Restrictions in terms of using external libraries (Python) in a Storm Bolt
Question: I want to implement a Bolt (<https://github.com/nathanmarz/storm>) that does
some heavy processing on a tuples using scikit Machine Learning API
(<http://scikit-learn.org/>)

For example -

    
    
    from sklearn import decomposition
    from sklearn import datasets
    
    trans_corpus = vectorizer.fit_transform(corpus)
    tfidf = text.TfidfTransformer().fit_transform(trans_corpus)
    ...
    ...
    

Is this possible ? Is having sklearn and all it's dependencies installed on
each node in the cluster enough?


Answer: Theoretically, it should be possible unless there is something really weird
about scikit I don't know. You just need to build your topologies such that
you can write your bolts in Python, which I suspect you already know is
possible and there are plenty of examples.

