The Docker container executes a [`start-notebook.sh` script](./start-notebook.sh) script by default. The `start-notebook.sh` script handles the `NB_UID`, `NB_GID` and `GRANT_SUDO` features documented in the next section, and then executes the `jupyter notebook`.
The Docker container executes a `start-notebook.sh` script script by default. The `start-notebook.sh` script handles the `NB_UID`, `NB_GID` and `GRANT_SUDO` features documented in the next section, and then executes the `jupyter notebook`.
You can pass [Jupyter command line options](https://jupyter.readthedocs.io/en/latest/projects/jupyter-command.html) through the `start-notebook.sh` script when launching the container. For example, to secure the Notebook server with a custom password hashed using `IPython.lib.passwd()` instead of the default token, run the following:
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@@ -101,9 +101,9 @@ You can bypass the provided scripts and specify your an arbitrary start command.
## Image Specifics
## Spark and PySpark
### Spark and PySpark
### Using Spark Local Mode
#### Using Spark Local Mode
This configuration is nice for using Spark on small, local data.
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@@ -166,9 +166,9 @@ To use Python 2 in the notebook and on the workers, change the `PYSPARK_PYTHON`
Of course, all of this can be hidden in an [IPython kernel startup script](http://ipython.org/ipython-doc/stable/development/config.html?highlight=startup#startup-files), but "explicit is better than implicit." :)
## Connecting to a Spark Cluster on Standalone Mode
#### Connecting to a Spark Cluster in Standalone Mode
Connection to Spark Cluster on Standalone Mode requires the following set of steps:
Connection to Spark Cluster in Standalone Mode requires the following set of steps:
0. Verify that the docker image (check the Dockerfile) and the Spark Cluster which is being deployed, run the same version of Spark.
1.[Deploy Spark on Standalone Mode](http://spark.apache.org/docs/latest/spark-standalone.html).
@@ -9,7 +9,7 @@ Jupyter Docker Stacks are a set of ready-to-run Docker images containing Jupyter
:maxdepth: 1
using
features
configuration
contributing
Quick Start
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@@ -18,19 +18,19 @@ Quick Start
The examples below may help you get started if you have Docker installed, know which Docker image you want to use, and want to launch a single Jupyter Notebook server in a container. The other pages in this documentation describe additional uses and features in detail.::
# Run a Jupyter Notebook server in a Docker container started
# from the jupyter/scipy-notebook image built from Git commit 27ba573.
# from the jupyter/scipy-notebook image built from Git commit 2c80cf3537ca.
# All files saved in the container are lost when the notebook server exits.
# -ti: pseudo-TTY+STDIN open, so the logs appear in the terminal
# -rm: remove the container on exit
# -p: publish the notebook port 8888 as port 8888 on the host
docker run -ti --rm -p 8888:8888 jupyter/scipy-notebook:27ba573
docker run -ti --rm -p 8888:8888 jupyter/scipy-notebook:2c80cf3537ca
# Run a Jupyter Notebook server in a Docker container started from the
# jupyter/r-notebook image built from Git commit cf1a3aa.
# jupyter/r-notebook image built from Git commit e5c5a7d3e52d.
# All files written to ~/work in the container are saved to the
# current working on the host and persist even when the notebook server
# exits.
docker run -ti --rm -p 8888:8888 -v "$PWD":/home/jovyan/work jupyter/r-notebook:cf1a3aa
docker run -ti --rm -p 8888:8888 -v "$PWD":/home/jovyan/work jupyter/r-notebook:e5c5a7d3e52d
# Run a Jupyter Notebook server in a background Docker container started
# from the latest jupyter/all-spark-notebook image available on the local
