October 2021
Beginner to intermediate
322 pages
7h 27m
English
Content preview from Essential PySpark for Scalable Data Analytics
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Chapter 1: Distributed Computing Primer
This chapter introduces you to the Distributed Computing paradigm and shows you how Distributed Computing can help you to easily process very large amounts of data. You will learn about the concept of Data Parallel Processing using the MapReduce paradigm and, finally, learn how Data Parallel Processing can be made more efficient by using an in-memory, unified data processing engine such as Apache Spark.
Then, you will dive deeper into the architecture and components of Apache Spark along with code examples. Finally, you will get an overview of what's new with the latest 3.0 release of Apache Spark.
In this chapter, the key skills that you will acquire include an understanding of the basics of the Distributed ...
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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.
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.