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Apache Spark for Data Science Cookbook

You're reading from   Apache Spark for Data Science Cookbook Solve real-world analytical problems

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Product type Paperback
Published in Dec 2016
Publisher
ISBN-13 9781785880100
Length 392 pages
Edition 1st Edition
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Authors (2):
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Padma Priya Chitturi Padma Priya Chitturi
Author Profile Icon Padma Priya Chitturi
Padma Priya Chitturi
Nagamallikarjuna Inelu Nagamallikarjuna Inelu
Author Profile Icon Nagamallikarjuna Inelu
Nagamallikarjuna Inelu
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Table of Contents (11) Chapters Close

Preface 1. Big Data Analytics with Spark 2. Tricky Statistics with Spark FREE CHAPTER 3. Data Analysis with Spark 4. Clustering, Classification, and Regression 5. Working with Spark MLlib 6. NLP with Spark 7. Working with Sparkling Water - H2O 8. Data Visualization with Spark 9. Deep Learning on Spark 10. Working with SparkR

Creating plots with the lightning visualization server


Lightning is a framework for interactive data visualization, including a server, visualizations, and client libraries. The lightning server provides API-based access to reproducible, web-based visualizations. It includes a core set of visualization types, but is built for extendibility and customization. It can be deployed in many ways, including Heroku, Docker, a public server, a local app for OS X and even a serverless version well suited to notebooks such as Jupyter.

Lightning can expose a single visualization to all the languages of data science. Client libraries are available in multiple languages, including Python, Scala, JavaScript, and rstats, with many more in future.

Getting ready

To step through this recipe, you will need a running Spark Cluster in any one of the modes, that is, local, standalone, YARN, or Mesos. Install Hadoop (optionally), Scala, and Java. Lightning is designed to support a variety of use cases. The first option...

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