October 2019
Beginner to intermediate
293 pages
6h 55m
English
Content preview from Mastering Spark with R
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Chapter 7. Connections
They don’t get to choose.
—Daenerys Targaryen
Chapter 6 presented the major cluster computing trends, cluster managers, distributions, and cloud service providers to help you choose the Spark cluster that best suits your needs. In contrast, this chapter presents the internal components of a Spark cluster and how to connect to a particular Spark cluster.
When reading this chapter, don’t try to execute every line of code; this would be quite hard since you would need to prepare different Spark environments. Instead, if you already have a Spark cluster or if the previous chapter gets you motivated enough to sign up for an on-demand cluster, now is the time to learn how to connect to it. This chapter helps you connect to your cluster, which you should have already chosen by now. Without a cluster, we recommend that you learn the concepts and come back to execute code later on.
In addition, this chapter provides various troubleshooting connection techniques. While we hope you won’t need to use them, this chapter prepares you to use them as effective techniques to resolve connectivity issues.
While this chapter might feel a bit dry—connecting and troubleshooting connections is definitely not the most exciting part of large-scale computing—it introduces the components of a Spark cluster and how they interact, often known as the architecture of Apache Spark. This chapter, along with Chapters 8 and 9, will provide a detailed view of how Spark works, which will help ...
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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.