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Apache Spark for Data Science Cookbook

You're reading from  Apache Spark for Data Science Cookbook

Product type Book
Published in Dec 2016
Publisher
ISBN-13 9781785880100
Pages 392 pages
Edition 1st Edition
Languages
Author (1):
Padma Priya Chitturi Padma Priya Chitturi
Profile icon Padma Priya Chitturi

Table of Contents (17) Chapters

Apache Spark for Data Science Cookbook
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
Big Data Analytics with Spark Tricky Statistics with Spark Data Analysis with Spark Clustering, Classification, and Regression Working with Spark MLlib NLP with Spark Working with Sparkling Water - H2O Data Visualization with Spark Deep Learning on Spark Working with SparkR

Visualizing data on HDFS - parameterizing inputs


Once we start the service, we can point our browser to http://localhost:8080 (change the port as per your modified port configuration) to view the Zeppelin UI. Zeppelin organizes its contents as notes and paragraphs. A note is simply a list of all the paragraphs on a single web page.

Using data from HDFS simply means that we point to the HDFS location instead of the local file system location. Before we consume the file from HDFS, let's quickly check the Spark version that Zeppelin uses. This can be achieved by issuing sc.version on a paragraph. The sc variable is an implicit variable representing the SparkContext inside Zeppelin, which simply means that we need not programmatically create a SparkContext within Zeppelin:

sc.version 
res0: String = 1.6.0

Let's load the sample file profiles.json, convert it into a DataFrame, and print the schema and the first 20 rows (show) for verification. Let's also finally register the DataFrame as a...

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