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MapReduce >> mail # user >> Distributing the code to multiple nodes


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Re: Distributing the code to multiple nodes
Hello Chris,

I have now a cluster with 3 nodes and replication factor being 2. When I
distribute a file I could see that there are replica of data available in
other nodes. However when I run a map reduce job again only one node is
serving all the request :(. Can you or anyone please provide some more
inputs.

Thanks
Ashish
On Wed, Jan 8, 2014 at 7:16 PM, Chris Mawata <[EMAIL PROTECTED]> wrote:

> 2 nodes and replication factor of 2 results in a replica of each block
> present on each node. This would allow the possibility that a single node
> would do the work and yet be data local.  It will probably happen if that
> single node has the needed capacity.  More nodes than the replication
> factor are needed to force distribution of the processing.
> Chris
> On Jan 8, 2014 7:35 AM, "Ashish Jain" <[EMAIL PROTECTED]> wrote:
>
>> Guys,
>>
>> I am sure that only one node is being used. I just know ran the job again
>> and could see that CPU usage only for one server going high other server
>> CPU usage remains constant and hence it means other node is not being used.
>> Can someone help me to debug this issue?
>>
>> ++Ashish
>>
>>
>> On Wed, Jan 8, 2014 at 5:04 PM, Ashish Jain <[EMAIL PROTECTED]> wrote:
>>
>>> Hello All,
>>>
>>> I have a 2 node hadoop cluster running with a replication factor of 2. I
>>> have a file of size around 1 GB which when copied to HDFS is replicated to
>>> both the nodes. Seeing the block info I can see the file has been
>>> subdivided into 8 parts which means it has been subdivided into 8 blocks
>>> each of size 128 MB.  I use this file as input to run the word count
>>> program. Some how I feel only one node is doing all the work and the code
>>> is not distributed to other node. How can I make sure code is distributed
>>> to both the nodes? Also is there a log or GUI which can be used for this?
>>> Please note I am using the latest stable release that is 2.2.0.
>>>
>>> ++Ashish
>>>
>>
>>