GMT+02:00 Sébastien Rainville <sebastienrainvi...@gmail.com >: > Hi, > > this is just a follow-up regarding this issue. Turns out that it's caused > by a bug in Spark. I created a case for it: > https://issues.apache.org/jira/browse/SPARK-2204 and submitted a patch. > > Any chance this could be included in the 1.0.1 release? > > Thanks, > > - Sebastien > > > > On Tue, Jun 17, 2014 at 2:57 PM, Sébastien Rainville < > sebastienrainvi...@gmail.com> wrote: > >> Hi, >> >> I'm having trouble running spark on mesos in fine-grained mode. I'm >> running spark 1.0.0 and mesos 0.18.0. The tasks are failing randomly, which >> most of the time, but not always, cause the job to fail. The same code is >> running fine in coarse-grained mode. I see the following exceptions in the >> logs of the spark driver: >> >> W0617 10:57:36.774382 8735 sched.cpp:901] Attempting to launch task 21 >> with an unknown offer 20140416-011500-1369465866-5050-26096-52332715 >> W0617 10:57:36.774433 8735 sched.cpp:901] Attempting to launch task 22 >> with an unknown offer 20140416-011500-1369465866-5050-26096-52332715 >> 14/06/17 10:57:36 INFO TaskSetManager: Re-queueing tasks for >> 201311011608-1369465866-5050-9189-46 from TaskSet 0.0 >> 14/06/17 10:57:36 WARN TaskSetManager: Lost TID 22 (task 0.0:2) >> 14/06/17 10:57:36 WARN TaskSetManager: Lost TID 19 (task 0.0:0) >> 14/06/17 10:57:36 WARN TaskSetManager: Lost TID 21 (task 0.0:1) >> 14/06/17 10:57:36 INFO DAGScheduler: Executor lost: >> 201311011608-1369465866-5050-9189-46 (epoch 0) >> 14/06/17 10:57:36 INFO BlockManagerMasterActor: Trying to remove executor >> 201311011608-1369465866-5050-9189-46 from BlockManagerMaster. >> 14/06/17 10:57:36 INFO BlockManagerMaster: Removed >> 201311011608-1369465866-5050-9189-46 successfully in removeExecutor >> 14/06/17 10:57:36 DEBUG MapOutputTrackerMaster: Increasing epoch to 1 >> 14/06/17 10:57:36 INFO DAGScheduler: Host added was in lost list earlier: >> ca1-dcc1-0065.lab.mtl >> >> I don't see any exceptions in the spark executor logs. The only error >> message I found in mesos itself is warnings in the mesos master: >> >> W0617 10:57:36.816748 26100 master.cpp:1615] Failed to validate task 21 : >> Task 21 attempted to use cpus(*):1 combined with already used cpus(*):1; >> mem(*):2048 is greater than offered mem(*):3216; disk(*):98304; >> ports(*):[11900-11919, 1192 >> 1-11995, 11997-11999]; cpus(*):1 >> W0617 10:57:36.819807 26100 master.cpp:1615] Failed to validate task 22 : >> Task 22 attempted to use cpus(*):1 combined with already used cpus(*):1; >> mem(*):2048 is greater than offered mem(*):3216; disk(*):98304; >> ports(*):[11900-11919, 1192 >> 1-11995, 11997-11999]; cpus(*):1 >> W0617 10:57:36.932287 26102 master.cpp:1615] Failed to validate task 28 : >> Task 28 attempted to use cpus(*):1 combined with already used cpus(*):1; >> mem(*):2048 is greater than offered cpus(*):1; mem(*):3216; disk(*):98304; >> ports(*):[11900- >> 11960, 11962-11978, 11980-11999] >> W0617 11:05:52.783133 26098 master.cpp:2106] Ignoring unknown exited >> executor 201311011608-1369465866-5050-9189-46 on slave >> 201311011608-1369465866-5050-9189-46 (ca1-dcc1-0065.lab.mtl) >> W0617 11:05:52.787739 26103 master.cpp:2106] Ignoring unknown exited >> executor 201311011608-1369465866-5050-9189-34 on slave >> 201311011608-1369465866-5050-9189-34 (ca1-dcc1-0053.lab.mtl) >> W0617 11:05:52.790292 26102 master.cpp:2106] Ignoring unknown exited >> executor 201311011608-1369465866-5050-9189-59 on slave >> 201311011608-1369465866-5050-9189-59 (ca1-dcc1-0079.lab.mtl) >> W0617 11:05:52.800649 26099 master.cpp:2106] Ignoring unknown exited >> executor 201311011608-1369465866-5050-9189-18 on slave >> 201311011608-1369465866-5050-9189-18 (ca1-dcc1-0027.lab.mtl) >> ... (more of those "Ignoring unknown exited executor") >> >> >> I analyzed the difference in between the execution of the same job in >> coarse-grained mode and fine-grained mode, and I noticed that in the >> fine-grained mode the tasks get executed on executors different than the >> ones reported in spark, as if spark and mesos get out of sync as to which >> executor is responsible for which task. See the following: >> >> >> Coarse-grained mode: >> >> Spark Mesos Task IndexTask ID ExecutorStatusTask ID (UI)Task Name Task >> ID (logs)ExecutorState 0066SUCCESS 4"Task 4"0 66RUNNING1 159SUCCESS0 "Task >> 0"159 RUNNING22 54SUCCESS10"Task 10" 254RUNNING 33128 SUCCESS6"Task 6" 3 >> 128RUNNING ... >> >> Fine-grained mode: >> >> Spark Mesos Task IndexTask ID ExecutorTask ID (UI)Task NameTask ID >> (logs) ExecutorState0 23108SUCCESS 23"task 0.0:0"23 27FINISHED0 1965 >> FAILED19 "task 0.0:0"1986 FINISHED1 2165FAILED Mesos executor was never >> created124 92SUCCESS24"task 0.0:1" 24129FINISHED 22265 FAILEDMesos >> executor was never created 225100SUCCESS 25"task 0.0:2" 2584FINISHED 326 >> 80SUCCESS 26"task 0.0:3"26 124FINISHED 42765FAILED 27"task 0.0:4"27 108 >> FINISHED 42992SUCCESS 29"task 0.0:4"29 65FINISHED 52865FAILED Mesos >> executor was never created5 3077SUCCESS30 "task 0.0:5"3062 FINISHED6 053 >> SUCCESS0 "task 0.0:6"041 FINISHED7 177SUCCESS1 "task 0.0:7"1114 FINISHED >> ... >> >> >> Is it normal that the executor reported in spark and mesos to be >> different when running in fine-grained mode? >> >> Please note that in this particular example the job actually succeeded, >> but most of the time it's failing after 4 failed attempts of a given task. >> This job never fails in coarse-grained mode. Every job is working in >> coarse-grained mode and failing the same way in fine-grained mode. >> >> Does anybody have an idea what the problem could be? >> >> Thanks, >> >> - Sebastien >> >> >> >> >> >
