February 2017
Intermediate to advanced
274 pages
5h 58m
English
Content preview from Learning PySparkBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Summary
With Spark DataFrames, Python developers can make use of a simpler abstraction layer that is also potentially significantly faster. One of the main reasons Python is initially slower within Spark is due to the communication layer between Python sub-processes and the JVM. For Python DataFrame users, we have a Python wrapper around Scala DataFrames that avoids the Python sub-process/JVM communication overhead. Spark DataFrames has many performance enhancements through the Catalyst Optimizer and Project Tungsten which we have reviewed in this chapter. In this chapter, we also reviewed how to work with Spark DataFrames and worked on an on-time flight performance scenario using DataFrames.
In this chapter, we created and worked with DataFrames ...
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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.