Exploring Google Ngrams with Amazon EMR
SPL-31 Version 4.0.6
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In this lab, you will use Amazon EMR to analyze Ngrams from Google Books. An n-gram is a contiguous sequence of n items from a given sequence of text or speech. For example, consider this sentence:
Some 2-grams from this sentence are "the sun", "in the" and "sets in". A sample 3-gram is "sets in the" and a sample 4-gram is "rises in the east".
N-grams are used to predict the probability of certain words appearing in a sequence. This can be useful for providing typing suggestions on web pages and mobile phones.
The steps in this lab are very similar to the activities that a Data Scientist would perform when analyzing a new set of data. This includes loading the data, examining the data attributes and writing SQL to analyze the data. You will run SQL against publicly available Ngrams data stored in Amazon S3 to gain interesting insights.
After completing this lab, you will be able to:
- Create an Amazon EMR cluster running Hive and Ganglia
- Use Hive statements to create tables from Google Ngram input data stored in Amazon S3
- Run Hive queries to drill-down and analyze data
- Use Ganglia to monitor an AMR cluster
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