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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

Pointing to an external Spark Cluster


Running Zeppelin with built-in Spark is all good, but in most of our cases, we'll be executing the Spark jobs initiated by Zeppelin on a cluster of workers. Achieving this is pretty simple: we need to configure Zeppelin to point its Spark master property to an external Spark master URL. Let's take for example a simple and standalone external Spark cluster running on my local machine. Please note that we will have to run Zeppelin on a different port because of the Zeppelin UI port's conflict with the Spark standalone cluster master web UI over 8080.

Let's bring up the Spark Cluster. From inside your Spark source, execute the following:

sbin/start-all.sh

How to do it…

  1. Finally, let's modify conf/interpreter.json and conf/zeppelin-env.sh to point the master property to the host on which the Spark VM is running. In this case, it will be my localhost, with the port being 7077, which is the default master port:

  2. The conf/interpreter.json file looks like the following...

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