This post will quickly cover how to connect an ipython notebook to two kinds of Spark Clusters: Spark Cluster running in Standalone mode and a Spark Cluster running on Amazon EC2.
Table of Contents
- What is ipython?
- Is iPython still relevant?
- Why is Jupyter better than ipython for Spark?
- Connecting ipython notebook to an Apache Spark Standalone Cluster
- Connecting an ipython notebook to an Apache Spark Cluster running on EC2
What is ipython?
An interactive computing environment called IPython Notebook enables users to create and share documents with real-time code, equations, visuals, and text. It offers a web-based interface for the IPython interpreter and the Python programming language.
The notebook interface is divided into cells, each of which can hold text or program code. Text cells can be used to create documentation or notes, while code cells let users write and run Python programs. The LaTeX syntax allows users to add mathematical equations to their notebooks.
Is iPython still relevant?
Jupyter Notebook, which supports numerous programming languages including Python, R, Julia, and others similar to ipython, has now preferred over IPython Notebook.
Why is Jupyter better than ipython for Spark?
The successor to IPython Notebook, Jupyter Notebook, features a number of enhancements and advantages.
- Jupyter Notebook supports more than 40 programming languages, including R, Julia, and Scala, in contrast to IPython Notebook, which was created solely for Python.
- Jupyter Notebook offers a more user-friendly and intuitive interface than IPython Notebook. To make it simpler to use and navigate, the notebook interface has been updated.
- Improved cell execution is possible with Jupyter Notebook compared to IPython Notebook. It offers better error messages and debugging tools, and it can handle more intricate and time-consuming computations.
- More adaptable architecture: Jupyter Notebook’s architecture is more adaptable than IPython Notebook’s. It is compatible with GitHub and Docker and can be used locally or in the cloud. It can also be linked with other programs and services.
- Active maintenance: Jupyter Notebook is continuously updated and developed, but IPython Notebook is no longer updated.
Generally, Jupyter Notebook is a more robust and functional tool than IPython Notebook and is advised for use instead of iPython.
But if you still want to continue with iPython notebook with Spark….
iPython Notebook with Spark Requirements
You need to have a Spark Cluster Standalone and Apache Spark Cluster running to complete this tutorial. See the Background section of this post for further information and helpful references.
Connecting ipython notebook to an Apache Spark Standalone Cluster
Connecting to the Spark Cluster from ipython notebook is easy. Simply set the master environment variable when calling pyspark, for example:
IPYTHON_OPTS=”notebook” ./bin/pyspark –master spark://todd-mcgraths-macbook-pro.local:7077
Run a version or some function off of sc. There’s really know way I know of to programmatically determine if we are truly running ipython notebook against the Spark cluster. But, we can verify from the Spark Web UI:
Connecting an ipython notebook to an Apache Spark Cluster running on EC2
Using pyspark against a remote cluster is just as easy. Just pass in the appropriate URL to the –master argument.
IPYTHON_OPTS=”notebook” ./bin/pyspark –master spark://ec2-54-198-139-10.compute-1.amazonaws.com:7077
Conclusion
As you saw in this tutorial, connecting to a standalone cluster or spark cluster running on EC2 is essentially the same. It’s easy. The difficult part of connecting to a Spark cluster happens beforehand. Check the next section on Background Information to help setup your Apache Spark Cluster and/or connection ipython notebook to a spark cluster.
Background Information or Possibly Helpful References
1) How to use ipython notebook with Spark: Apache Spark and ipython notebook – The Easy Way
2) Apache Spark Cluster in Standalone tutorial, you learned how to run a Spark Standalone cluster. In addition, you learned how to connect the Scala console to utilize this cluster.
3) Running an Apache Spark Cluster on EC2
4) More on iPython — https://en.wikipedia.org/wiki/IPython
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