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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

Product type Paperback

Published in Oct 2016

Publisher Packt

ISBN-13 9781785889271

Length 274 pages

Edition 3rd Edition

Languages

Scala

Tools

Apache Spark

Concepts

Data Processing

Authors (2):

Krishna Sankar

Holden Karau

View More author details

Table of Contents (13) Chapters

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

Developing Spark with other IDEs

IntelliJ is a very popular IDE, which a lot of engineers use for developing Spark applications. I also like the Zeppelin IDE, which is very interactive, with good visualization capabilities, and supports Python, Scala, Java, and SQL.

To keep it simple and focused on our goals of working with Spark, we will use the Spark shell most of the time in this book.

Tip

We want to make sure you understand the essentials of Spark and get to work with all its features and not worry about IDEs. Once you are familiar with Spark, you can use your favorite language and IDE.

The rest of the chapter is locked

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Authors (2)

Karau

Karau

Holden Karau is a software development engineer and is active in the open source. She has worked on a variety of search, classification, and distributed systems problems at IBM, Alpine, Databricks, Google, Foursquare, and Amazon. She graduated from the University of Waterloo with a bachelor's of mathematics degree in computer science. Other than software, she enjoys playing with fire and hula hoops, and welding.

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Krishna Sankar

Krishna Sankar

Krishna Sankar is an AI data scientist with Volvo Cars focusing on autonomous vehicles. Previously, he was the chief data scientist at blackarrow, where he was focusing on optimizing user experience via inference, intelligence, and interfaces. He was the director of a data science/bioinformatics startup and also worked as a distinguished engineer at Cisco. He has been speaking at various conferences as well as guest lecturing at the Naval Postgraduate School. His other passion is Lego Robotics. You'll find him at the St.Louis FLL World Competition as the robot design judge.

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