Other users might have consumed all map slots which may have caused long wait times for some mapper in your job. In such cases I would watch the queues closely and reconsider job distribution to grid queues with sufficient map slots.
Thanks, Phani Best Regards, Phani phan...@ovi.com >________________________________ > From: Robert Evans <ev...@yahoo-inc.com> >To: "mapreduce-user@hadoop.apache.org" <mapreduce-user@hadoop.apache.org> >Sent: Friday, 6 July 2012 10:30 PM >Subject: Re: issue with map running time > > >How long a program takes to run depends on a lot of things. It could be a >connectivity issue, or it could be that your program does a lot more >processing for some input records then for others, or it could be that some of >your records are a lot smaller so that more of them exist in a single input >split. Without knowing what the code is doing it is hard to say more then >that. > > >--Bobby Evans > >From: Kasi Subrahmanyam <kasisubbu...@gmail.com> >Reply-To: "mapreduce-user@hadoop.apache.org" ><mapreduce-user@hadoop.apache.org> >To: "mapreduce-user@hadoop.apache.org" <mapreduce-user@hadoop.apache.org> >Subject: issue with map running time > > > >Hi , > >I have a job which has let us say 10 mappers running in parallel. >Some are running fast but few of them are taking too long to run. >For example few mappers are taking 5 to 10 mins but others are taking around >12 hours or more. >Does the difference in the data handled by the mappers can cause such a >variation or is it the issue with connectivity. > >Note:The cluster we are using have multiple users running their jobs on it. > >Thanks in advance. >Subbu > > > --- Sent via Epic Browser
