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Fast Data Processing with Spark 2

You're reading from   Fast Data Processing with Spark 2 Accelerate your data for rapid insight

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Product type Paperback
Published in Oct 2016
Publisher Packt
ISBN-13 9781785889271
Length 274 pages
Edition 3rd Edition
Languages
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Authors (2):
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Krishna Sankar Krishna Sankar
Author Profile Icon Krishna Sankar
Krishna Sankar
Holden Karau Holden Karau
Author Profile Icon Holden Karau
Holden Karau
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Toc

Table of Contents (13) Chapters Close

Preface 1. Installing Spark and Setting Up Your Cluster 2. Using the Spark Shell FREE CHAPTER 3. Building and Running a Spark Application 4. Creating a SparkSession Object 5. Loading and Saving Data in Spark 6. Manipulating Your RDD 7. Spark 2.0 Concepts 8. Spark SQL 9. Foundations of Datasets/DataFrames – The Proverbial Workhorse for DataScientists 10. Spark with Big Data 11. Machine Learning with Spark ML Pipelines 12. GraphX

Summary


This was a slightly longer chapter, but I am sure you have progressed to be experts in Spark by now. We started by looking at graph processing and then moved on to GraphX APIs and finally to a case study. Keep a look out for more GraphX APIs and also the new GraphFrame API, which is being developed for querying. We also have come to the end of this book. You started by installing Spark and understanding Spark from the basics, then you progressed to RDDs, Datasets, SQL, big data, and machine learning. In the process, we also discussed how Spark has matured from 1.x to 2.x, what data scientists would look for in a framework such as Spark, and the Spark architecture. We (the authors, editors, reviewers, and the rest of the gang at Packt) enjoyed writing this book, and we hope you were able to get a good start on your journey to distributed computing with Apache Spark.

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