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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Stream processing
Before covering online learning with Spark, we will first explore the basics of stream processing and introduce the Spark Streaming library.
In addition to the core Spark API and functionality, the Spark project contains another major library (in the same way as MLlib is a major project library) called Spark Streaming, which focuses on processing data streams in real time.
A data stream is a continuous sequence of records. Common examples include activity stream data from a web or mobile application, time-stamped log data, transactional data, and event streams from sensor or device networks.
The batch processing approach typically involves saving the data stream to an intermediate storage system (for example, HDFS or a database) ...
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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.