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From java8964 java8964 <java8...@hotmail.com>
Subject RE: running map tasks in remote node
Date Fri, 23 Aug 2013 14:11:14 GMT
It is possible to do what you are trying to do, but only make sense if your MR job is very
CPU intensive, and you want to use the CPU resource in your cluster, instead of the IO.
You may want to do some research about what is the HDFS's role in Hadoop. First but not least,
it provides a central storage for all the files will be processed by MR jobs. If you don't
want to use HDFS, so you need to  identify a share storage to be shared among all the nodes
in your cluster. HDFS is NOT required, but a shared storage is required in the cluster.
For simply your question, let's just use NFS to replace HDFS. It is possible for a POC to
help you understand how to set it up.
Assume your have a cluster with 3 nodes (one NN, two DN. The JT running on NN, and TT running
on DN). So instead of using HDFS, you can try to use NFS by this way:
1) Mount /share_data in all of your 2 data nodes. They need to have the same mount. So /share_data
in each data node point to the same NFS location. It doesn't matter where you host this NFS
share, but just make sure each data node mount it as the same /share_data2) Create a folder
under /share_data, put all your data into that folder.3) When kick off your MR jobs, you need
to give a full URL of the input path, like 'file:///shared_data/myfolder', also a full URL
of the output path, like 'file:///shared_data/output'. In this way, each mapper will understand
that in fact they will run the data from local file system, instead of HDFS. That's the reason
you want to make sure each task node has the same mount path, as 'file:///shared_data/myfolder'
should work fine for each  task node. Check this and make sure that /share_data/myfolder all
point to the same path in each of your task node.4) You want each mapper to process one file,
so instead of using the default 'TextInputFormat', use a 'WholeFileInputFormat', this will
make sure that every file under '/share_data/myfolder' won't be split and sent to the same
mapper processor. 5) In the above set up, I don't think you need to start NameNode or DataNode
process any more, anyway you just use JobTracker and TaskTracker.6) Obviously when your data
is big, the NFS share will be your bottleneck. So maybe you can replace it with Share Network
Storage, but above set up gives you a start point.7) Keep in mind when set up like above,
you lost the Data Replication, Data Locality etc, that's why I said it ONLY makes sense if
your MR job is CPU intensive. You simple want to use the Mapper/Reducer tasks to process your
data, instead of any scalability of IO.
Make sense?
Yong

Date: Fri, 23 Aug 2013 15:43:38 +0530
Subject: Re: running map tasks in remote node
From: rabmdu@gmail.com
To: user@hadoop.apache.org

Thanks for the reply. 
I am basically exploring possible ways to work with hadoop framework for one of my use case.
I have my limitations in using hdfs but agree with the fact that using map reduce in conjunction
with hdfs makes sense.  

I successfully tested wholeFileInputFormat by some googling. 
Now, coming to my use case. I would like to keep some files in my master node and want to
do some processing in the cloud nodes. The policy does not allow us to configure and use cloud
nodes as HDFS.  However, I would like to span a map process in those nodes. Hence, I set input
path as local file system, for example, $HOME/inputs. I have a file listing filenames (10
lines) in this input directory.  I use NLineInputFormat and span 10 map process. Each map
process gets a line. The map process will then do a file transfer and process it.  However,
I get an error in the map saying that the FileNotFoundException $HOME/inputs. I am sure this
directory is present in my master but not in the slave nodes. When I copy this input directory
to slave nodes, it works fine. I am not able to figure out how to fix this and the reason
for the error. I am not understand why it complains about the input directory is not present.
As far as I know, slave nodes get a map and map method contains contents of the input file.
This should be fine for the map logic to work.


with regardsrabmdu



On Thu, Aug 22, 2013 at 4:40 PM, java8964 java8964 <java8964@hotmail.com> wrote:




If you don't plan to use HDFS, what kind of sharing file system you are going to use between
cluster? NFS?For what you want to do, even though it doesn't make too much sense, but you
need to the first problem as the shared file system.

Second, if you want to process the files file by file, instead of block by block in HDFS,
then you need to use the WholeFileInputFormat (google this how to write one). So you don't
need a file to list all the files to be processed, just put them into one folder in the sharing
file system, then send this folder to your MR job. In this way, as long as each node can access
it through some file system URL, each file will be processed in each mapper.

Yong

Date: Wed, 21 Aug 2013 17:39:10 +0530
Subject: running map tasks in remote node
From: rabmdu@gmail.com
To: user@hadoop.apache.org


Hello, 

Here is the new bie question of the day. For one of my use cases, I want to use hadoop map
reduce without HDFS. Here, I will have a text file containing a list of file names to process.
Assume that I have 10 lines (10 files to process) in the input text file and I wish to generate
10 map tasks and execute them in parallel in 10 nodes. I started with basic tutorial on hadoop
and could setup single node hadoop cluster and successfully tested wordcount code.

 Now, I took two machines A (master) and B (slave). I did the below configuration in these
machines to setup a two node cluster.

 hdfs-site.xml

 <?xml version="1.0"?>

<?xml-stylesheet type="text/xsl" href="configuration.xsl"?><!-- Put site-specific
property overrides in this file. -->

<configuration><property>

          <name>dfs.replication</name>          <value>1</value>

</property><property>

  <name>dfs.name.dir</name>  <value>/tmp/hadoop-bala/dfs/name</value>

</property><property>

  <name>dfs.data.dir</name>  <value>/tmp/hadoop-bala/dfs/data</value>

</property><property>

     <name>mapred.job.tracker</name>    <value>A:9001</value>

</property> 

</configuration> mapred-site.xml

 <?xml version="1.0"?>

<?xml-stylesheet type="text/xsl" href="configuration.xsl"?> 

<!-- Put site-specific property overrides in this file. --> 

<configuration><property>

            <name>mapred.job.tracker</name>            <value>A:9001</value>

</property><property>

          <name>mapreduce.tasktracker.map.tasks.maximum</name>
           <value>1</value>
</property></configuration>

 core-site.xml 

<?xml version="1.0"?><?xml-stylesheet type="text/xsl" href="configuration.xsl"?>

<!-- Put site-specific property overrides in this file. --><configuration>

         <property>                <name>fs.default.name</name>

                <value>hdfs://A:9000</value>        </property>

</configuration> 

 In A and B, I do have a file named ‘slaves’ with an entry ‘B’ in it and another file
called ‘masters’ wherein an entry ‘A’ is there.

 I have kept my input file at A. I see the map method process the input file line by line
but they are all processed in A. Ideally, I would expect those processing to take place in
B.

 Can anyone highlight where I am going wrong?

  regardsrab
 		 	   		  

 		 	   		  
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