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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

iPython


Finally, let's fire up iPython and interact with the SparkContext object. As mentioned in Chapter 3, Building and Running a Spark Application, refer to the iPython site (http://jupyter.readthedocs.org/en/latest/install.html) for installing the Jupyter and iPython system.

First, change the directory to fdps-v3, where you would have downloaded the code and data for this book:

cd ~/fdps-v3

The command to start iPython is as follows:

PYSPARK_DRIVER_PYTHON=ipython PYSPARK_DRIVER_PYTHON_OPTS="notebook" ~/Downloads/spark-2.0.0/bin/pyspark

The iPython notebook will be launched in the web browser, as shown in the following screenshot, and you will see a list of iPython notebooks:

Click on the 000-PreFlightCheck.ipynb notebook:

Run the first cell using Shift + Enter. You will see the results, including the Python version, Spark version, and so on, as shown in the preceding screenshot. The notebook has more cells, which we will see in the next few chapters.

Now that you are able to create a...

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