February 2016
Beginner to intermediate
326 pages
7h 46m
English
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Summary
In this chapter, we discussed Spark SQL as a one-stop solution for processing large data using a mix of SQL-like queries and complex procedural algorithms in-memory, producing results in seconds/minutes but not hours.
We started with the various aspects of Spark SQL including its architecture and various components. We also talked about the complete process of writing Spark SQL jobs in Scala and at the same time, we also talked about various methodologies for converting Spark RDDs into DataFrames. Toward the middle of the chapter, we executed various examples of Spark SQL using different data formats such as Hive/Parquet along with important aspects such as schema evolution and schema merging. Finally at the end, we discussed the various ...
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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.