June 2017
Beginner to intermediate
296 pages
7h 4m
English
Content preview from Frank Kane's Taming Big Data with Apache Spark and Python
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Spark is scalable
The way that Spark scales data analysis problems is, it runs on top of a cluster manager, so your actual Spark scripts are just everyday scripts written in Python, Java, or Scala; they behave just like any other script. Your "driver program" is what we call it, and it will run on your desktop or on one master node of your cluster. However, under the hood, when you run it, Spark knows how to take the work and actually farm it out to different computers on your cluster or even different CPUs on the same machine. Spark can actually run on top of different cluster managers. It has its own built-in cluster manager that you can use by default, but if you have access to a Hadoop cluster there's a component called YARN, that Spark ...
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