Hi, This may be cause, depending on your scheduler, only one Reducer may be allocated per TT heartbeat. A reasoning of why this is the case is explained here: http://search-hadoop.com/m/KYv8JhkOHc1
You may have better results in 1.0.3 using an alternative scheduler such as FairScheduler with multiple-assignments-per-heartbeat turned on (See http://hadoop.apache.org/common/docs/current/fair_scheduler.html and boolean property "mapred.fairscheduler.assignmultiple" to enable) or via CapacityScheduler (See http://hadoop.apache.org/common/docs/current/capacity_scheduler.html) which does it as well (OOB). On Tue, May 22, 2012 at 5:36 PM, Andrés Durán <du...@tadium.es> wrote: > Hello, > > I'm working with a Hadoop, version is 1.0.3 and configured in > pseudo-distributed mode. > > I have 128 reducers tasks and it's running in a local machine with 32 > cores. The job is working fine and fast it takes 1 hour and 30 minutes to > fininsh. But when the Job starts, the reducers are comming to the running > phase from the tasks queue very slow, it takes 7 minutes to allocate 32 tasks > in the running phase. Why is too slow to allocate task in running mode? It's > possible to adjust any variable in the jobs tracker setup to reduce this > allocation time? > > Thanks to all! > > Best regards, > Andrés Durán -- Harsh J
