[ https://issues.apache.org/jira/browse/SPARK-6325?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Sean Owen resolved SPARK-6325. ------------------------------ Resolution: Fixed Fix Version/s: 1.3.1 1.4.0 Issue resolved by pull request 5018 [https://github.com/apache/spark/pull/5018] > YarnAllocator crash with dynamic allocation on > ---------------------------------------------- > > Key: SPARK-6325 > URL: https://issues.apache.org/jira/browse/SPARK-6325 > Project: Spark > Issue Type: Bug > Components: Spark Core, YARN > Affects Versions: 1.3.0 > Reporter: Marcelo Vanzin > Priority: Critical > Fix For: 1.4.0, 1.3.1 > > > Run spark-shell like this: > {noformat} > spark-shell --conf spark.shuffle.service.enabled=true \ > --conf spark.dynamicAllocation.enabled=true \ > --conf spark.dynamicAllocation.minExecutors=1 \ > --conf spark.dynamicAllocation.maxExecutors=20 \ > --conf spark.dynamicAllocation.executorIdleTimeout=10 \ > --conf spark.dynamicAllocation.schedulerBacklogTimeout=5 \ > --conf spark.dynamicAllocation.sustainedSchedulerBacklogTimeout=5 > {noformat} > Then run this simple test: > {code} > scala> val verySmallRdd = sc.parallelize(1 to 10, 10).map { i => > | if (i % 2 == 0) { Thread.sleep(30 * 1000); i } else 0 > | } > verySmallRdd: org.apache.spark.rdd.RDD[Int] = MapPartitionsRDD[1] at map at > <console>:21 > scala> verySmallRdd.collect() > {code} > When Spark starts ramping down the number of allocated executors, it will hit > an assert in YarnAllocator.scala: > {code} > assert(targetNumExecutors >= 0, "Allocator killed more executors than are > allocated!") > {code} > This assert will cause the akka backend to die, but not the AM itself. So the > app will be in a zombie-like state, where the driver is alive but can't talk > to the AM. Sadness ensues. > I have a working fix, just need to add unit tests. Stay tuned. > Thanks to [~wypoon] for finding the problem, and for the test case. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org