If you look at larger cluster and jobs that involve larger input data sets.
The data would be spread across the whole cluster, and a single node might
have various blocks of that entire data set. Imagine you have a cluster
with 100 map slots and your job has 500 map tasks, now in that case there
should be multiple map tasks in a single task tracker based on slot
Here if you enable jvm reuse, all tasks related to a job on a single
TaskTracker would use the same jvm. The benefit here is just the time you
are saving in spawning and cleaning up jvm for individual tasks.
On Tue, Apr 16, 2013 at 2:04 PM, Rahul Bhattacharjee <
[EMAIL PROTECTED]> wrote:
> I have a question related to VM reuse in Hadoop.I now understand the
> purpose of VM reuse , but I am wondering how is it useful.
> Example. for VM reuse to be effective or kicked in , we need more than one
> mapper task to be submitted to a single node (for the same job).Hadoop
> would consider spawning mappers into nodes which actually contains the data
> , it might rarely happen that multiple mappers are allocated to a single
> task tracker. And even if a single task nodes gets to run multiple mappers
> then it might as well run in parallel in multiple VM rather than
> sequentially in a single VM.
> I am sure I am missing some link here , please help me find that.