agree. just check your app. or paste map code here. --Send from my Sony mobile. On Apr 14, 2013 4:08 AM, "Edward Capriolo" <edlinuxg...@gmail.com> wrote:
> Your application logic is likely stuck in a loop. > > > On Sat, Apr 13, 2013 at 12:47 PM, Chris Hokamp <chris.hok...@gmail.com>wrote: > >> >When you say "never progresses", do you see the MR framework kill it >> >automatically after 10 minutes of inactivity or does it never ever >> >exit? >> >> The latter -- it never exits. Killing it manually seems like a good >> option for now. We already have mapred.max.map.failures.percent set to a >> non-zero value, but because the task never fails, this never comes into >> effect. >> >> Thanks for the help, >> Chris >> >> >> On Sat, Apr 13, 2013 at 5:00 PM, Harsh J <ha...@cloudera.com> wrote: >> >>> When you say "never progresses", do you see the MR framework kill it >>> automatically after 10 minutes of inactivity or does it never ever >>> exit? >>> >>> You can lower the timeout period on tasks via mapred.task.timeout set >>> in msec. You could also set mapred.max.map.failures.percent to a >>> non-zero value to allow that much percentage of tasks to fail without >>> also marking the whole job as a failure. >>> >>> If the task itself does not get killed by the framework due to >>> inactiveness, try doing a hadoop job -fail-task on its attempt ID >>> manually. >>> >>> On Sat, Apr 13, 2013 at 8:45 PM, Chris Hokamp <chris.hok...@gmail.com> >>> wrote: >>> > Hello, >>> > >>> > We have a job where all mappers finish except for one, which always >>> hangs at >>> > the same spot (i.e. reaches 49%, then never progresses). >>> > >>> > This is likely due to a bug in the wiki parser in our Pig UDF. We can >>> afford >>> > to lose the data this mapper is working on if it would allow the job to >>> > finish. Question: is there a hadoop configuration parameter similar to >>> > mapred.skip.map.max.skip.records that would let us skip a map that >>> doesn't >>> > progress after X amount of time? Any other possible workarounds for >>> this >>> > case would also be useful. >>> > >>> > We are currently using hadoop 1.1.0 and Pig 0.10.1. >>> > >>> > Thanks, >>> > Chris >>> >>> >>> >>> -- >>> Harsh J >>> >> >> >
