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Marcelo Vanzin commented on SPARK-14209: ---------------------------------------- So, I don't know what to say. Your log configuration is resulting in corrupt logs that make debugging your issue very hard. So unless you can easily replace your logging configuration with Spark's default, it will be hard to make progress here. > Application failure during preemption. > -------------------------------------- > > Key: SPARK-14209 > URL: https://issues.apache.org/jira/browse/SPARK-14209 > Project: Spark > Issue Type: Bug > Components: Block Manager > Affects Versions: 1.6.1 > Environment: Spark on YARN > Reporter: Miles Crawford > > We have a fair-sharing cluster set up, including the external shuffle > service. When a new job arrives, existing jobs are successfully preempted > down to fit. > A spate of these messages arrives: > ExecutorLostFailure (executor 48 exited unrelated to the running tasks) > Reason: Container container_1458935819920_0019_01_000143 on host: > ip-10-12-46-235.us-west-2.compute.internal was preempted. > This seems fine - the problem is that soon thereafter, our whole application > fails because it is unable to fetch blocks from the pre-empted containers: > org.apache.spark.storage.BlockFetchException: Failed to fetch block from 1 > locations. Most recent failure cause: > Caused by: java.io.IOException: Failed to connect to > ip-10-12-46-235.us-west-2.compute.internal/10.12.46.235:55681 > Caused by: java.net.ConnectException: Connection refused: > ip-10-12-46-235.us-west-2.compute.internal/10.12.46.235:55681 > Full stack: https://gist.github.com/milescrawford/33a1c1e61d88cc8c6daf > Spark does not attempt to recreate these blocks - the tasks simply fail over > and over until the maxTaskAttempts value is reached. > It appears to me that there is some fault in the way preempted containers are > being handled - shouldn't these blocks be recreated on demand? -- 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