November 2016
Beginner to intermediate
687 pages
15h 31m
English
book
Natural Language Processing: Python and NLTK
by Nitin Hardeniya, Jacob Perkins, Deepti Chopra, Nisheeth Joshi, Iti Mathur
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NLTK on Hadoop
We talked enough about NLTK as a library, and what are some of the most-used functions it gives us. Now, NLTK can solve many NLP problems from which many are highly parallelizable. This is the reason why we will try to use NLTK on Hadoop.
The best way of running NLTK on Hadoop is to get it installed on all the nodes of the cluster. This is probably not that difficult to achieve. There are ways in which you can do this, such as sending the resource files as a streaming argument. However, we will rather prefer the first option.
A UDF
There are a variety of ways in which we can make NLTK run on Hadoop. Let's talk about one example of using NLTK by doing tokenization in parallel using a Hive UDF.
For this use case, we have to follow these ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.