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Learning Apache Spark 2

You're reading from   Learning Apache Spark 2 A beginner's guide to real-time Big Data processing using the Apache Spark framework

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781785885136
Length 356 pages
Edition 1st Edition
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Author (1):
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 Abbasi Abbasi
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Abbasi
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Table of Contents (18) Chapters Close

Learning Apache Spark 2
Credits
About the Author
About the Reviewers
www.packtpub.com
Customer Feedback
Preface
1. Architecture and Installation FREE CHAPTER 2. Transformations and Actions with Spark RDDs 3. ETL with Spark 4. Spark SQL 5. Spark Streaming 6. Machine Learning with Spark 7. GraphX 8. Operating in Clustered Mode 9. Building a Recommendation System 10. Customer Churn Prediction 1. Theres More with Spark

PairRDDs


So far we have seen basic RDD where elements have been words, numbers, or lines of text. We'll now discuss PairRDD, which are essentially datasets of key/value pairs. People who have been using MapReduce will be familiar with the concept of key/value pairs and their benefits during aggregation, joining, sorting, counting, and other ETL operations. The beauty of having key value pairs is that you can operate on data belonging to a particular key in parallel, which includes operations such as aggregation or joining. The simplest example could be retail store sales with StoreId as the key, and the sales amount as the value. This helps you perform advanced analytics on StoreId, which can be used to operate the data in parallel.

Creating PairRDDs

The first step in understanding PairRDDs is to understand how they are created. As we have seen previously, it is not necessary that we have the data available in key/value form upon ingestion and hence there is a need to transform the data using...

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