Hello, Hadoop poses no restrictions on the number of concurrent jobs. Perhaps you meant tasks.
If on a TaskTracker, the maximum limit of tasks is set to N, N parallel tasks may be run on it. The N is set to two by default (since most machines today are 2+ core'd). You can tweak this parameter to reflect one, and then you'll see only a maximum of one Task running on the TaskTracker at a given time. On Tue, Mar 29, 2011 at 7:51 PM, <[email protected]> wrote: > Hi, > > > > We recently did some experiment on mapreduce job scheduling and found that > sometimes there were 2 jobs running on the same machine and each of them ran > very slowly. We used to think that 2nd job will wait for the 1st freeing the > slave machine occupied and then began to run and seems that this is wrong. > > > > Our questions are: > > (1) How does this scenario happen? Is it because that there’s a threshold > about on workload and if a slave machine doesn’t reach the threshold, then > it will carry new task ignoring that there’s other task running on it > already? > > (2) If (1) is true, how can we avoid it? If (1) is not true, then what’s > the reason of this scenario and how to avoid it? > > > > Thanks very much in advance. J > > > > > > Best regards, > > Wisteria.Lavender > > One is never too old to learn. ^^ > > -- Harsh J http://harshj.com
