August 2014
Beginner to intermediate
304 pages
7h 10m
English
Content preview from Python 3 Text Processing with NLTK 3 Cookbook - Second EditionBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Chapter 8. Distributed Processing and Handling Large Datasets
In this chapter, we will cover the following recipes:
- Distributed tagging with execnet
- Distributed chunking with execnet
- Parallel list processing with execnet
- Storing a frequency distribution in Redis
- Storing a conditional frequency distribution in Redis
- Storing an ordered dictionary in Redis
- Distributed word scoring with Redis and execnet
Introduction
NLTK is great for in-memory, single-processor natural language processing. However, there are times when you have a lot of data to process and want to take advantage of multiple CPUs, multicore CPUs, and even multiple computers. Or, you might want to store frequencies and probabilities in a persistent, shared database so multiple processes can ...
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