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From Shivani Rao <sg...@purdue.edu>
Subject Hadoop 0.21 running problems , no namenode to stop
Date Thu, 03 Mar 2011 04:54:52 GMT
Problems running local installation of hadoop on single-node cluster

I followed instructions given by tutorials to run hadoop-0.21 on a single node cluster. 

The first problem I encountered was that of HADOOP-6953. Thankfully that has got fixed.

The other problem I am facing is that the datanode does not start. This I guess because when
I run stop-dfs.sh  for datanode, I get a message 
"no datanode to stop"

I am wondering if it is related remotely to the difference in the IP addresses on my computer	localhost	my-laptop 

Although I am aware of this, I do not know how to fix this.

I am unable to even run a simple pi estimate example on the haddop installation

This is the output I get is

bin/hadoop jar hadoop-mapred-examples-0.21.0.jar pi 10 10
Number of Maps  = 10
Samples per Map = 10
11/03/02 23:38:47 INFO security.Groups: Group mapping impl=org.apache.hadoop.security.ShellBasedUnixGroupsMapping;

And nothing else for long long time.

I have not set the dfs.namedir and dfs.datadir in my hdfs-site.xml. But After running bin/hadoop
namenode -format, I see that the tmp.dir has a folder with dfs/data and dfs/data folders for
the two directories. 

what Am I doing wrong? Any help is appreciated.

Here are my configuration files



  <description>Default block replication.
  The actual number of replications can be specified when the file is created.
  The default is used if replication is not specified in create time.


  <description>A base for other temporary directories.</description>

  <description>The name of the default file system.  A URI whose
  scheme and authority determine the FileSystem implementation.  The
  uri's scheme determines the config property (fs.SCHEME.impl) naming
  the FileSystem implementation class.  The uri's authority is used to
  determine the host, port, etc. for a filesystem.</description>


  <description>The host and port that the MapReduce job tracker runs
  at.  If "local", then jobs are run in-process as a single map
  and reduce task.

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