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For running python Based MR tasks ,have a Look at: <a href="http://hadoop.apache.org/docs/r1.1.2/streaming.html" rel="nofollow">http://hadoop.apache.org/docs/r1.1.2/streaming.html</a> <a href="http://www.michael-noll.com/tutorials/writing-an-hadoop-mapreduce-program-in-python/" rel="nofollow">http://www.michael-noll.com/tutorials/writing-an-hadoop-mapreduce-program-in-python/</a> You need to design your code in Terms of Mapper - Reducer to enable Hadoop to execute your Python script. Read on the Map-Reduce Programming Paradigm before you can jump into writing the code. Its important to understand the MR programming paradigm and the role of {Key , value } pairs in solving the problem. <pre><code>#Modified your above code to generate the required output import urllib2 import random from operator import itemgetter current_word = {} current_count = 0 story = 'http://sixty-north.com/c/t.txt' request = urllib2.Request(story) response = urllib2.urlopen(request) each_word = [] words = None count = 1 same_words ={} word = [] """ looping the entire file """ #Collect All the words into a list for line in response: #print "Line = " , line line_words = line.split() for word in line_words: # looping each line and extracting words each_word.append(word) #for every word collected, in dict same_words #if a key exists, such that key == word then increment Mapping Value by 1 # Else add word as new key with mapped value as 1 for words in each_word: if words.lower() not in same_words.keys() : same_words[words.lower()]=1 else: same_words[words.lower()]=same_words[words.lower()]+1 for each in same_words.keys(): print "word = ",each, ", count = ",same_words[each] </code></pre>
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