Hi David,
Thanks for your response.

But I can't install anything on cluster. 
Could anyone please help me understand how the file 'multiarray.so' is used by the tagger. I mean how it is loaded( I assume its some sort of DLL for windows and shared library for unix based systems). Is it a module or what?

Right now what I did is I packaged numpy so that numpy will be present at the current working directory for mapper and reducer. So now control goes into numpy packaged alongwith mapper. 
But still right now I see such error:

File "glossextractionengine.mod/nltk/tag/__init__.py", line 123, in pos_tag
  File "glossextractionengine.mod/pickle.py", line 1380, in load
    return doctest.testmod()
  File "glossextractionengine.mod/pickle.py", line 860, in load
    return stopinst.value
  File "glossextractionengine.mod/pickle.py", line 1092, in load_global
    dispatch[GLOBAL] = load_global
  File "glossextractionengine.mod/pickle.py", line 1126, in find_class
    klass = getattr(mod, name)
  File "numpy.mod/numpy/__init__.py", line 137, in <module>
  File "numpy.mod/numpy/add_newdocs.py", line 13, in <module>
  File "numpy.mod/numpy/lib/__init__.py", line 4, in <module>
  File "numpy.mod/numpy/lib/type_check.py", line 21, in <module>
  File "numpy.mod/numpy/core/__init__.py", line 9, in <module>
ImportError: No module named multiarray

In this case the file 'multiarray.so' is present in within core package only, but it is still not found.
Can anyone throw some light on it.


On Wed, Feb 11, 2015 at 7:17 AM, Daπid <davidmenhur@gmail.com> wrote:
On 11 February 2015 at 08:06, Kartik Kumar Perisetla
<kartik.peri@gmail.com> wrote:
> Thanks David. But do I need to install virtualenv on every node in hadoop
> cluster? Actually I am not very sure whether same namenodes are assigned for
> my every hadoop job. So how shall I proceed on such scenario.

I have never used hadoop, but in the clusters I have used, you have a
home folder on the central node, and each and every computing node has
access to it. You can then install Python in your home folder and make
every node run that, or pull a local copy.

Probably the cluster support can clear this up further and adapt it to
your particular case.

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