Yes, I think so, esp. for a pregel application… have any suggestion? Best, Yifan LI
> On 30 Jan 2015, at 22:25, Sonal Goyal <sonalgoy...@gmail.com> wrote: > > Is your code hitting frequent garbage collection? > > Best Regards, > Sonal > Founder, Nube Technologies <http://www.nubetech.co/> > > <http://in.linkedin.com/in/sonalgoyal> > > > > On Fri, Jan 30, 2015 at 7:52 PM, Yifan LI <iamyifa...@gmail.com > <mailto:iamyifa...@gmail.com>> wrote: > >> >> >> Hi, >> >> I am running my graphx application on Spark 1.2.0(11 nodes cluster), has >> requested 30GB memory per node and 100 cores for around 1GB input dataset(5 >> million vertices graph). >> >> But the error below always happen… >> >> Is there anyone could give me some points? >> >> (BTW, the overall edge/vertex RDDs will reach more than 100GB during graph >> computation, and another version of my application can work well on the same >> dataset while it need much less memory during computation) >> >> Thanks in advance!!! >> >> >> 15/01/29 18:05:08 ERROR ContextCleaner: Error cleaning broadcast 60 >> java.util.concurrent.TimeoutException: Futures timed out after [30 seconds] >> at scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:219) >> at >> scala.concurrent.impl.Promise$DefaultPromise.result(Promise.scala:223) >> at scala.concurrent.Await$$anonfun$result$1.apply(package.scala:107) >> at >> scala.concurrent.BlockContext$DefaultBlockContext$.blockOn(BlockContext.scala:53) >> at scala.concurrent.Await$.result(package.scala:107) >> at >> org.apache.spark.storage.BlockManagerMaster.removeBroadcast(BlockManagerMaster.scala:137) >> at >> org.apache.spark.broadcast.TorrentBroadcast$.unpersist(TorrentBroadcast.scala:227) >> at >> org.apache.spark.broadcast.TorrentBroadcastFactory.unbroadcast(TorrentBroadcastFactory.scala:45) >> at >> org.apache.spark.broadcast.BroadcastManager.unbroadcast(BroadcastManager.scala:66) >> at >> org.apache.spark.ContextCleaner.doCleanupBroadcast(ContextCleaner.scala:185) >> at >> org.apache.spark.ContextCleaner$$anonfun$org$apache$spark$ContextCleaner$$keepCleaning$1$$anonfun$apply$mcV$sp$2.apply(ContextCleaner.scala:147) >> at >> org.apache.spark.ContextCleaner$$anonfun$org$apache$spark$ContextCleaner$$keepCleaning$1$$anonfun$apply$mcV$sp$2.apply(ContextCleaner.scala:138) >> at scala.Option.foreach(Option.scala:236) >> at >> org.apache.spark.ContextCleaner$$anonfun$org$apache$spark$ContextCleaner$$keepCleaning$1.apply$mcV$sp(ContextCleaner.scala:138) >> at >> org.apache.spark.ContextCleaner$$anonfun$org$apache$spark$ContextCleaner$$keepCleaning$1.apply(ContextCleaner.scala:134) >> at >> org.apache.spark.ContextCleaner$$anonfun$org$apache$spark$ContextCleaner$$keepCleaning$1.apply(ContextCleaner.scala:134) >> at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1460) >> at org.apache.spark.ContextCleaner.org >> <http://org.apache.spark.contextcleaner.org/>$apache$spark$ContextCleaner$$keepCleaning(ContextCleaner.scala:133) >> at org.apache.spark.ContextCleaner$$anon$3.run(ContextCleaner.scala:65) >> [Stage 91:===================> (2 + 4) >> / 6]15/01/29 18:08:15 ERROR SparkDeploySchedulerBackend: Asked to remove >> non-existent executor 0 >> [Stage 93:================================> (29 + 20) / >> 49]15/01/29 23:47:03 ERROR TaskSchedulerImpl: Lost executor 9 on >> small11-tap1.common.lip6.fr <http://small11-tap1.common.lip6.fr/>: remote >> Akka client disassociated >> [Stage 83:> (1 + 0) / 6][Stage 86:> (0 + 1) / 2][Stage 88:> (0 + 2) / >> 8]15/01/29 23:47:06 ERROR SparkDeploySchedulerBackend: Asked to remove >> non-existent executor 9 >> [Stage 83:===============> (5 + 1) / 6][Stage 88:=============> (9 + 2) / >> 11]15/01/29 23:57:30 ERROR TaskSchedulerImpl: Lost executor 8 on >> small10-tap1.common.lip6.fr <http://small10-tap1.common.lip6.fr/>: remote >> Akka client disassociated >> 15/01/29 23:57:30 ERROR SparkDeploySchedulerBackend: Asked to remove >> non-existent executor 8 >> 15/01/29 23:57:30 ERROR SparkDeploySchedulerBackend: Asked to remove >> non-existent executor 8 >> >> Best, >> Yifan LI >> >> >> >> >> > >
