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mai shurong commented on YARN-3416: ----------------------------------- I found a new case today. I submitted a more larger job with 5800 maps and 380 reduces to a queue which has max 263 cores. Even though no map fail, a deadlock of map and reduce cores allocation always occured when I tried several times. And I tried to submitted to other queues, as long as reduces of a job is more than max cores of the queue , deadlock always happened. I attach the printscreens of deadlock jobs, and attach the head 100000 line log (AM_log_head100000.txt.gz) and tail 100000 line (AM_log_tail100000.txt.gz) of AM log of one deadlock job. The parameter mapreduce.job.reduce.slowstart.completedmaps is 0.5. > deadlock in a job between map and reduce cores allocation > ---------------------------------------------------------- > > Key: YARN-3416 > URL: https://issues.apache.org/jira/browse/YARN-3416 > Project: Hadoop YARN > Issue Type: Bug > Components: fairscheduler > Affects Versions: 2.6.0 > Reporter: mai shurong > Priority: Critical > Attachments: AM_log_head100000.txt.gz, AM_log_tail100000.txt.gz, > queue_with_max163cores.png, queue_with_max263cores.png, > queue_with_max333cores.png > > > I submit a big job, which has 500 maps and 350 reduce, to a > queue(fairscheduler) with 300 max cores. When the big mapreduce job is > running 100% maps, the 300 reduces have occupied 300 max cores in the queue. > And then, a map fails and retry, waiting for a core, while the 300 reduces > are waiting for failed map to finish. So a deadlock occur. As a result, the > job is blocked, and the later job in the queue cannot run because no > available cores in the queue. > I think there is the similar issue for memory of a queue . -- This message was sent by Atlassian JIRA (v6.3.4#6332)