[ https://issues.apache.org/jira/browse/MAPREDUCE-6302?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Karthik Kambatla updated MAPREDUCE-6302: ---------------------------------------- Attachment: mr-6302-4.patch Here is a patch that greatly simplifies {{preemptReducesIfNecessary}}. [~adhoot], [~jlowe] - would like to hear your thoughts on whether an extensive change like this is reasonable. > Incorrect headroom can lead to a deadlock between map and reduce allocations > ----------------------------------------------------------------------------- > > Key: MAPREDUCE-6302 > URL: https://issues.apache.org/jira/browse/MAPREDUCE-6302 > Project: Hadoop Map/Reduce > Issue Type: Bug > Affects Versions: 2.6.0 > Reporter: mai shurong > Assignee: Karthik Kambatla > Priority: Critical > Attachments: AM_log_head100000.txt.gz, AM_log_tail100000.txt.gz, > log.txt, mr-6302-1.patch, mr-6302-2.patch, mr-6302-3.patch, mr-6302-4.patch, > mr-6302-prelim.patch, 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)