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NLTK python UDF script using streaming python
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from pig_util import outputSchema | |
import nltk | |
@outputSchema("top_five:bag{t:(bigram:chararray)}") | |
def top_5_bigrams(tweets): | |
tokenized_tweets = [ nltk.tokenize.WhitespaceTokenizer().tokenize(t[0]) for t in tweets ] | |
bgm = nltk.collocations.BigramAssocMeasures() | |
finder = nltk.collocations.BigramCollocationFinder.from_documents(tokenized_tweets) | |
top_5 = finder.nbest(bgm.likelihood_ratio, 5) | |
return [ ("%s %s" % (s[0], s[1]),) for s in top_5 ] |
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