https://github.com/radanalyticsio/base-notebook
An image for running Jupyter notebooks and Apache Spark in the cloud on OpenShift
https://github.com/radanalyticsio/base-notebook
apache-spark data-science jupyter-notebook notebook openshift
Last synced: about 1 year ago
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An image for running Jupyter notebooks and Apache Spark in the cloud on OpenShift
- Host: GitHub
- URL: https://github.com/radanalyticsio/base-notebook
- Owner: radanalyticsio
- Created: 2017-03-30T15:24:27.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2019-03-14T23:26:49.000Z (over 7 years ago)
- Last Synced: 2025-03-22T04:02:09.768Z (over 1 year ago)
- Topics: apache-spark, data-science, jupyter-notebook, notebook, openshift
- Language: Shell
- Homepage: https://radanalytics.io
- Size: 16.6 KB
- Stars: 4
- Watchers: 4
- Forks: 15
- Open Issues: 14
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Metadata Files:
- Readme: README.md
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README
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# base-notebook
This is a container image intended to make it easy to run Jupyter notebooks with Apache Spark on OpenShift. You can use it as-is (by adding it to a project), or you can use it as the basis for another image. In the latter case, you'll probably want to add some notebooks, data, and/or additional packages to the derived image.
## Usage
### As a standalone image
For your convenience, binary image builds are available from Docker Hub.
* Add the image `radanalyticsio/base-notebook` to an OpenShift project.
* Set `JUPYTER_NOTEBOOK_PASSWORD` in the pod environment to something you can remember (this step is optional but highly recommended; if you don't do this, you'll need to trawl the logs for an access token for your new notebook).
* Create a route to the pod.
### As a base image
* As `nbuser` (uid 1011), add notebooks to `/notebooks` and data to `/data`.
* This process should be easier in the future; stay tuned!
## Notes
Make sure that this notebook image is running the same version of Spark as the external cluster you want to connect it to.
## Credits
This image was initially based on [Graham Dumpleton's images](https://github.com/getwarped/jupyter-stacks), which have some additional functionality (notably s2i support) that we'd like to incorporate in the future.