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From Chris Mawata <chris.maw...@gmail.com>
Subject Re: Running Hadoop v2 clustered mode MR on an NFS mounted filesystem
Date Sat, 21 Dec 2013 02:36:13 GMT
Yong raises an important issue:  You have thrown out the I/O advantages 
of HDFS and also thrown out the advantages of data locality. It would be 
interesting to know why you are taking this approach.

On 12/20/2013 9:28 AM, java8964 wrote:
> I believe the "-fs local" should be removed too. The reason is that 
> even you have a dedicated JobTracker after removing "-jt local", but 
> with "-fs local", I believe that all the mappers will be run 
> sequentially.
> "-fs local" will force the mapreducer run in "local" mode, which is 
> really a test mode.
> What you can do is to remove both "-fs local -jt local", but give the 
> FULL URI of the input and output path, to tell Hadoop that they are 
> local filesystem instead of HDFS.
> "hadoop jar 
> /hduser/hadoop/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.2.0.jar 
> wordcount file:///hduser/mount_point file:///results"
> Keep in mind followings:
> 1) The NFS mount need to be available in all your Task Nodes, and 
> mounted in the same way.
> 2) Even you can do that, but your sharing storage will be your 
> bottleneck. NFS won't work well for scalability.
> Yong
> ------------------------------------------------------------------------
> Date: Fri, 20 Dec 2013 09:01:32 -0500
> Subject: Re: Running Hadoop v2 clustered mode MR on an NFS mounted 
> filesystem
> From: dsuiter@rdx.com
> To: user@hadoop.apache.org
> I think most of your problem is coming from the options you are setting:
> "hadoop jar 
> /hduser/hadoop/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.2.0.jar 
> wordcount *-fs local -jt local* /hduser/mount_point/  /results"
> You appear to be directing your namenode to run jobs in the 
> *LOCAL* job runner and directing it to read from the 
> *LOCAL* filesystem. Drop the *-jt* argument and it should run in 
> distributed mode if your cluster is set up right. You don't need to do 
> anything special to point Hadoop towards a NFS location, other than 
> set up the NFS location properly and make sure if you are directing to 
> it by name that it will resolve to the right address. Hadoop doesn't 
> care where it is, as long as it can read from and write to it. The 
> fact that you are telling it to read/write from/to a NFS location that 
> happens to be mounted as a local filesystem object doesn't matter - 
> you could direct it to the local /hduser/ path and set the -fs local 
> option, and it would end up on the NFS mount, because that's where the 
> NFS mount actually exists, or you could direct it to the absolute 
> network location of the folder that you want, it shouldn't make a 
> difference.
> *Devin Suiter*
> Jr. Data Solutions Software Engineer
> 100 Sandusky Street | 2nd Floor | Pittsburgh, PA 15212
> Google Voice: 412-256-8556 | www.rdx.com <http://www.rdx.com/>
> On Fri, Dec 20, 2013 at 5:27 AM, Atish Kathpal 
> <atish.kathpal@gmail.com <mailto:atish.kathpal@gmail.com>> wrote:
>     Hello
>     The picture below describes the deployment architecture I am
>     trying to achieve.
>     However, when I run the wordcount example code with the below
>     configuration, by issuing the command from the master node, I
>     notice only the master node spawning map tasks and completing the
>     submitted job. Below is the command I used:
>     *hadoop jar
>     /hduser/hadoop/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.2.0.jar
>     wordcount -fs local -jt local /hduser/mount_point/  /results*
>     _Question: How can I leverage both the hadoop nodes for running
>     MR, while serving my data from the common NFS mount point running
>     my filesystem at the backend? Has any one tried such a setup before?_
>     Inline image 1
>     Thanks!

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