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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Input sources
Spark Streaming receivers are responsible for receiving data from an input source and converting the raw data into a DStream made up of Spark RDDs.
Spark Streaming supports various input sources, including file-based sources (where the receiver watches for new files arriving at the input location and creates the DStream from the contents read from each new file) and network-based sources (such as receivers that communicate with socket-based sources, the Twitter API stream, Akka actors, or message queues and distributed stream and log transfer frameworks, such as Flume, Kafka, and Amazon Kinesis).
See the documentation on input sources at http://spark.apache.org/docs/latest/streaming-programming-guide.html#input-dstreams for ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
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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.