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Upgrade to Python 3.x
Download and install Python
3.x . For this tutorial I have used 3.5 .
Once you downloaded and run the installation app, Python 3 will be installed under:
The installer also adds the path for the above to your default path in
.bash_profile so that when you type:
Jupyter Notebook
on the command line, the system can find it. You'll know you've been successful if you see the Python interpreter launch.
Install pip
Fire up your Terminal and type:
Install PySpark on Mac
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Next, we will edit our
.bash_profile so we can open a spark notebook in any directory. So fire up your Terminal and type in:
my
.bash_profile looks as follows:
The relevant stuff is:
The
PYSPARK_DRIVER_PYTHON parameter and the PYSPARK_DRIVER_PYTHON_OPTS parameter are used to launch the PySpark shell in Jupyter Notebook. The --master parameter is used for setting the master node address. Here we launch Spark locally on 2 cores for local testing.
Install Jupyter Notebook with pip
First, ensure that you have the latest pip; older versions may have trouble with some dependencies:
Then install the Jupyter Notebook using:
Thats it!
You can now run:
in the command line. A browser window should open with Jupyter Notebook running under http://localhost:8888/ https://yellowsilk944.weebly.com/blog/solidworks-mac-free-download-crack.
Configure Jupyter Notebook to show line numbers
Run
to get the Jupyter config directory. Mine is located under
/Users/lucas/.jupyter .Run:
Run:
to create a
custom directory (if does not already exist).Run:
Run:
and add:
You could add any javascript. It will be executed by the ipython notebook at load time.
Install a Java 9 Kernel
Install Java 9. Java home is then:
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Install kulla.jar. I have installed it under
~/opt/ .
Download the kernel. Again, I placed the entire
javakernel directory under ~/opt/ .
This kernel expects two environment variables defined, which can be set in the kernel.json (described below):
So go ahead and edit
kernel.json in the kernel you have just download to look as follows: Reason 5 keygen mac download.
Run:
Run:
Run:
to copy the edited
kernel.json into the newly created java directory.
Install
gnureadline by running:
in the commoand line.
If all worked you should be able to run the kernel:
and see the following output:
Whether it’s for social science, marketing, business intelligence or something else, the number of times data analysis benefits from heavy duty parallelization is growing all the time.
Apache Spark is an awesome platform for big data analysis, so getting to know how it works and how to use it is probably a good idea. Setting up your own cluster, administering it etc. etc. is a bit of a hassle to just learn the basics though (although Amazon EMR or Databricks make that quite easy, and you can even build your own Raspberry Pi cluster if you want…), so getting Spark and Pyspark running on your local machine seems like a better idea. You can also use Spark with
R and Scala, among others, but I have no experience with how to set that up. So, we’ll stick to Pyspark in this guide.
While dipping my toes into the water I noticed that all the guides I could find online weren’t entirely transparent, so I’ve tried to compile the steps I actually did to get this up and running here. The original guides I’m working from are here, here and here.
Pre-requesites
Before we can actually install Spark and Pyspark, there are a few things that need to be present on your machine.
You need:
Installing the XCode Developer Tools
Installing homebrewDownload Jupyter Notebook For Mac
Installing Pipenv
If that doesn’t work for some reason, you can do the following:
Download Jupyter Notebook For Mac Free
This does a pip user install, which puts pipenv in your home directory. If pipenv isn’t available in your shell after installation, you need to add stuff to you
PATH . Here’s pipenv’s guide on how to do that.
Installing Java
To run, Spark needs Java installed on your system. It’s important that you do not install Java with
brew for uninteresting reasons.Just go here to download Java for your Mac and follow the instructions.
You can confirm Java is installed by typing
$ java --showversion in Terminal.
Installing Spark
With the pre-requisites in place, you can now install Apache Spark on your Mac.
Installing Pyspark
I recommend that you install Pyspark in your own virtual environment using
pipenv to keep things clean and separated.
Your
~/.bashrc or ~/.zshrc should now have a section that looks kinda like this:
Now you save the file, and source your Terminal:
To start Pyspark and open up Jupyter, you can simply run
$ pyspark . You only need to make sure you’re inside your pipenv environment. That means:
Using Pyspark inside your Jupyter Notebooks
To test whether Pyspark is running as it is supposed to, put the following code into a new notebook and run it:
(You might need to install
numpy inside your pipenv environment if you haven’t already done so without my instruction ?)
If you get an error along the lines of
sc is not defined , you need to add sc = SparkContext.getOrCreate() at the top of the cell. If things are still not working, make sure you followed the installation instructions closely.Still no luck? Send me an email if you want (I most definitely can’t guarantee that I know how to fix your problem), particularly if you find a bug and figure out how to make it work! RelatedComments are closed.
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December 2020
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