Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Hands-On Big Data Analytics with PySpark

You're reading from   Hands-On Big Data Analytics with PySpark Analyze large datasets and discover techniques for testing, immunizing, and parallelizing Spark jobs

Arrow left icon
Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781838644130
Length 182 pages
Edition 1st Edition
Languages
Tools
Concepts
Arrow right icon
Authors (3):
Arrow left icon
James Cross James Cross
Author Profile Icon James Cross
James Cross
Bartłomiej Potaczek Bartłomiej Potaczek
Author Profile Icon Bartłomiej Potaczek
Bartłomiej Potaczek
Rudy Lai Rudy Lai
Author Profile Icon Rudy Lai
Rudy Lai
Arrow right icon
View More author details
Toc

Table of Contents (15) Chapters Close

Preface 1. Installing Pyspark and Setting up Your Development Environment FREE CHAPTER 2. Getting Your Big Data into the Spark Environment Using RDDs 3. Big Data Cleaning and Wrangling with Spark Notebooks 4. Aggregating and Summarizing Data into Useful Reports 5. Powerful Exploratory Data Analysis with MLlib 6. Putting Structure on Your Big Data with SparkSQL 7. Transformations and Actions 8. Immutable Design 9. Avoiding Shuffle and Reducing Operational Expenses 10. Saving Data in the Correct Format 11. Working with the Spark Key/Value API 12. Testing Apache Spark Jobs 13. Leveraging the Spark GraphX API 14. Other Books You May Enjoy

Summary

In this chapter, we first saw available the transformations on key/value pairs. We then learned how to use aggregateByKey instead of groupBy. We also covered actions on key/value pairs. Later, we looked at available partitioners like rangePartitioner and HashPartition on key/value data. By the end of this chapter, we had implemented our custom partitioner, which was able to assign partitions, based on the end and start of the range for learning purposes.

In the next chapter, we will learn how to test our Spark jobs and Apache Spark jobs.

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image