March 2019
Beginner to intermediate
182 pages
4h 6m
English
Content preview from Hands-On Big Data Analytics with PySpark
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Using keyBy() operations to reduce shuffle
In this section, we will use keyBy() operations to reduce shuffle. We will cover the following topics:
- Loading randomly partitioned data
- Trying to pre-partition data in a meaningful way
- Leveraging the keyBy() function
We will load randomly partitioned data, but this time using the RDD API. We will repartition the data in a meaningful way and extract the information that is going on underneath, similar to DataFrame and the Dataset API. We will learn how to leverage the keyBy() function to give our data some structure and to cause the pre-partitioning in the RDD API.
Here is the test we will be using in this section. We are creating two random input records. The first record has a random user ...
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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.