Sounds like you want more reducer to reduce the execution time but only
want a single output file.
Is this waht you want?
You can use as many as your want (may not be optimal) reducers when you are
running your reducer. Once the program is done, write a small perl, python,
or shell program connect those part-* files.
if you do not want to write your own script to connect those files and let
Hadoop automatically generate a single file.
It may need some patched to current Hadoop. I am not sure they are ready or
On Thu, Jan 3, 2013 at 10:45 PM, Vinod Kumar Vavilapalli <
[EMAIL PROTECTED]> wrote:
> Is it that you want the parallelism but a single final output? Assuming
> your first job's reducers generate a small output, another stage is the way
> to go. If not, second stage won't help. What exactly are your objectives?
> On Jan 3, 2013, at 1:11 PM, Pavel Hančar wrote:
> I'd like to use more than one reduce task with Hadoop Streaming and I'd
> like to have only one result. Is it possible? Or should I run one more job
> to merge the result? And is it the same with non-streaming jobs? Below you
> see, I have 5 results for mapred.reduce.tasks=5.
> $ hadoop jar
> -D mapred.reduce.tasks=5 -mapper /bin/cat -reducer /tmp/wcc -file /tmp/wcc
> -file /bin/cat -input /user/hadoopnlp/1gb -output 1gb.wc
> 13/01/03 22:00:03 INFO streaming.StreamJob: map 100% reduce 100%
> 13/01/03 22:00:07 INFO streaming.StreamJob: Job complete:
> 13/01/03 22:00:07 INFO streaming.StreamJob: Output: 1gb.wc
> $ hadoop dfs -cat 1gb.wc/part-*
> where /tmp/wcc contains
> wc -c
> Thanks for any answer,
> Pavel Hančar