Hi Sebastien, Are you using Pyspark by any chance, is that working for you (post the patch?)
Mayur Rustagi Ph: +1 (760) 203 3257 http://www.sigmoidanalytics.com @mayur_rustagi <https://twitter.com/mayur_rustagi> On Mon, Jun 23, 2014 at 1:51 PM, Fedechicco <fedechi...@gmail.com> wrote: > 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 >>> >>> >>> >>> >>> >> >
