October 2015
Beginner to intermediate
254 pages
5h 31m
English
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Chapter 6. Scaling Up
In this chapter, we will cover the following recipes:
- Building the Uber JAR
- Submitting jobs to the Spark cluster (local)
- Running the Spark standalone cluster on EC2
- Running the Spark job on Mesos (local)
- Running the Spark job on YARN (local)
Introduction
In this chapter, we'll be looking at how to bundle our Spark application and deploy it on various distributed environments.
As we discussed earlier in Chapter 3, Loading and Preparing Data – DataFrame the foundation of Spark is the RDD. From a programmer's perspective, the composability of RDDs such as a regular Scala collection is a huge advantage. RDD wraps three vital (and two subsidiary) pieces of information that help in reconstruction of data. This enables fault tolerance. ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
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.