April 2017
Intermediate to advanced
532 pages
12h 39m
English
book
Machine Learning with Spark - Second Edition
by Rajdeep Dua, Brian O'Neill, Stephen Boesch, Manpreet Singh Ghotra, Nick Pentreath
Content preview from Machine Learning with Spark - Second Edition
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Summary
In this chapter, we covered how to set up Spark locally on our own computer as well as in the cloud as a cluster running on Amazon EC2. You learned how to run Spark on top of Amazon's Elastic Map Reduce (EMR). You also learned how to use Google Compute Engine's Spark Service to create a cluster and run a simple job. We discussed the basics of Spark's programming model and API using the interactive Scala console, and we wrote the same basic Spark program in Scala, Java, R, and Python. We also compared the performance metrics of Hadoop versus Spark for different machine learning algorithms as well as SORT benchmark tests.
In the next chapter, we will consider how to go about using Spark to create a machine learning system.
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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.