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Hands-On Big Data Analytics with PySpark

You're reading from   Hands-On Big Data Analytics with PySpark Analyze large datasets and discover techniques for testing, immunizing, and parallelizing Spark jobs

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Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781838644130
Length 182 pages
Edition 1st Edition
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Authors (3):
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James Cross James Cross
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James Cross
Bartłomiej Potaczek Bartłomiej Potaczek
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Bartłomiej Potaczek
Rudy Lai Rudy Lai
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Rudy Lai
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Toc

Table of Contents (15) Chapters Close

Preface 1. Installing Pyspark and Setting up Your Development Environment FREE CHAPTER 2. Getting Your Big Data into the Spark Environment Using RDDs 3. Big Data Cleaning and Wrangling with Spark Notebooks 4. Aggregating and Summarizing Data into Useful Reports 5. Powerful Exploratory Data Analysis with MLlib 6. Putting Structure on Your Big Data with SparkSQL 7. Transformations and Actions 8. Immutable Design 9. Avoiding Shuffle and Reducing Operational Expenses 10. Saving Data in the Correct Format 11. Working with the Spark Key/Value API 12. Testing Apache Spark Jobs 13. Leveraging the Spark GraphX API 14. Other Books You May Enjoy

Setting up Spark on Windows and PySpark

Complete the following steps to install PySpark on a Windows machine:

  1. Download Gnu on Windows (GOW) from https://github.com/bmatzelle/gow/releases/download/v0.8.0/Gow-0.8.0.exe.
  2. GOW allows the use of Linux commands on Windows. We can use the following command to see the basic Linux commands allowed by installing GOW:
gow --list

This gives the following output:

  1. Download and install Anaconda. If you need help, you can go through the following tutorial: https://medium.com/@GalarnykMichael/install-python-on-windows-anaconda-c63c7c3d1444.
  2. Close the previous command line and open a new command line.
  3. Go to the Apache Spark website (https://spark.apache.org/).
  4. To download Spark, choose the following from the drop-down menu:
    • A recent Spark release
    • A proper package type

The following screenshot shows the download page of Apache Spark:

  1. Then, download Spark. Once it is downloaded, move the file to the folder where you want to unzip it.
  2. You can either unzip it manually or use the following commands:
gzip -d spark-2.1.0-bin-hadoop2.7.tgz
tar xvf spark-2.1.0-bin-hadoop2.7.tar
  1. Now, download winutils.exe into your spark-2.1.0-bin-hadoop2.7\bin folder using the following command:
curl -k -L -o winutils.exe https://github.com/steveloughran/winutils/blob/master/hadoop-2.6.0/bin/winutils.exe?raw=true
  1. Make sure you have Java installed on your machine. You can use the following command to see the Java version:
java --version

This gives the following output:

  1. Check for the Python version by using the following command:
python --version 

This gives the following output:

  1. Let's edit our environmental variables so that we can open Spark in any directory, as follows:
setx SPARK_HOME C:\opt\spark\spark-2.1.0-bin-hadoop2.7
setx HADOOP_HOME C:\opt\spark\spark-2.1.0-bin-hadoop2.7
setx PYSPARK_DRIVER_PYTHON ipython
setx PYSPARK_DRIVER_PYTHON_OPTS notebook

Add C:\opt\spark\spark-2.1.0-bin-hadoop2.7\bin to your path.

  1. Close the Terminal, open a new one, and type the following command:
--master local[2]
The PYSPARK_DRIVER_PYTHON and the PYSPARK_DRIVER_PYTHON_OPTS parameters are used to launch the PySpark shell in Jupyter Notebook. The --master parameter is used for setting the master node address.
  1. The next thing to do is to run the PySpark command in the bin folder:
.\bin\pyspark

This gives the following output:

You have been reading a chapter from
Hands-On Big Data Analytics with PySpark
Published in: Mar 2019
Publisher: Packt
ISBN-13: 9781838644130
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