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From "GOEKE, MATTHEW (AG/1000)" <matthew.go...@monsanto.com>
Subject RE: phases of Hadoop Jobs
Date Mon, 19 Sep 2011 19:19:54 GMT
Was the command line output really ever intended to be *that* verbose? I can see how it would
be useful but considering how easy it is to interact with the web-ui I can't see why much
effort should be put into enhancing it. Even if you didn't want to see all of the details
the web-ui has to offer it doesn't take long to learn how to skim it and get 10x more accurate
reading on your job progress.


-----Original Message-----
From: Arun C Murthy [mailto:acm@hortonworks.com] 
Sent: Sunday, September 18, 2011 11:27 PM
To: common-user@hadoop.apache.org
Subject: Re: phases of Hadoop Jobs


At least, I believe the new web-ui for MRv2 is (or will be soon) more verbose about this.

On Sep 18, 2011, at 9:23 PM, Kai Voigt wrote:

> Hi,
> this 0-33-66-100% phases are really confusing to beginners. We see that in our training
classes. The output should be more verbose, such as breaking down the phases into seperate
progress numbers.
> Does that make sense?
> Am 19.09.2011 um 06:17 schrieb Arun C Murthy:
>> Nan,
>> The 'phase' is implicitly understood by the 'progress' (value) made by the map/reduce
tasks (see o.a.h.mapred.TaskStatus.Phase).
>> For e.g. 
>> Reduce: 
>> 0-33% -> Shuffle
>> 34-66% -> Sort (actually, just 'merge', there is no sort in the reduce since all
map-outputs are sorted)
>> 67-100% -> Reduce
>> With 0.23 onwards the Map has phases too:
>> 0-90% -> Map
>> 91-100% -> Final Sort/merge
>> Now,about starting reduces early - this is done to ensure shuffle can proceed for
completed maps while rest of the maps run, there-by pipelining shuffle and map completion.
There is a 'reduce slowstart' feature to control this - by default, reduces aren't started
until 5% of maps are complete. Users can set this higher.
>> Arun
>> On Sep 18, 2011, at 7:24 PM, Nan Zhu wrote:
>>> Hi, all
>>> recently, I was hit by a question, "how is a hadoop job divided into 2
>>> phases?",
>>> In textbooks, we are told that the mapreduce jobs are divided into 2 phases,
>>> map and reduce, and for reduce, we further divided it into 3 stages,
>>> shuffle, sort, and reduce, but in hadoop codes, I never think about
>>> this question, I didn't see any variable members in JobInProgress class
>>> to indicate this information,
>>> and according to my understanding on the source code of hadoop, the reduce
>>> tasks are unnecessarily started until all mappers are finished, in
>>> constract, we can see the reduce tasks are in shuffle stage while there are
>>> mappers which are still in running,
>>> So how can I indicate the phase which the job is belonging to?
>>> Thanks
>>> -- 
>>> Nan Zhu
>>> School of Electronic, Information and Electrical Engineering,229
>>> Shanghai Jiao Tong University
>>> 800,Dongchuan Road,Shanghai,China
>>> E-Mail: zhunansjtu@gmail.com
> -- 
> Kai Voigt
> k@123.org

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