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Machine Learning with Spark - Second Edition
book

Machine Learning with Spark - Second Edition

by Rajdeep Dua, Brian O'Neill, Stephen Boesch, Manpreet Singh Ghotra, Nick Pentreath
April 2017
Intermediate to advanced
532 pages
12h 39m
English
Packt Publishing
Content preview from Machine Learning with Spark - Second Edition

Creating RDDs

RDDs can be Scala Spark shells that you launched earlier:

val collection = List("a", "b", "c", "d", "e") val rddFromCollection = sc.parallelize(collection)

RDDs can also be created from Hadoop-based input sources, including the local filesystem, HDFS, and Amazon S3. A Hadoop-based RDD can utilize any input format that implements the Hadoop InputFormat interface, including text files, other standard Hadoop formats, HBase, Cassandra, tachyon, and many more.

The following code is an example of creating an RDD from a text file located on the local filesystem:

val rddFromTextFile = sc.textFile("LICENSE")

The preceding textFile method returns an RDD where each record is a String object that represents one line of the text file. ...

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Publisher Resources

ISBN: 9781785889936