Less work by skipping setting up the input splits, distributing the job jar
files, scheduling the map tasks on the task trackers, collecting the task
status results, then starting all the reduce tasks, collecting all the
results, sorting them, feeding them to the reduce tasks, then writing them
to
Thanks Aaron. That worked! However, when i run everything as local, I
see everything executing much faster on local as compared to a single
node. Is there any reason for the same?
-Asim
On Thu, Apr 30, 2009 at 9:23 AM, Aaron Kimball wrote:
> First thing I would do is to run the job in the local
First thing I would do is to run the job in the local jobrunner (as a single
process on your local machine without involving the cluster):
JobConf conf = .
// set other params, mapper, etc. here
conf.set("mapred.job.tracker", "local"); // use localjobrunner
conf.set("fs.default.name", "file://
