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From John Lilley <john.lil...@redpoint.net>
Subject RE: Shuffle phase replication factor
Date Thu, 23 May 2013 17:22:01 GMT
Ling,
Thanks for the response!  I could use more clarification on item 1.  Specifically

*         mapred.reduce.parallel.copies  limits the number of outbound connections for a reducer,
but not the inbound connections for a mapper.  Does tasktracker.http.threads limit the number
of simultaneous inbound connections for a mapper, or only the size of the thread pool servicing
the connections?  (i.e. is it one thread per inbound connection?).

*         Who actually creates the listen port for serving up the mapper files?  The mapper
task?  Or something more persistent in MapReduce?
Thanks,
John

From: erlv5241@gmail.com [mailto:erlv5241@gmail.com] On Behalf Of Kun Ling
Sent: Wednesday, May 22, 2013 7:50 PM
To: user
Subject: Re: Shuffle phase replication factor

Hi John,


   1. for the number of  simultaneous connection limitations. You can configure this using
the mapred.reduce.parallel.copies flag. the default  is 5.

   2. For the aggressively disconnect implication, I am afraid it is only a little. Normally,
each reducer will connect to each mapper task, and asking for the partions of the map output
file.   Because there are about 5 simultaneous connections to fetch the map output for each
reducer. For a large MR cluster with 1000 node, and a Huge MR job with 1000 Mapper, and 1000
reducer, for each node, there are only about 5 connections. So the imply is only a little.


  3.  What happens to the pending/ failing coonection, the short answer is: just try to reconnect.
   There is a List<>, which maintain all the output of the Mapper that need to copied,
and the element will be removed iff the map output is successfully copied.  A forever loop
will keep on look into the List, and fetch the corrsponding map output.


  All the above answer is based on the Hadoop 1.0.4 source code, especially the ReduceTask.java
file.

yours,
Ling Kun

On Wed, May 22, 2013 at 10:57 PM, John Lilley <john.lilley@redpoint.net<mailto:john.lilley@redpoint.net>>
wrote:
Ummmm, is that also the limit for the number of simultaneous connections?  In general, one
does not need a 1:1 map between threads and connections.
If this is the connection limit, does it imply  that the client or server side aggressively
disconnects after a transfer?
What happens to the pending/failing connection attempts that exceed the limit?
Thanks!
john

From: Rahul Bhattacharjee [mailto:rahul.rec.dgp@gmail.com<mailto:rahul.rec.dgp@gmail.com>]
Sent: Wednesday, May 22, 2013 8:52 AM

To: user@hadoop.apache.org<mailto:user@hadoop.apache.org>
Subject: Re: Shuffle phase replication factor

There are properties/configuration to control the no. of copying threads for copy.
tasktracker.http.threads=40
Thanks,
Rahul

On Wed, May 22, 2013 at 8:16 PM, John Lilley <john.lilley@redpoint.net<mailto:john.lilley@redpoint.net>>
wrote:
This brings up another nagging question I've had for some time.  Between HDFS and shuffle,
there seems to be the potential for "every node connecting to every other node" via TCP. 
Are there explicit mechanisms in place to manage or limit simultaneous connections?  Is the
protocol simply robust enough to allow a server-side to disconnect at any time to free up
slots and the client-side will retry the request?
Thanks
john

From: Shahab Yunus [mailto:shahab.yunus@gmail.com<mailto:shahab.yunus@gmail.com>]
Sent: Wednesday, May 22, 2013 8:38 AM

To: user@hadoop.apache.org<mailto:user@hadoop.apache.org>
Subject: Re: Shuffle phase replication factor

As mentioned by Bertrand, Hadoop, The Definitive Guide, is well... really definitive :) place
to start. It is pretty thorough for starts and once you are gone through it, the code will
start making more sense too.

Regards,
Shahab

On Wed, May 22, 2013 at 10:33 AM, John Lilley <john.lilley@redpoint.net<mailto:john.lilley@redpoint.net>>
wrote:
Oh I see.  Does this mean there is another service and TCP listen port for this purpose?
Thanks for your indulgence... I would really like to read more about this without bothering
the group but not sure where to start to learn these internals other than the code.
john

From: Kai Voigt [mailto:k@123.org<mailto:k@123.org>]
Sent: Tuesday, May 21, 2013 12:59 PM
To: user@hadoop.apache.org<mailto:user@hadoop.apache.org>
Subject: Re: Shuffle phase replication factor

The map output doesn't get written to HDFS. The map task writes its output to its local disk,
the reduce tasks will pull the data through HTTP for further processing.

Am 21.05.2013 um 19:57 schrieb John Lilley <john.lilley@redpoint.net<mailto:john.lilley@redpoint.net>>:

When MapReduce enters "shuffle" to partition the tuples, I am assuming that it writes intermediate
data to HDFS.  What replication factor is used for those temporary files?
john


--
Kai Voigt
k@123.org<mailto:k@123.org>








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