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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Transformations
As we saw in Chapter 1, Getting Up and Running with Spark, and throughout this book, Spark allows us to apply powerful transformations to RDDs. As DStreams are made up of RDDs, Spark Streaming provides a set of transformations available on DStreams; these transformations are similar to those available on RDDs. These include map, flatMap, filter, join, and reduceByKey.
Spark Streaming transformations, such as those applicable to RDDs, operate on each element of a DStream's underlying data. That is, the transformations are effectively applied to each RDD in the DStream, which, in turn, applies the transformation to the elements of the RDD.
Spark Streaming also provides operators such as reduce and count. These operators return ...
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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.