February 2016
Beginner to intermediate
326 pages
7h 46m
English
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Resilient distributed datasets (RDD)
In this section, we will talk about the architecture, motivation, features, and other important concepts related to RDD. We will also briefly talk about the implementation methodology adopted by Spark and various APIs/functions exposed by RDDs.
Frameworks such as Hadoop and MapReduce are widely adopted for parallel and distributed data processing. There is no doubt that these frameworks introduce a new paradigm for distributed data processing and that too in a fault-tolerant manner (without losing a single byte). However, these frameworks do have some limitations; for example, Hadoop is not suited for the problem statements where we need iterative data processing as in recursive functions or machine learning ...
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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.